v1

package
v0.16.0 Latest Latest
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 Go to latest Published: Mar 11, 2022 License: Apache-2.0 Imports: 7 Imported by: 0

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Index

Constants

View Source 
const (
	// Goal Type will default to maximize.
	GoogleCloudMlV1_StudyConfig_MetricSpecGoalGoalTypeUnspecified = GoogleCloudMlV1_StudyConfig_MetricSpecGoal("GOAL_TYPE_UNSPECIFIED")
	// Maximize the goal metric.
	GoogleCloudMlV1_StudyConfig_MetricSpecGoalMaximize = GoogleCloudMlV1_StudyConfig_MetricSpecGoal("MAXIMIZE")
	// Minimize the goal metric.
	GoogleCloudMlV1_StudyConfig_MetricSpecGoalMinimize = GoogleCloudMlV1_StudyConfig_MetricSpecGoal("MINIMIZE")
)
View Source 
const (
	// By default, no scaling is applied.
	GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeScaleTypeUnspecified = GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType("SCALE_TYPE_UNSPECIFIED")
	// Scales the feasible space to (0, 1) linearly.
	GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeUnitLinearScale = GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType("UNIT_LINEAR_SCALE")
	// Scales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.
	GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeUnitLogScale = GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType("UNIT_LOG_SCALE")
	// Scales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.
	GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeUnitReverseLogScale = GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType("UNIT_REVERSE_LOG_SCALE")
)
View Source 
const (
	// You must specify a valid type. Using this unspecified type will result in an error.
	GoogleCloudMlV1_StudyConfig_ParameterSpecTypeParameterTypeUnspecified = GoogleCloudMlV1_StudyConfig_ParameterSpecType("PARAMETER_TYPE_UNSPECIFIED")
	// Type for real-valued parameters.
	GoogleCloudMlV1_StudyConfig_ParameterSpecTypeDouble = GoogleCloudMlV1_StudyConfig_ParameterSpecType("DOUBLE")
	// Type for integral parameters.
	GoogleCloudMlV1_StudyConfig_ParameterSpecTypeInteger = GoogleCloudMlV1_StudyConfig_ParameterSpecType("INTEGER")
	// The parameter is categorical, with a value chosen from the categories field.
	GoogleCloudMlV1_StudyConfig_ParameterSpecTypeCategorical = GoogleCloudMlV1_StudyConfig_ParameterSpecType("CATEGORICAL")
	// The parameter is real valued, with a fixed set of feasible points. If `type==DISCRETE`, feasible_points must be provided, and {`min_value`, `max_value`} will be ignored.
	GoogleCloudMlV1_StudyConfig_ParameterSpecTypeDiscrete = GoogleCloudMlV1_StudyConfig_ParameterSpecType("DISCRETE")
)
View Source 
const (
	// Unspecified accelerator type. Default to no GPU.
	GoogleCloudMlV1__AcceleratorConfigTypeAcceleratorTypeUnspecified = GoogleCloudMlV1__AcceleratorConfigType("ACCELERATOR_TYPE_UNSPECIFIED")
	// Nvidia Tesla K80 GPU.
	GoogleCloudMlV1__AcceleratorConfigTypeNvidiaTeslaK80 = GoogleCloudMlV1__AcceleratorConfigType("NVIDIA_TESLA_K80")
	// Nvidia Tesla P100 GPU.
	GoogleCloudMlV1__AcceleratorConfigTypeNvidiaTeslaP100 = GoogleCloudMlV1__AcceleratorConfigType("NVIDIA_TESLA_P100")
	// Nvidia V100 GPU.
	GoogleCloudMlV1__AcceleratorConfigTypeNvidiaTeslaV100 = GoogleCloudMlV1__AcceleratorConfigType("NVIDIA_TESLA_V100")
	// Nvidia Tesla P4 GPU.
	GoogleCloudMlV1__AcceleratorConfigTypeNvidiaTeslaP4 = GoogleCloudMlV1__AcceleratorConfigType("NVIDIA_TESLA_P4")
	// Nvidia T4 GPU.
	GoogleCloudMlV1__AcceleratorConfigTypeNvidiaTeslaT4 = GoogleCloudMlV1__AcceleratorConfigType("NVIDIA_TESLA_T4")
	// Nvidia A100 GPU.
	GoogleCloudMlV1__AcceleratorConfigTypeNvidiaTeslaA100 = GoogleCloudMlV1__AcceleratorConfigType("NVIDIA_TESLA_A100")
	// TPU v2.
	GoogleCloudMlV1__AcceleratorConfigTypeTpuV2 = GoogleCloudMlV1__AcceleratorConfigType("TPU_V2")
	// TPU v3.
	GoogleCloudMlV1__AcceleratorConfigTypeTpuV3 = GoogleCloudMlV1__AcceleratorConfigType("TPU_V3")
	// TPU v2 POD.
	GoogleCloudMlV1__AcceleratorConfigTypeTpuV2Pod = GoogleCloudMlV1__AcceleratorConfigType("TPU_V2_POD")
	// TPU v3 POD.
	GoogleCloudMlV1__AcceleratorConfigTypeTpuV3Pod = GoogleCloudMlV1__AcceleratorConfigType("TPU_V3_POD")
)
View Source 
const (
	// The default algorithm used by the hyperparameter tuning service. This is a Bayesian optimization algorithm.
	GoogleCloudMlV1__HyperparameterSpecAlgorithmAlgorithmUnspecified = GoogleCloudMlV1__HyperparameterSpecAlgorithm("ALGORITHM_UNSPECIFIED")
	// Simple grid search within the feasible space. To use grid search, all parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.
	GoogleCloudMlV1__HyperparameterSpecAlgorithmGridSearch = GoogleCloudMlV1__HyperparameterSpecAlgorithm("GRID_SEARCH")
	// Simple random search within the feasible space.
	GoogleCloudMlV1__HyperparameterSpecAlgorithmRandomSearch = GoogleCloudMlV1__HyperparameterSpecAlgorithm("RANDOM_SEARCH")
)
View Source 
const (
	// Goal Type will default to maximize.
	GoogleCloudMlV1__HyperparameterSpecGoalGoalTypeUnspecified = GoogleCloudMlV1__HyperparameterSpecGoal("GOAL_TYPE_UNSPECIFIED")
	// Maximize the goal metric.
	GoogleCloudMlV1__HyperparameterSpecGoalMaximize = GoogleCloudMlV1__HyperparameterSpecGoal("MAXIMIZE")
	// Minimize the goal metric.
	GoogleCloudMlV1__HyperparameterSpecGoalMinimize = GoogleCloudMlV1__HyperparameterSpecGoal("MINIMIZE")
)
View Source 
const (
	// Unspecified MetricName.
	GoogleCloudMlV1__MetricSpecNameMetricNameUnspecified = GoogleCloudMlV1__MetricSpecName("METRIC_NAME_UNSPECIFIED")
	// CPU usage.
	GoogleCloudMlV1__MetricSpecNameCpuUsage = GoogleCloudMlV1__MetricSpecName("CPU_USAGE")
	// GPU duty cycle.
	GoogleCloudMlV1__MetricSpecNameGpuDutyCycle = GoogleCloudMlV1__MetricSpecName("GPU_DUTY_CYCLE")
)
View Source 
const (
	// By default, no scaling is applied.
	GoogleCloudMlV1__ParameterSpecScaleTypeNone = GoogleCloudMlV1__ParameterSpecScaleType("NONE")
	// Scales the feasible space to (0, 1) linearly.
	GoogleCloudMlV1__ParameterSpecScaleTypeUnitLinearScale = GoogleCloudMlV1__ParameterSpecScaleType("UNIT_LINEAR_SCALE")
	// Scales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.
	GoogleCloudMlV1__ParameterSpecScaleTypeUnitLogScale = GoogleCloudMlV1__ParameterSpecScaleType("UNIT_LOG_SCALE")
	// Scales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.
	GoogleCloudMlV1__ParameterSpecScaleTypeUnitReverseLogScale = GoogleCloudMlV1__ParameterSpecScaleType("UNIT_REVERSE_LOG_SCALE")
)
View Source 
const (
	// You must specify a valid type. Using this unspecified type will result in an error.
	GoogleCloudMlV1__ParameterSpecTypeParameterTypeUnspecified = GoogleCloudMlV1__ParameterSpecType("PARAMETER_TYPE_UNSPECIFIED")
	// Type for real-valued parameters.
	GoogleCloudMlV1__ParameterSpecTypeDouble = GoogleCloudMlV1__ParameterSpecType("DOUBLE")
	// Type for integral parameters.
	GoogleCloudMlV1__ParameterSpecTypeInteger = GoogleCloudMlV1__ParameterSpecType("INTEGER")
	// The parameter is categorical, with a value chosen from the categories field.
	GoogleCloudMlV1__ParameterSpecTypeCategorical = GoogleCloudMlV1__ParameterSpecType("CATEGORICAL")
	// The parameter is real valued, with a fixed set of feasible points. If `type==DISCRETE`, feasible_points must be provided, and {`min_value`, `max_value`} will be ignored.
	GoogleCloudMlV1__ParameterSpecTypeDiscrete = GoogleCloudMlV1__ParameterSpecType("DISCRETE")
)
View Source 
const (
	// Unspecified format.
	GoogleCloudMlV1__PredictionInputDataFormatDataFormatUnspecified = GoogleCloudMlV1__PredictionInputDataFormat("DATA_FORMAT_UNSPECIFIED")
	// Each line of the file is a JSON dictionary representing one record.
	GoogleCloudMlV1__PredictionInputDataFormatJson = GoogleCloudMlV1__PredictionInputDataFormat("JSON")
	// Deprecated. Use JSON instead.
	GoogleCloudMlV1__PredictionInputDataFormatText = GoogleCloudMlV1__PredictionInputDataFormat("TEXT")
	// The source file is a TFRecord file. Currently available only for input data.
	GoogleCloudMlV1__PredictionInputDataFormatTfRecord = GoogleCloudMlV1__PredictionInputDataFormat("TF_RECORD")
	// The source file is a GZIP-compressed TFRecord file. Currently available only for input data.
	GoogleCloudMlV1__PredictionInputDataFormatTfRecordGzip = GoogleCloudMlV1__PredictionInputDataFormat("TF_RECORD_GZIP")
	// Values are comma-separated rows, with keys in a separate file. Currently available only for output data.
	GoogleCloudMlV1__PredictionInputDataFormatCsv = GoogleCloudMlV1__PredictionInputDataFormat("CSV")
)
View Source 
const (
	// Unspecified format.
	GoogleCloudMlV1__PredictionInputOutputDataFormatDataFormatUnspecified = GoogleCloudMlV1__PredictionInputOutputDataFormat("DATA_FORMAT_UNSPECIFIED")
	// Each line of the file is a JSON dictionary representing one record.
	GoogleCloudMlV1__PredictionInputOutputDataFormatJson = GoogleCloudMlV1__PredictionInputOutputDataFormat("JSON")
	// Deprecated. Use JSON instead.
	GoogleCloudMlV1__PredictionInputOutputDataFormatText = GoogleCloudMlV1__PredictionInputOutputDataFormat("TEXT")
	// The source file is a TFRecord file. Currently available only for input data.
	GoogleCloudMlV1__PredictionInputOutputDataFormatTfRecord = GoogleCloudMlV1__PredictionInputOutputDataFormat("TF_RECORD")
	// The source file is a GZIP-compressed TFRecord file. Currently available only for input data.
	GoogleCloudMlV1__PredictionInputOutputDataFormatTfRecordGzip = GoogleCloudMlV1__PredictionInputOutputDataFormat("TF_RECORD_GZIP")
	// Values are comma-separated rows, with keys in a separate file. Currently available only for output data.
	GoogleCloudMlV1__PredictionInputOutputDataFormatCsv = GoogleCloudMlV1__PredictionInputOutputDataFormat("CSV")
)
View Source 
const (
	// The default algorithm used by the Cloud AI Platform Vizier service.
	GoogleCloudMlV1__StudyConfigAlgorithmAlgorithmUnspecified = GoogleCloudMlV1__StudyConfigAlgorithm("ALGORITHM_UNSPECIFIED")
	// Gaussian Process Bandit.
	GoogleCloudMlV1__StudyConfigAlgorithmGaussianProcessBandit = GoogleCloudMlV1__StudyConfigAlgorithm("GAUSSIAN_PROCESS_BANDIT")
	// Simple grid search within the feasible space. To use grid search, all parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`.
	GoogleCloudMlV1__StudyConfigAlgorithmGridSearch = GoogleCloudMlV1__StudyConfigAlgorithm("GRID_SEARCH")
	// Simple random search within the feasible space.
	GoogleCloudMlV1__StudyConfigAlgorithmRandomSearch = GoogleCloudMlV1__StudyConfigAlgorithm("RANDOM_SEARCH")
)
View Source 
const (
	// A single worker instance. This tier is suitable for learning how to use Cloud ML, and for experimenting with new models using small datasets.
	GoogleCloudMlV1__TrainingInputScaleTierBasic = GoogleCloudMlV1__TrainingInputScaleTier("BASIC")
	// Many workers and a few parameter servers.
	GoogleCloudMlV1__TrainingInputScaleTierStandard1 = GoogleCloudMlV1__TrainingInputScaleTier("STANDARD_1")
	// A large number of workers with many parameter servers.
	GoogleCloudMlV1__TrainingInputScaleTierPremium1 = GoogleCloudMlV1__TrainingInputScaleTier("PREMIUM_1")
	// A single worker instance [with a GPU](/ai-platform/training/docs/using-gpus).
	GoogleCloudMlV1__TrainingInputScaleTierBasicGpu = GoogleCloudMlV1__TrainingInputScaleTier("BASIC_GPU")
	// A single worker instance with a [Cloud TPU](/ml-engine/docs/tensorflow/using-tpus).
	GoogleCloudMlV1__TrainingInputScaleTierBasicTpu = GoogleCloudMlV1__TrainingInputScaleTier("BASIC_TPU")
	// The CUSTOM tier is not a set tier, but rather enables you to use your own cluster specification. When you use this tier, set values to configure your processing cluster according to these guidelines: * You _must_ set `TrainingInput.masterType` to specify the type of machine to use for your master node. This is the only required setting. * You _may_ set `TrainingInput.workerCount` to specify the number of workers to use. If you specify one or more workers, you _must_ also set `TrainingInput.workerType` to specify the type of machine to use for your worker nodes. * You _may_ set `TrainingInput.parameterServerCount` to specify the number of parameter servers to use. If you specify one or more parameter servers, you _must_ also set `TrainingInput.parameterServerType` to specify the type of machine to use for your parameter servers. Note that all of your workers must use the same machine type, which can be different from your parameter server type and master type. Your parameter servers must likewise use the same machine type, which can be different from your worker type and master type.
	GoogleCloudMlV1__TrainingInputScaleTierCustom = GoogleCloudMlV1__TrainingInputScaleTier("CUSTOM")
)
View Source 
const (
	// Default case. Should never be this.
	GoogleIamV1__AuditLogConfigLogTypeLogTypeUnspecified = GoogleIamV1__AuditLogConfigLogType("LOG_TYPE_UNSPECIFIED")
	// Admin reads. Example: CloudIAM getIamPolicy
	GoogleIamV1__AuditLogConfigLogTypeAdminRead = GoogleIamV1__AuditLogConfigLogType("ADMIN_READ")
	// Data writes. Example: CloudSQL Users create
	GoogleIamV1__AuditLogConfigLogTypeDataWrite = GoogleIamV1__AuditLogConfigLogType("DATA_WRITE")
	// Data reads. Example: CloudSQL Users list
	GoogleIamV1__AuditLogConfigLogTypeDataRead = GoogleIamV1__AuditLogConfigLogType("DATA_READ")
)
View Source 
const (
	// The trial state is unspecified.
	TrialStateEnumStateUnspecified = TrialStateEnum("STATE_UNSPECIFIED")
	// Indicates that a specific trial has been requested, but it has not yet been suggested by the service.
	TrialStateEnumRequested = TrialStateEnum("REQUESTED")
	// Indicates that the trial has been suggested.
	TrialStateEnumActive = TrialStateEnum("ACTIVE")
	// Indicates that the trial is done, and either has a final_measurement set, or is marked as trial_infeasible.
	TrialStateEnumCompleted = TrialStateEnum("COMPLETED")
	// Indicates that the trial should stop according to the service.
	TrialStateEnumStopping = TrialStateEnum("STOPPING")
)
View Source 
const (
	// Unspecified framework. Assigns a value based on the file suffix.
	VersionFrameworkFrameworkUnspecified = VersionFramework("FRAMEWORK_UNSPECIFIED")
	// Tensorflow framework.
	VersionFrameworkTensorflow = VersionFramework("TENSORFLOW")
	// Scikit-learn framework.
	VersionFrameworkScikitLearn = VersionFramework("SCIKIT_LEARN")
	// XGBoost framework.
	VersionFrameworkXgboost = VersionFramework("XGBOOST")
)

Variables

This section is empty.

Functions

This section is empty.

Types

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfig 

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfig struct {
	// If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
	UseElapsedTime *bool `pulumi:"useElapsedTime"`
}

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs 

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs struct {
	// If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
	UseElapsedTime pulumi.BoolPtrInput `pulumi:"useElapsedTime"`
}

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ElementType 

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput 

func (i GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutputWithContext 

func (i GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput 

func (i GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutputWithContext 

func (i GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigInput 

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput
	ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutputWithContext(context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput
}

GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigInput is an input type that accepts GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs and GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigInput` via: 

GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs{...}

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput 

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ElementType 

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutputWithContext 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutputWithContext 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) UseElapsedTime 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput) UseElapsedTime() pulumi.BoolPtrOutput

If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrInput 

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput
	ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutputWithContext(context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput
}

GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrInput is an input type that accepts GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs, GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtr and GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrInput` via: 

        GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs{...}

or:

        nil

func GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtr 

func GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtr(v *GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs) GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrInput

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput 

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) Elem 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) Elem() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) ElementType 

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutputWithContext 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) UseElapsedTime 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput) UseElapsedTime() pulumi.BoolPtrOutput

If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponse 

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponse struct {
	// If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
	UseElapsedTime bool `pulumi:"useElapsedTime"`
}

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput 

type GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput) ElementType 

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutputWithContext 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput) UseElapsedTime 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput) UseElapsedTime() pulumi.BoolOutput

If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfig 

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfig struct {
	// If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
	UseElapsedTime *bool `pulumi:"useElapsedTime"`
}

The median automated stopping rule stops a pending trial if the trial's best objective_value is strictly below the median 'performance' of all completed trials reported up to the trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the trial in each measurement.

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs 

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs struct {
	// If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
	UseElapsedTime pulumi.BoolPtrInput `pulumi:"useElapsedTime"`
}

The median automated stopping rule stops a pending trial if the trial's best objective_value is strictly below the median 'performance' of all completed trials reported up to the trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the trial in each measurement.

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ElementType 

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput 

func (i GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutputWithContext 

func (i GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput 

func (i GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutputWithContext 

func (i GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigInput 

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput
	ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutputWithContext(context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput
}

GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigInput is an input type that accepts GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs and GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigInput` via: 

GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs{...}

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput 

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput struct{ *pulumi.OutputState }

The median automated stopping rule stops a pending trial if the trial's best objective_value is strictly below the median 'performance' of all completed trials reported up to the trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the trial in each measurement.

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ElementType 

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutputWithContext 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutputWithContext 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) UseElapsedTime 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput) UseElapsedTime() pulumi.BoolPtrOutput

If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrInput 

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput
	ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutputWithContext(context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput
}

GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrInput is an input type that accepts GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs, GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtr and GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrInput` via: 

        GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs{...}

or:

        nil

func GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtr 

func GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtr(v *GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs) GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrInput

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput 

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) Elem 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) Elem() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) ElementType 

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutputWithContext 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) UseElapsedTime 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput) UseElapsedTime() pulumi.BoolPtrOutput

If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponse 

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponse struct {
	// If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
	UseElapsedTime bool `pulumi:"useElapsedTime"`
}

The median automated stopping rule stops a pending trial if the trial's best objective_value is strictly below the median 'performance' of all completed trials reported up to the trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the trial in each measurement.

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput 

type GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput struct{ *pulumi.OutputState }

The median automated stopping rule stops a pending trial if the trial's best objective_value is strictly below the median 'performance' of all completed trials reported up to the trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the trial in each measurement.

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput) ElementType 

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutputWithContext 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput

func (GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput) UseElapsedTime 

func (o GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput) UseElapsedTime() pulumi.BoolOutput

If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric struct {
	// The objective value at this training step.
	ObjectiveValue *float64 `pulumi:"objectiveValue"`
	// The global training step for this metric.
	TrainingStep *string `pulumi:"trainingStep"`
}

An observed value of a metric.

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs struct {
	// The objective value at this training step.
	ObjectiveValue pulumi.Float64PtrInput `pulumi:"objectiveValue"`
	// The global training step for this metric.
	TrainingStep pulumi.StringPtrInput `pulumi:"trainingStep"`
}

An observed value of a metric.

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ElementType 

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput 

func (i GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutputWithContext 

func (i GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutputWithContext(ctx context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput 

func (i GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutputWithContext 

func (i GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray []GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricInput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray) ElementType 

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray) ElementType() reflect.Type

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput 

func (i GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutputWithContext 

func (i GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayInput 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput
	ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutputWithContext(context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput
}

GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayInput is an input type that accepts GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray and GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayInput` via: 

GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArray{ GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs{...} }

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput) ElementType 

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput) Index 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutputWithContext 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricInput 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput
	ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutputWithContext(context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput
}

GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricInput is an input type that accepts GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs and GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput values. You can construct a concrete instance of `GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricInput` via: 

GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs{...}

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput struct{ *pulumi.OutputState }

An observed value of a metric.

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ElementType 

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ObjectiveValue 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ObjectiveValue() pulumi.Float64PtrOutput

The objective value at this training step.

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutputWithContext 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutputWithContext(ctx context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutputWithContext 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) TrainingStep 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput) TrainingStep() pulumi.StringPtrOutput

The global training step for this metric.

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrInput 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput
	ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutputWithContext(context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput
}

GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrInput is an input type that accepts GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs, GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtr and GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrInput` via: 

        GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs{...}

or:

        nil

func GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtr 

func GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtr(v *GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArgs) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrInput

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) Elem 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) Elem() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) ElementType 

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) ObjectiveValue 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) ObjectiveValue() pulumi.Float64PtrOutput

The objective value at this training step.

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutputWithContext 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) TrainingStep 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput) TrainingStep() pulumi.StringPtrOutput

The global training step for this metric.

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponse 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponse struct {
	// The objective value at this training step.
	ObjectiveValue float64 `pulumi:"objectiveValue"`
	// The global training step for this metric.
	TrainingStep string `pulumi:"trainingStep"`
}

An observed value of a metric.

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput) ElementType 

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput) Index 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutputWithContext 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput 

type GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput struct{ *pulumi.OutputState }

An observed value of a metric.

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) ElementType 

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) ObjectiveValue 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) ObjectiveValue() pulumi.Float64Output

The objective value at this training step.

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutputWithContext 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) ToGoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput

func (GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) TrainingStep 

func (o GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput) TrainingStep() pulumi.StringOutput

The global training step for this metric.

type GoogleCloudMlV1_Measurement_Metric 

type GoogleCloudMlV1_Measurement_Metric struct {
	// Metric name.
	Metric string `pulumi:"metric"`
	// The value for this metric.
	Value float64 `pulumi:"value"`
}

A message representing a metric in the measurement.

type GoogleCloudMlV1_Measurement_MetricArgs 

type GoogleCloudMlV1_Measurement_MetricArgs struct {
	// Metric name.
	Metric pulumi.StringInput `pulumi:"metric"`
	// The value for this metric.
	Value pulumi.Float64Input `pulumi:"value"`
}

A message representing a metric in the measurement.

func (GoogleCloudMlV1_Measurement_MetricArgs) ElementType 

func (GoogleCloudMlV1_Measurement_MetricArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_Measurement_MetricArgs) ToGoogleCloudMlV1_Measurement_MetricOutput 

func (i GoogleCloudMlV1_Measurement_MetricArgs) ToGoogleCloudMlV1_Measurement_MetricOutput() GoogleCloudMlV1_Measurement_MetricOutput

func (GoogleCloudMlV1_Measurement_MetricArgs) ToGoogleCloudMlV1_Measurement_MetricOutputWithContext 

func (i GoogleCloudMlV1_Measurement_MetricArgs) ToGoogleCloudMlV1_Measurement_MetricOutputWithContext(ctx context.Context) GoogleCloudMlV1_Measurement_MetricOutput

type GoogleCloudMlV1_Measurement_MetricArray 

type GoogleCloudMlV1_Measurement_MetricArray []GoogleCloudMlV1_Measurement_MetricInput

func (GoogleCloudMlV1_Measurement_MetricArray) ElementType 

func (GoogleCloudMlV1_Measurement_MetricArray) ElementType() reflect.Type

func (GoogleCloudMlV1_Measurement_MetricArray) ToGoogleCloudMlV1_Measurement_MetricArrayOutput 

func (i GoogleCloudMlV1_Measurement_MetricArray) ToGoogleCloudMlV1_Measurement_MetricArrayOutput() GoogleCloudMlV1_Measurement_MetricArrayOutput

func (GoogleCloudMlV1_Measurement_MetricArray) ToGoogleCloudMlV1_Measurement_MetricArrayOutputWithContext 

func (i GoogleCloudMlV1_Measurement_MetricArray) ToGoogleCloudMlV1_Measurement_MetricArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_Measurement_MetricArrayOutput

type GoogleCloudMlV1_Measurement_MetricArrayInput 

type GoogleCloudMlV1_Measurement_MetricArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_Measurement_MetricArrayOutput() GoogleCloudMlV1_Measurement_MetricArrayOutput
	ToGoogleCloudMlV1_Measurement_MetricArrayOutputWithContext(context.Context) GoogleCloudMlV1_Measurement_MetricArrayOutput
}

GoogleCloudMlV1_Measurement_MetricArrayInput is an input type that accepts GoogleCloudMlV1_Measurement_MetricArray and GoogleCloudMlV1_Measurement_MetricArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1_Measurement_MetricArrayInput` via: 

GoogleCloudMlV1_Measurement_MetricArray{ GoogleCloudMlV1_Measurement_MetricArgs{...} }

type GoogleCloudMlV1_Measurement_MetricArrayOutput 

type GoogleCloudMlV1_Measurement_MetricArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_Measurement_MetricArrayOutput) ElementType 

func (GoogleCloudMlV1_Measurement_MetricArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_Measurement_MetricArrayOutput) Index 

func (o GoogleCloudMlV1_Measurement_MetricArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_Measurement_MetricOutput

func (GoogleCloudMlV1_Measurement_MetricArrayOutput) ToGoogleCloudMlV1_Measurement_MetricArrayOutput 

func (o GoogleCloudMlV1_Measurement_MetricArrayOutput) ToGoogleCloudMlV1_Measurement_MetricArrayOutput() GoogleCloudMlV1_Measurement_MetricArrayOutput

func (GoogleCloudMlV1_Measurement_MetricArrayOutput) ToGoogleCloudMlV1_Measurement_MetricArrayOutputWithContext 

func (o GoogleCloudMlV1_Measurement_MetricArrayOutput) ToGoogleCloudMlV1_Measurement_MetricArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_Measurement_MetricArrayOutput

type GoogleCloudMlV1_Measurement_MetricInput 

type GoogleCloudMlV1_Measurement_MetricInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_Measurement_MetricOutput() GoogleCloudMlV1_Measurement_MetricOutput
	ToGoogleCloudMlV1_Measurement_MetricOutputWithContext(context.Context) GoogleCloudMlV1_Measurement_MetricOutput
}

GoogleCloudMlV1_Measurement_MetricInput is an input type that accepts GoogleCloudMlV1_Measurement_MetricArgs and GoogleCloudMlV1_Measurement_MetricOutput values. You can construct a concrete instance of `GoogleCloudMlV1_Measurement_MetricInput` via: 

GoogleCloudMlV1_Measurement_MetricArgs{...}

type GoogleCloudMlV1_Measurement_MetricOutput 

type GoogleCloudMlV1_Measurement_MetricOutput struct{ *pulumi.OutputState }

A message representing a metric in the measurement.

func (GoogleCloudMlV1_Measurement_MetricOutput) ElementType 

func (GoogleCloudMlV1_Measurement_MetricOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_Measurement_MetricOutput) Metric 

func (o GoogleCloudMlV1_Measurement_MetricOutput) Metric() pulumi.StringOutput

Metric name.

func (GoogleCloudMlV1_Measurement_MetricOutput) ToGoogleCloudMlV1_Measurement_MetricOutput 

func (o GoogleCloudMlV1_Measurement_MetricOutput) ToGoogleCloudMlV1_Measurement_MetricOutput() GoogleCloudMlV1_Measurement_MetricOutput

func (GoogleCloudMlV1_Measurement_MetricOutput) ToGoogleCloudMlV1_Measurement_MetricOutputWithContext 

func (o GoogleCloudMlV1_Measurement_MetricOutput) ToGoogleCloudMlV1_Measurement_MetricOutputWithContext(ctx context.Context) GoogleCloudMlV1_Measurement_MetricOutput

func (GoogleCloudMlV1_Measurement_MetricOutput) Value 

func (o GoogleCloudMlV1_Measurement_MetricOutput) Value() pulumi.Float64Output

The value for this metric.

type GoogleCloudMlV1_Measurement_MetricResponse 

type GoogleCloudMlV1_Measurement_MetricResponse struct {
	// Metric name.
	Metric string `pulumi:"metric"`
	// The value for this metric.
	Value float64 `pulumi:"value"`
}

A message representing a metric in the measurement.

type GoogleCloudMlV1_Measurement_MetricResponseArrayOutput 

type GoogleCloudMlV1_Measurement_MetricResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_Measurement_MetricResponseArrayOutput) ElementType 

func (GoogleCloudMlV1_Measurement_MetricResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_Measurement_MetricResponseArrayOutput) Index 

func (o GoogleCloudMlV1_Measurement_MetricResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_Measurement_MetricResponseOutput

func (GoogleCloudMlV1_Measurement_MetricResponseArrayOutput) ToGoogleCloudMlV1_Measurement_MetricResponseArrayOutput 

func (o GoogleCloudMlV1_Measurement_MetricResponseArrayOutput) ToGoogleCloudMlV1_Measurement_MetricResponseArrayOutput() GoogleCloudMlV1_Measurement_MetricResponseArrayOutput

func (GoogleCloudMlV1_Measurement_MetricResponseArrayOutput) ToGoogleCloudMlV1_Measurement_MetricResponseArrayOutputWithContext 

func (o GoogleCloudMlV1_Measurement_MetricResponseArrayOutput) ToGoogleCloudMlV1_Measurement_MetricResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_Measurement_MetricResponseArrayOutput

type GoogleCloudMlV1_Measurement_MetricResponseOutput 

type GoogleCloudMlV1_Measurement_MetricResponseOutput struct{ *pulumi.OutputState }

A message representing a metric in the measurement.

func (GoogleCloudMlV1_Measurement_MetricResponseOutput) ElementType 

func (GoogleCloudMlV1_Measurement_MetricResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_Measurement_MetricResponseOutput) Metric 

func (o GoogleCloudMlV1_Measurement_MetricResponseOutput) Metric() pulumi.StringOutput

Metric name.

func (GoogleCloudMlV1_Measurement_MetricResponseOutput) ToGoogleCloudMlV1_Measurement_MetricResponseOutput 

func (o GoogleCloudMlV1_Measurement_MetricResponseOutput) ToGoogleCloudMlV1_Measurement_MetricResponseOutput() GoogleCloudMlV1_Measurement_MetricResponseOutput

func (GoogleCloudMlV1_Measurement_MetricResponseOutput) ToGoogleCloudMlV1_Measurement_MetricResponseOutputWithContext 

func (o GoogleCloudMlV1_Measurement_MetricResponseOutput) ToGoogleCloudMlV1_Measurement_MetricResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_Measurement_MetricResponseOutput

func (GoogleCloudMlV1_Measurement_MetricResponseOutput) Value 

func (o GoogleCloudMlV1_Measurement_MetricResponseOutput) Value() pulumi.Float64Output

The value for this metric.

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec 

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec struct {
	// Must be specified if type is `CATEGORICAL`. The list of possible categories.
	Values []string `pulumi:"values"`
}

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs 

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs struct {
	// Must be specified if type is `CATEGORICAL`. The list of possible categories.
	Values pulumi.StringArrayInput `pulumi:"values"`
}

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs and GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecInput` via: 

GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs{...}

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput) Values() pulumi.StringArrayOutput

Must be specified if type is `CATEGORICAL`. The list of possible categories.

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs, GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtr and GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrInput` via: 

        GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs{...}

or:

        nil

func GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtr 

func GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtr(v *GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs) GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrInput

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) Elem 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) Elem() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput) Values() pulumi.StringArrayOutput

Must be specified if type is `CATEGORICAL`. The list of possible categories.

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponse 

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponse struct {
	// Must be specified if type is `CATEGORICAL`. The list of possible categories.
	Values []string `pulumi:"values"`
}

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput) Values() pulumi.StringArrayOutput

Must be specified if type is `CATEGORICAL`. The list of possible categories.

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec 

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec struct {
	// Must be specified if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
	Values []float64 `pulumi:"values"`
}

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs 

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs struct {
	// Must be specified if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
	Values pulumi.Float64ArrayInput `pulumi:"values"`
}

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs and GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecInput` via: 

GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs{...}

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput) Values() pulumi.Float64ArrayOutput

Must be specified if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs, GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtr and GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrInput` via: 

        GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs{...}

or:

        nil

func GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtr 

func GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtr(v *GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs) GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrInput

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) Elem 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) Elem() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput) Values() pulumi.Float64ArrayOutput

Must be specified if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponse 

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponse struct {
	// Must be specified if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
	Values []float64 `pulumi:"values"`
}

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput) Values() pulumi.Float64ArrayOutput

Must be specified if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec 

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec struct {
	// Must be specified if type is `DOUBLE`. Maximum value of the parameter.
	MaxValue *float64 `pulumi:"maxValue"`
	// Must be specified if type is `DOUBLE`. Minimum value of the parameter.
	MinValue *float64 `pulumi:"minValue"`
}

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs 

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs struct {
	// Must be specified if type is `DOUBLE`. Maximum value of the parameter.
	MaxValue pulumi.Float64PtrInput `pulumi:"maxValue"`
	// Must be specified if type is `DOUBLE`. Minimum value of the parameter.
	MinValue pulumi.Float64PtrInput `pulumi:"minValue"`
}

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs and GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecInput` via: 

GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs{...}

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) MaxValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) MaxValue() pulumi.Float64PtrOutput

Must be specified if type is `DOUBLE`. Maximum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) MinValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) MinValue() pulumi.Float64PtrOutput

Must be specified if type is `DOUBLE`. Minimum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs, GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtr and GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrInput` via: 

        GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs{...}

or:

        nil

func GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtr 

func GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtr(v *GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs) GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrInput

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) Elem 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) Elem() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) MaxValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) MaxValue() pulumi.Float64PtrOutput

Must be specified if type is `DOUBLE`. Maximum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) MinValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) MinValue() pulumi.Float64PtrOutput

Must be specified if type is `DOUBLE`. Minimum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponse 

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponse struct {
	// Must be specified if type is `DOUBLE`. Maximum value of the parameter.
	MaxValue float64 `pulumi:"maxValue"`
	// Must be specified if type is `DOUBLE`. Minimum value of the parameter.
	MinValue float64 `pulumi:"minValue"`
}

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) MaxValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) MaxValue() pulumi.Float64Output

Must be specified if type is `DOUBLE`. Maximum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) MinValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) MinValue() pulumi.Float64Output

Must be specified if type is `DOUBLE`. Minimum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec 

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec struct {
	// Must be specified if type is `INTEGER`. Maximum value of the parameter.
	MaxValue *string `pulumi:"maxValue"`
	// Must be specified if type is `INTEGER`. Minimum value of the parameter.
	MinValue *string `pulumi:"minValue"`
}

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs 

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs struct {
	// Must be specified if type is `INTEGER`. Maximum value of the parameter.
	MaxValue pulumi.StringPtrInput `pulumi:"maxValue"`
	// Must be specified if type is `INTEGER`. Minimum value of the parameter.
	MinValue pulumi.StringPtrInput `pulumi:"minValue"`
}

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs and GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecInput` via: 

GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs{...}

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) MaxValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) MaxValue() pulumi.StringPtrOutput

Must be specified if type is `INTEGER`. Maximum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) MinValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) MinValue() pulumi.StringPtrOutput

Must be specified if type is `INTEGER`. Minimum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs, GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtr and GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrInput` via: 

        GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs{...}

or:

        nil

func GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtr 

func GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtr(v *GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs) GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrInput

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) Elem 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) Elem() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) MaxValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) MaxValue() pulumi.StringPtrOutput

Must be specified if type is `INTEGER`. Maximum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) MinValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) MinValue() pulumi.StringPtrOutput

Must be specified if type is `INTEGER`. Minimum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponse 

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponse struct {
	// Must be specified if type is `INTEGER`. Maximum value of the parameter.
	MaxValue string `pulumi:"maxValue"`
	// Must be specified if type is `INTEGER`. Minimum value of the parameter.
	MinValue string `pulumi:"minValue"`
}

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) MaxValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) MaxValue() pulumi.StringOutput

Must be specified if type is `INTEGER`. Maximum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) MinValue 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) MinValue() pulumi.StringOutput

Must be specified if type is `INTEGER`. Minimum value of the parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec struct {
	// Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in `categorical_value_spec` of parent parameter.
	Values []string `pulumi:"values"`
}

Represents the spec to match categorical values from parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs struct {
	// Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in `categorical_value_spec` of parent parameter.
	Values pulumi.StringArrayInput `pulumi:"values"`
}

Represents the spec to match categorical values from parent parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs and GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecInput` via: 

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs{...}

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput struct{ *pulumi.OutputState }

Represents the spec to match categorical values from parent parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in `categorical_value_spec` of parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs, GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtr and GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrInput` via: 

        GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs{...}

or:

        nil

func GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtr 

func GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtr(v *GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrInput

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) Elem 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) Elem() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in `categorical_value_spec` of parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse struct {
	// Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in `categorical_value_spec` of parent parameter.
	Values []string `pulumi:"values"`
}

Represents the spec to match categorical values from parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput struct{ *pulumi.OutputState }

Represents the spec to match categorical values from parent parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in `categorical_value_spec` of parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec struct {
	// Matches values of the parent parameter with type 'DISCRETE'. All values must exist in `discrete_value_spec` of parent parameter.
	Values []float64 `pulumi:"values"`
}

Represents the spec to match discrete values from parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs struct {
	// Matches values of the parent parameter with type 'DISCRETE'. All values must exist in `discrete_value_spec` of parent parameter.
	Values pulumi.Float64ArrayInput `pulumi:"values"`
}

Represents the spec to match discrete values from parent parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs and GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecInput` via: 

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs{...}

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput struct{ *pulumi.OutputState }

Represents the spec to match discrete values from parent parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput) Values() pulumi.Float64ArrayOutput

Matches values of the parent parameter with type 'DISCRETE'. All values must exist in `discrete_value_spec` of parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs, GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtr and GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrInput` via: 

        GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs{...}

or:

        nil

func GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtr 

func GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtr(v *GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrInput

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) Elem 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) Elem() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput) Values() pulumi.Float64ArrayOutput

Matches values of the parent parameter with type 'DISCRETE'. All values must exist in `discrete_value_spec` of parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse struct {
	// Matches values of the parent parameter with type 'DISCRETE'. All values must exist in `discrete_value_spec` of parent parameter.
	Values []float64 `pulumi:"values"`
}

Represents the spec to match discrete values from parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput struct{ *pulumi.OutputState }

Represents the spec to match discrete values from parent parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput) Values() pulumi.Float64ArrayOutput

Matches values of the parent parameter with type 'DISCRETE'. All values must exist in `discrete_value_spec` of parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec struct {
	// Matches values of the parent parameter with type 'INTEGER'. All values must lie in `integer_value_spec` of parent parameter.
	Values []string `pulumi:"values"`
}

Represents the spec to match integer values from parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs struct {
	// Matches values of the parent parameter with type 'INTEGER'. All values must lie in `integer_value_spec` of parent parameter.
	Values pulumi.StringArrayInput `pulumi:"values"`
}

Represents the spec to match integer values from parent parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutputWithContext 

func (i GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs and GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecInput` via: 

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs{...}

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput struct{ *pulumi.OutputState }

Represents the spec to match integer values from parent parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter with type 'INTEGER'. All values must lie in `integer_value_spec` of parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrInput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput
	ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput
}

GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrInput is an input type that accepts GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs, GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtr and GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrInput` via: 

        GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs{...}

or:

        nil

func GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtr 

func GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtr(v *GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrInput

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) Elem 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) Elem() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter with type 'INTEGER'. All values must lie in `integer_value_spec` of parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse struct {
	// Matches values of the parent parameter with type 'INTEGER'. All values must lie in `integer_value_spec` of parent parameter.
	Values []string `pulumi:"values"`
}

Represents the spec to match integer values from parent parameter.

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput 

type GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput struct{ *pulumi.OutputState }

Represents the spec to match integer values from parent parameter.

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput) ElementType 

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutputWithContext 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput) ToGoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput) Values 

func (o GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput) Values() pulumi.StringArrayOutput

Matches values of the parent parameter with type 'INTEGER'. All values must lie in `integer_value_spec` of parent parameter.

type GoogleCloudMlV1_StudyConfig_MetricSpec 

type GoogleCloudMlV1_StudyConfig_MetricSpec struct {
	// The optimization goal of the metric.
	Goal GoogleCloudMlV1_StudyConfig_MetricSpecGoal `pulumi:"goal"`
	// The name of the metric.
	Metric string `pulumi:"metric"`
}

Represents a metric to optimize.

type GoogleCloudMlV1_StudyConfig_MetricSpecArgs 

type GoogleCloudMlV1_StudyConfig_MetricSpecArgs struct {
	// The optimization goal of the metric.
	Goal GoogleCloudMlV1_StudyConfig_MetricSpecGoalInput `pulumi:"goal"`
	// The name of the metric.
	Metric pulumi.StringInput `pulumi:"metric"`
}

Represents a metric to optimize.

func (GoogleCloudMlV1_StudyConfig_MetricSpecArgs) ElementType 

func (GoogleCloudMlV1_StudyConfig_MetricSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_MetricSpecArgs) ToGoogleCloudMlV1_StudyConfig_MetricSpecOutput 

func (i GoogleCloudMlV1_StudyConfig_MetricSpecArgs) ToGoogleCloudMlV1_StudyConfig_MetricSpecOutput() GoogleCloudMlV1_StudyConfig_MetricSpecOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecArgs) ToGoogleCloudMlV1_StudyConfig_MetricSpecOutputWithContext 

func (i GoogleCloudMlV1_StudyConfig_MetricSpecArgs) ToGoogleCloudMlV1_StudyConfig_MetricSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecOutput

type GoogleCloudMlV1_StudyConfig_MetricSpecArray 

type GoogleCloudMlV1_StudyConfig_MetricSpecArray []GoogleCloudMlV1_StudyConfig_MetricSpecInput

func (GoogleCloudMlV1_StudyConfig_MetricSpecArray) ElementType 

func (GoogleCloudMlV1_StudyConfig_MetricSpecArray) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_MetricSpecArray) ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput 

func (i GoogleCloudMlV1_StudyConfig_MetricSpecArray) ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput() GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecArray) ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutputWithContext 

func (i GoogleCloudMlV1_StudyConfig_MetricSpecArray) ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput

type GoogleCloudMlV1_StudyConfig_MetricSpecArrayInput 

type GoogleCloudMlV1_StudyConfig_MetricSpecArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput() GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput
	ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput
}

GoogleCloudMlV1_StudyConfig_MetricSpecArrayInput is an input type that accepts GoogleCloudMlV1_StudyConfig_MetricSpecArray and GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfig_MetricSpecArrayInput` via: 

GoogleCloudMlV1_StudyConfig_MetricSpecArray{ GoogleCloudMlV1_StudyConfig_MetricSpecArgs{...} }

type GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput 

type GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput) ElementType 

func (GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput) Index 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_StudyConfig_MetricSpecOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput() GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutputWithContext 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput

type GoogleCloudMlV1_StudyConfig_MetricSpecGoal added in v0.4.0 

type GoogleCloudMlV1_StudyConfig_MetricSpecGoal string

Required. The optimization goal of the metric.

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ElementType added in v0.4.0 

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput() GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput() GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_MetricSpecGoal) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1_StudyConfig_MetricSpecGoalInput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_MetricSpecGoalInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput() GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput
	ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput
}

GoogleCloudMlV1_StudyConfig_MetricSpecGoalInput is an input type that accepts GoogleCloudMlV1_StudyConfig_MetricSpecGoalArgs and GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfig_MetricSpecGoalInput` via: 

GoogleCloudMlV1_StudyConfig_MetricSpecGoalArgs{...}

type GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput() GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput() GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrInput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput() GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput
	ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput
}

func GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtr added in v0.6.0 

func GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtr(v string) GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrInput

type GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) Elem() GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput() GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecGoalPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1_StudyConfig_MetricSpecInput 

type GoogleCloudMlV1_StudyConfig_MetricSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_MetricSpecOutput() GoogleCloudMlV1_StudyConfig_MetricSpecOutput
	ToGoogleCloudMlV1_StudyConfig_MetricSpecOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecOutput
}

GoogleCloudMlV1_StudyConfig_MetricSpecInput is an input type that accepts GoogleCloudMlV1_StudyConfig_MetricSpecArgs and GoogleCloudMlV1_StudyConfig_MetricSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfig_MetricSpecInput` via: 

GoogleCloudMlV1_StudyConfig_MetricSpecArgs{...}

type GoogleCloudMlV1_StudyConfig_MetricSpecOutput 

type GoogleCloudMlV1_StudyConfig_MetricSpecOutput struct{ *pulumi.OutputState }

Represents a metric to optimize.

func (GoogleCloudMlV1_StudyConfig_MetricSpecOutput) ElementType 

func (GoogleCloudMlV1_StudyConfig_MetricSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_MetricSpecOutput) Goal 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecOutput) Goal() GoogleCloudMlV1_StudyConfig_MetricSpecGoalOutput

The optimization goal of the metric.

func (GoogleCloudMlV1_StudyConfig_MetricSpecOutput) Metric 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecOutput) Metric() pulumi.StringOutput

The name of the metric.

func (GoogleCloudMlV1_StudyConfig_MetricSpecOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecOutput 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecOutput() GoogleCloudMlV1_StudyConfig_MetricSpecOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecOutputWithContext 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecOutput

type GoogleCloudMlV1_StudyConfig_MetricSpecResponse 

type GoogleCloudMlV1_StudyConfig_MetricSpecResponse struct {
	// The optimization goal of the metric.
	Goal string `pulumi:"goal"`
	// The name of the metric.
	Metric string `pulumi:"metric"`
}

Represents a metric to optimize.

type GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput 

type GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput) ElementType 

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput) Index 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput() GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutputWithContext 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput

type GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput 

type GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput struct{ *pulumi.OutputState }

Represents a metric to optimize.

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) ElementType 

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) Goal 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) Goal() pulumi.StringOutput

The optimization goal of the metric.

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) Metric 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) Metric() pulumi.StringOutput

The name of the metric.

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput() GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput

func (GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecResponseOutputWithContext 

func (o GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput) ToGoogleCloudMlV1_StudyConfig_MetricSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_MetricSpecResponseOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpec 

type GoogleCloudMlV1_StudyConfig_ParameterSpec struct {
	// The value spec for a 'CATEGORICAL' parameter.
	CategoricalValueSpec *GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec `pulumi:"categoricalValueSpec"`
	// A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
	ChildParameterSpecs []GoogleCloudMlV1_StudyConfig_ParameterSpec `pulumi:"childParameterSpecs"`
	// The value spec for a 'DISCRETE' parameter.
	DiscreteValueSpec *GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec `pulumi:"discreteValueSpec"`
	// The value spec for a 'DOUBLE' parameter.
	DoubleValueSpec *GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec `pulumi:"doubleValueSpec"`
	// The value spec for an 'INTEGER' parameter.
	IntegerValueSpec *GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec `pulumi:"integerValueSpec"`
	// The parameter name must be unique amongst all ParameterSpecs.
	Parameter               string                                                                       `pulumi:"parameter"`
	ParentCategoricalValues *GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec `pulumi:"parentCategoricalValues"`
	ParentDiscreteValues    *GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec    `pulumi:"parentDiscreteValues"`
	ParentIntValues         *GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec         `pulumi:"parentIntValues"`
	// How the parameter should be scaled. Leave unset for categorical parameters.
	ScaleType *GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType `pulumi:"scaleType"`
	// The type of the parameter.
	Type GoogleCloudMlV1_StudyConfig_ParameterSpecType `pulumi:"type"`
}

Represents a single parameter to optimize.

type GoogleCloudMlV1_StudyConfig_ParameterSpecArgs 

type GoogleCloudMlV1_StudyConfig_ParameterSpecArgs struct {
	// The value spec for a 'CATEGORICAL' parameter.
	CategoricalValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrInput `pulumi:"categoricalValueSpec"`
	// A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
	ChildParameterSpecs GoogleCloudMlV1_StudyConfig_ParameterSpecArrayInput `pulumi:"childParameterSpecs"`
	// The value spec for a 'DISCRETE' parameter.
	DiscreteValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrInput `pulumi:"discreteValueSpec"`
	// The value spec for a 'DOUBLE' parameter.
	DoubleValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrInput `pulumi:"doubleValueSpec"`
	// The value spec for an 'INTEGER' parameter.
	IntegerValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrInput `pulumi:"integerValueSpec"`
	// The parameter name must be unique amongst all ParameterSpecs.
	Parameter               pulumi.StringInput                                                                  `pulumi:"parameter"`
	ParentCategoricalValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrInput `pulumi:"parentCategoricalValues"`
	ParentDiscreteValues    GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrInput    `pulumi:"parentDiscreteValues"`
	ParentIntValues         GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrInput         `pulumi:"parentIntValues"`
	// How the parameter should be scaled. Leave unset for categorical parameters.
	ScaleType GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrInput `pulumi:"scaleType"`
	// The type of the parameter.
	Type GoogleCloudMlV1_StudyConfig_ParameterSpecTypeInput `pulumi:"type"`
}

Represents a single parameter to optimize.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArgs) ElementType 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArgs) ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutput 

func (i GoogleCloudMlV1_StudyConfig_ParameterSpecArgs) ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArgs) ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutputWithContext 

func (i GoogleCloudMlV1_StudyConfig_ParameterSpecArgs) ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpecArray 

type GoogleCloudMlV1_StudyConfig_ParameterSpecArray []GoogleCloudMlV1_StudyConfig_ParameterSpecInput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArray) ElementType 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArray) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArray) ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput 

func (i GoogleCloudMlV1_StudyConfig_ParameterSpecArray) ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArray) ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutputWithContext 

func (i GoogleCloudMlV1_StudyConfig_ParameterSpecArray) ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpecArrayInput 

type GoogleCloudMlV1_StudyConfig_ParameterSpecArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput
	ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput
}

GoogleCloudMlV1_StudyConfig_ParameterSpecArrayInput is an input type that accepts GoogleCloudMlV1_StudyConfig_ParameterSpecArray and GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfig_ParameterSpecArrayInput` via: 

GoogleCloudMlV1_StudyConfig_ParameterSpecArray{ GoogleCloudMlV1_StudyConfig_ParameterSpecArgs{...} }

type GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput 

type GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput) ElementType 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput) Index 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_StudyConfig_ParameterSpecOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutputWithContext 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpecInput 

type GoogleCloudMlV1_StudyConfig_ParameterSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecOutput
	ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecOutput
}

GoogleCloudMlV1_StudyConfig_ParameterSpecInput is an input type that accepts GoogleCloudMlV1_StudyConfig_ParameterSpecArgs and GoogleCloudMlV1_StudyConfig_ParameterSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfig_ParameterSpecInput` via: 

GoogleCloudMlV1_StudyConfig_ParameterSpecArgs{...}

type GoogleCloudMlV1_StudyConfig_ParameterSpecOutput 

type GoogleCloudMlV1_StudyConfig_ParameterSpecOutput struct{ *pulumi.OutputState }

Represents a single parameter to optimize.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) CategoricalValueSpec 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) CategoricalValueSpec() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecPtrOutput

The value spec for a 'CATEGORICAL' parameter.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ChildParameterSpecs 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ChildParameterSpecs() GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput

A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) DiscreteValueSpec 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) DiscreteValueSpec() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecPtrOutput

The value spec for a 'DISCRETE' parameter.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) DoubleValueSpec 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) DoubleValueSpec() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecPtrOutput

The value spec for a 'DOUBLE' parameter.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ElementType 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) IntegerValueSpec 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) IntegerValueSpec() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecPtrOutput

The value spec for an 'INTEGER' parameter.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) Parameter 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) Parameter() pulumi.StringOutput

The parameter name must be unique amongst all ParameterSpecs.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ParentCategoricalValues 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ParentCategoricalValues() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ParentDiscreteValues 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ParentDiscreteValues() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ParentIntValues 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ParentIntValues() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecPtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ScaleType 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ScaleType() GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput

How the parameter should be scaled. Leave unset for categorical parameters.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutput 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutputWithContext 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) Type 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecOutput) Type() GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput

The type of the parameter.

type GoogleCloudMlV1_StudyConfig_ParameterSpecResponse 

type GoogleCloudMlV1_StudyConfig_ParameterSpecResponse struct {
	// The value spec for a 'CATEGORICAL' parameter.
	CategoricalValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponse `pulumi:"categoricalValueSpec"`
	// A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
	ChildParameterSpecs []GoogleCloudMlV1_StudyConfig_ParameterSpecResponse `pulumi:"childParameterSpecs"`
	// The value spec for a 'DISCRETE' parameter.
	DiscreteValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponse `pulumi:"discreteValueSpec"`
	// The value spec for a 'DOUBLE' parameter.
	DoubleValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponse `pulumi:"doubleValueSpec"`
	// The value spec for an 'INTEGER' parameter.
	IntegerValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponse `pulumi:"integerValueSpec"`
	// The parameter name must be unique amongst all ParameterSpecs.
	Parameter               string                                                                              `pulumi:"parameter"`
	ParentCategoricalValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse `pulumi:"parentCategoricalValues"`
	ParentDiscreteValues    GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse    `pulumi:"parentDiscreteValues"`
	ParentIntValues         GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse         `pulumi:"parentIntValues"`
	// How the parameter should be scaled. Leave unset for categorical parameters.
	ScaleType string `pulumi:"scaleType"`
	// The type of the parameter.
	Type string `pulumi:"type"`
}

Represents a single parameter to optimize.

type GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput 

type GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput) ElementType 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput) Index 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutputWithContext 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput 

type GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput struct{ *pulumi.OutputState }

Represents a single parameter to optimize.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) CategoricalValueSpec 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) CategoricalValueSpec() GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseOutput

The value spec for a 'CATEGORICAL' parameter.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ChildParameterSpecs 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ChildParameterSpecs() GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput

A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) DiscreteValueSpec 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) DiscreteValueSpec() GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseOutput

The value spec for a 'DISCRETE' parameter.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) DoubleValueSpec 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) DoubleValueSpec() GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseOutput

The value spec for a 'DOUBLE' parameter.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ElementType 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) IntegerValueSpec 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) IntegerValueSpec() GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseOutput

The value spec for an 'INTEGER' parameter.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) Parameter 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) Parameter() pulumi.StringOutput

The parameter name must be unique amongst all ParameterSpecs.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ParentCategoricalValues 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ParentCategoricalValues() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ParentDiscreteValues 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ParentDiscreteValues() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ParentIntValues 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ParentIntValues() GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ScaleType 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ScaleType() pulumi.StringOutput

How the parameter should be scaled. Leave unset for categorical parameters.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutputWithContext 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) Type 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecResponseOutput) Type() pulumi.StringOutput

The type of the parameter.

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType added in v0.4.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType string

How the parameter should be scaled. Leave unset for categorical parameters.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ElementType added in v0.4.0 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeInput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput
	ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput
}

GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeInput is an input type that accepts GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeArgs and GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeInput` via: 

GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeArgs{...}

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrInput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput
	ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput
}

func GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtr added in v0.6.0 

func GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtr(v string) GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrInput

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) Elem() GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpecType added in v0.4.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecType string

Required. The type of the parameter.

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ElementType added in v0.4.0 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1_StudyConfig_ParameterSpecType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpecTypeInput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecTypeInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput
	ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput
}

GoogleCloudMlV1_StudyConfig_ParameterSpecTypeInput is an input type that accepts GoogleCloudMlV1_StudyConfig_ParameterSpecTypeArgs and GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput values. You can construct a concrete instance of `GoogleCloudMlV1_StudyConfig_ParameterSpecTypeInput` via: 

GoogleCloudMlV1_StudyConfig_ParameterSpecTypeArgs{...}

type GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrInput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput
	ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutputWithContext(context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput
}

func GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtr added in v0.6.0 

func GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtr(v string) GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrInput

type GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput added in v0.6.0 

type GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) Elem() GoogleCloudMlV1_StudyConfig_ParameterSpecTypeOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput() GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ToGoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1_StudyConfig_ParameterSpecTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1_Trial_Parameter 

type GoogleCloudMlV1_Trial_Parameter struct {
	// Must be set if ParameterType is DOUBLE or DISCRETE.
	FloatValue *float64 `pulumi:"floatValue"`
	// Must be set if ParameterType is INTEGER
	IntValue *string `pulumi:"intValue"`
	// The name of the parameter.
	Parameter *string `pulumi:"parameter"`
	// Must be set if ParameterTypeis CATEGORICAL
	StringValue *string `pulumi:"stringValue"`
}

A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.

type GoogleCloudMlV1_Trial_ParameterArgs 

type GoogleCloudMlV1_Trial_ParameterArgs struct {
	// Must be set if ParameterType is DOUBLE or DISCRETE.
	FloatValue pulumi.Float64PtrInput `pulumi:"floatValue"`
	// Must be set if ParameterType is INTEGER
	IntValue pulumi.StringPtrInput `pulumi:"intValue"`
	// The name of the parameter.
	Parameter pulumi.StringPtrInput `pulumi:"parameter"`
	// Must be set if ParameterTypeis CATEGORICAL
	StringValue pulumi.StringPtrInput `pulumi:"stringValue"`
}

A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.

func (GoogleCloudMlV1_Trial_ParameterArgs) ElementType 

func (GoogleCloudMlV1_Trial_ParameterArgs) ElementType() reflect.Type

func (GoogleCloudMlV1_Trial_ParameterArgs) ToGoogleCloudMlV1_Trial_ParameterOutput 

func (i GoogleCloudMlV1_Trial_ParameterArgs) ToGoogleCloudMlV1_Trial_ParameterOutput() GoogleCloudMlV1_Trial_ParameterOutput

func (GoogleCloudMlV1_Trial_ParameterArgs) ToGoogleCloudMlV1_Trial_ParameterOutputWithContext 

func (i GoogleCloudMlV1_Trial_ParameterArgs) ToGoogleCloudMlV1_Trial_ParameterOutputWithContext(ctx context.Context) GoogleCloudMlV1_Trial_ParameterOutput

type GoogleCloudMlV1_Trial_ParameterArray 

type GoogleCloudMlV1_Trial_ParameterArray []GoogleCloudMlV1_Trial_ParameterInput

func (GoogleCloudMlV1_Trial_ParameterArray) ElementType 

func (GoogleCloudMlV1_Trial_ParameterArray) ElementType() reflect.Type

func (GoogleCloudMlV1_Trial_ParameterArray) ToGoogleCloudMlV1_Trial_ParameterArrayOutput 

func (i GoogleCloudMlV1_Trial_ParameterArray) ToGoogleCloudMlV1_Trial_ParameterArrayOutput() GoogleCloudMlV1_Trial_ParameterArrayOutput

func (GoogleCloudMlV1_Trial_ParameterArray) ToGoogleCloudMlV1_Trial_ParameterArrayOutputWithContext 

func (i GoogleCloudMlV1_Trial_ParameterArray) ToGoogleCloudMlV1_Trial_ParameterArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_Trial_ParameterArrayOutput

type GoogleCloudMlV1_Trial_ParameterArrayInput 

type GoogleCloudMlV1_Trial_ParameterArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_Trial_ParameterArrayOutput() GoogleCloudMlV1_Trial_ParameterArrayOutput
	ToGoogleCloudMlV1_Trial_ParameterArrayOutputWithContext(context.Context) GoogleCloudMlV1_Trial_ParameterArrayOutput
}

GoogleCloudMlV1_Trial_ParameterArrayInput is an input type that accepts GoogleCloudMlV1_Trial_ParameterArray and GoogleCloudMlV1_Trial_ParameterArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1_Trial_ParameterArrayInput` via: 

GoogleCloudMlV1_Trial_ParameterArray{ GoogleCloudMlV1_Trial_ParameterArgs{...} }

type GoogleCloudMlV1_Trial_ParameterArrayOutput 

type GoogleCloudMlV1_Trial_ParameterArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_Trial_ParameterArrayOutput) ElementType 

func (GoogleCloudMlV1_Trial_ParameterArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_Trial_ParameterArrayOutput) Index 

func (o GoogleCloudMlV1_Trial_ParameterArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_Trial_ParameterOutput

func (GoogleCloudMlV1_Trial_ParameterArrayOutput) ToGoogleCloudMlV1_Trial_ParameterArrayOutput 

func (o GoogleCloudMlV1_Trial_ParameterArrayOutput) ToGoogleCloudMlV1_Trial_ParameterArrayOutput() GoogleCloudMlV1_Trial_ParameterArrayOutput

func (GoogleCloudMlV1_Trial_ParameterArrayOutput) ToGoogleCloudMlV1_Trial_ParameterArrayOutputWithContext 

func (o GoogleCloudMlV1_Trial_ParameterArrayOutput) ToGoogleCloudMlV1_Trial_ParameterArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_Trial_ParameterArrayOutput

type GoogleCloudMlV1_Trial_ParameterInput 

type GoogleCloudMlV1_Trial_ParameterInput interface {
	pulumi.Input

	ToGoogleCloudMlV1_Trial_ParameterOutput() GoogleCloudMlV1_Trial_ParameterOutput
	ToGoogleCloudMlV1_Trial_ParameterOutputWithContext(context.Context) GoogleCloudMlV1_Trial_ParameterOutput
}

GoogleCloudMlV1_Trial_ParameterInput is an input type that accepts GoogleCloudMlV1_Trial_ParameterArgs and GoogleCloudMlV1_Trial_ParameterOutput values. You can construct a concrete instance of `GoogleCloudMlV1_Trial_ParameterInput` via: 

GoogleCloudMlV1_Trial_ParameterArgs{...}

type GoogleCloudMlV1_Trial_ParameterOutput 

type GoogleCloudMlV1_Trial_ParameterOutput struct{ *pulumi.OutputState }

A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.

func (GoogleCloudMlV1_Trial_ParameterOutput) ElementType 

func (GoogleCloudMlV1_Trial_ParameterOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_Trial_ParameterOutput) FloatValue 

func (o GoogleCloudMlV1_Trial_ParameterOutput) FloatValue() pulumi.Float64PtrOutput

Must be set if ParameterType is DOUBLE or DISCRETE.

func (GoogleCloudMlV1_Trial_ParameterOutput) IntValue 

func (o GoogleCloudMlV1_Trial_ParameterOutput) IntValue() pulumi.StringPtrOutput

Must be set if ParameterType is INTEGER

func (GoogleCloudMlV1_Trial_ParameterOutput) Parameter 

func (o GoogleCloudMlV1_Trial_ParameterOutput) Parameter() pulumi.StringPtrOutput

The name of the parameter.

func (GoogleCloudMlV1_Trial_ParameterOutput) StringValue 

func (o GoogleCloudMlV1_Trial_ParameterOutput) StringValue() pulumi.StringPtrOutput

Must be set if ParameterTypeis CATEGORICAL

func (GoogleCloudMlV1_Trial_ParameterOutput) ToGoogleCloudMlV1_Trial_ParameterOutput 

func (o GoogleCloudMlV1_Trial_ParameterOutput) ToGoogleCloudMlV1_Trial_ParameterOutput() GoogleCloudMlV1_Trial_ParameterOutput

func (GoogleCloudMlV1_Trial_ParameterOutput) ToGoogleCloudMlV1_Trial_ParameterOutputWithContext 

func (o GoogleCloudMlV1_Trial_ParameterOutput) ToGoogleCloudMlV1_Trial_ParameterOutputWithContext(ctx context.Context) GoogleCloudMlV1_Trial_ParameterOutput

type GoogleCloudMlV1_Trial_ParameterResponse 

type GoogleCloudMlV1_Trial_ParameterResponse struct {
	// Must be set if ParameterType is DOUBLE or DISCRETE.
	FloatValue float64 `pulumi:"floatValue"`
	// Must be set if ParameterType is INTEGER
	IntValue string `pulumi:"intValue"`
	// The name of the parameter.
	Parameter string `pulumi:"parameter"`
	// Must be set if ParameterTypeis CATEGORICAL
	StringValue string `pulumi:"stringValue"`
}

A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.

type GoogleCloudMlV1_Trial_ParameterResponseArrayOutput 

type GoogleCloudMlV1_Trial_ParameterResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1_Trial_ParameterResponseArrayOutput) ElementType 

func (GoogleCloudMlV1_Trial_ParameterResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_Trial_ParameterResponseArrayOutput) Index 

func (o GoogleCloudMlV1_Trial_ParameterResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1_Trial_ParameterResponseOutput

func (GoogleCloudMlV1_Trial_ParameterResponseArrayOutput) ToGoogleCloudMlV1_Trial_ParameterResponseArrayOutput 

func (o GoogleCloudMlV1_Trial_ParameterResponseArrayOutput) ToGoogleCloudMlV1_Trial_ParameterResponseArrayOutput() GoogleCloudMlV1_Trial_ParameterResponseArrayOutput

func (GoogleCloudMlV1_Trial_ParameterResponseArrayOutput) ToGoogleCloudMlV1_Trial_ParameterResponseArrayOutputWithContext 

func (o GoogleCloudMlV1_Trial_ParameterResponseArrayOutput) ToGoogleCloudMlV1_Trial_ParameterResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1_Trial_ParameterResponseArrayOutput

type GoogleCloudMlV1_Trial_ParameterResponseOutput 

type GoogleCloudMlV1_Trial_ParameterResponseOutput struct{ *pulumi.OutputState }

A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.

func (GoogleCloudMlV1_Trial_ParameterResponseOutput) ElementType 

func (GoogleCloudMlV1_Trial_ParameterResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1_Trial_ParameterResponseOutput) FloatValue 

func (o GoogleCloudMlV1_Trial_ParameterResponseOutput) FloatValue() pulumi.Float64Output

Must be set if ParameterType is DOUBLE or DISCRETE.

func (GoogleCloudMlV1_Trial_ParameterResponseOutput) IntValue 

func (o GoogleCloudMlV1_Trial_ParameterResponseOutput) IntValue() pulumi.StringOutput

Must be set if ParameterType is INTEGER

func (GoogleCloudMlV1_Trial_ParameterResponseOutput) Parameter 

func (o GoogleCloudMlV1_Trial_ParameterResponseOutput) Parameter() pulumi.StringOutput

The name of the parameter.

func (GoogleCloudMlV1_Trial_ParameterResponseOutput) StringValue 

func (o GoogleCloudMlV1_Trial_ParameterResponseOutput) StringValue() pulumi.StringOutput

Must be set if ParameterTypeis CATEGORICAL

func (GoogleCloudMlV1_Trial_ParameterResponseOutput) ToGoogleCloudMlV1_Trial_ParameterResponseOutput 

func (o GoogleCloudMlV1_Trial_ParameterResponseOutput) ToGoogleCloudMlV1_Trial_ParameterResponseOutput() GoogleCloudMlV1_Trial_ParameterResponseOutput

func (GoogleCloudMlV1_Trial_ParameterResponseOutput) ToGoogleCloudMlV1_Trial_ParameterResponseOutputWithContext 

func (o GoogleCloudMlV1_Trial_ParameterResponseOutput) ToGoogleCloudMlV1_Trial_ParameterResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1_Trial_ParameterResponseOutput

type GoogleCloudMlV1__AcceleratorConfig 

type GoogleCloudMlV1__AcceleratorConfig struct {
	// The number of accelerators to attach to each machine running the job.
	Count *string `pulumi:"count"`
	// The type of accelerator to use.
	Type *GoogleCloudMlV1__AcceleratorConfigType `pulumi:"type"`
}

Represents a hardware accelerator request config. Note that the AcceleratorConfig can be used in both Jobs and Versions. Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and [accelerators for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).

type GoogleCloudMlV1__AcceleratorConfigArgs 

type GoogleCloudMlV1__AcceleratorConfigArgs struct {
	// The number of accelerators to attach to each machine running the job.
	Count pulumi.StringPtrInput `pulumi:"count"`
	// The type of accelerator to use.
	Type GoogleCloudMlV1__AcceleratorConfigTypePtrInput `pulumi:"type"`
}

Represents a hardware accelerator request config. Note that the AcceleratorConfig can be used in both Jobs and Versions. Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and [accelerators for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).

func (GoogleCloudMlV1__AcceleratorConfigArgs) ElementType 

func (GoogleCloudMlV1__AcceleratorConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__AcceleratorConfigArgs) ToGoogleCloudMlV1__AcceleratorConfigOutput 

func (i GoogleCloudMlV1__AcceleratorConfigArgs) ToGoogleCloudMlV1__AcceleratorConfigOutput() GoogleCloudMlV1__AcceleratorConfigOutput

func (GoogleCloudMlV1__AcceleratorConfigArgs) ToGoogleCloudMlV1__AcceleratorConfigOutputWithContext 

func (i GoogleCloudMlV1__AcceleratorConfigArgs) ToGoogleCloudMlV1__AcceleratorConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigOutput

func (GoogleCloudMlV1__AcceleratorConfigArgs) ToGoogleCloudMlV1__AcceleratorConfigPtrOutput 

func (i GoogleCloudMlV1__AcceleratorConfigArgs) ToGoogleCloudMlV1__AcceleratorConfigPtrOutput() GoogleCloudMlV1__AcceleratorConfigPtrOutput

func (GoogleCloudMlV1__AcceleratorConfigArgs) ToGoogleCloudMlV1__AcceleratorConfigPtrOutputWithContext 

func (i GoogleCloudMlV1__AcceleratorConfigArgs) ToGoogleCloudMlV1__AcceleratorConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigPtrOutput

type GoogleCloudMlV1__AcceleratorConfigInput 

type GoogleCloudMlV1__AcceleratorConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__AcceleratorConfigOutput() GoogleCloudMlV1__AcceleratorConfigOutput
	ToGoogleCloudMlV1__AcceleratorConfigOutputWithContext(context.Context) GoogleCloudMlV1__AcceleratorConfigOutput
}

GoogleCloudMlV1__AcceleratorConfigInput is an input type that accepts GoogleCloudMlV1__AcceleratorConfigArgs and GoogleCloudMlV1__AcceleratorConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1__AcceleratorConfigInput` via: 

GoogleCloudMlV1__AcceleratorConfigArgs{...}

type GoogleCloudMlV1__AcceleratorConfigOutput 

type GoogleCloudMlV1__AcceleratorConfigOutput struct{ *pulumi.OutputState }

Represents a hardware accelerator request config. Note that the AcceleratorConfig can be used in both Jobs and Versions. Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and [accelerators for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).

func (GoogleCloudMlV1__AcceleratorConfigOutput) Count 

func (o GoogleCloudMlV1__AcceleratorConfigOutput) Count() pulumi.StringPtrOutput

The number of accelerators to attach to each machine running the job.

func (GoogleCloudMlV1__AcceleratorConfigOutput) ElementType 

func (GoogleCloudMlV1__AcceleratorConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AcceleratorConfigOutput) ToGoogleCloudMlV1__AcceleratorConfigOutput 

func (o GoogleCloudMlV1__AcceleratorConfigOutput) ToGoogleCloudMlV1__AcceleratorConfigOutput() GoogleCloudMlV1__AcceleratorConfigOutput

func (GoogleCloudMlV1__AcceleratorConfigOutput) ToGoogleCloudMlV1__AcceleratorConfigOutputWithContext 

func (o GoogleCloudMlV1__AcceleratorConfigOutput) ToGoogleCloudMlV1__AcceleratorConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigOutput

func (GoogleCloudMlV1__AcceleratorConfigOutput) ToGoogleCloudMlV1__AcceleratorConfigPtrOutput 

func (o GoogleCloudMlV1__AcceleratorConfigOutput) ToGoogleCloudMlV1__AcceleratorConfigPtrOutput() GoogleCloudMlV1__AcceleratorConfigPtrOutput

func (GoogleCloudMlV1__AcceleratorConfigOutput) ToGoogleCloudMlV1__AcceleratorConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__AcceleratorConfigOutput) ToGoogleCloudMlV1__AcceleratorConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigPtrOutput

func (GoogleCloudMlV1__AcceleratorConfigOutput) Type 

func (o GoogleCloudMlV1__AcceleratorConfigOutput) Type() GoogleCloudMlV1__AcceleratorConfigTypePtrOutput

The type of accelerator to use.

type GoogleCloudMlV1__AcceleratorConfigPtrInput 

type GoogleCloudMlV1__AcceleratorConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__AcceleratorConfigPtrOutput() GoogleCloudMlV1__AcceleratorConfigPtrOutput
	ToGoogleCloudMlV1__AcceleratorConfigPtrOutputWithContext(context.Context) GoogleCloudMlV1__AcceleratorConfigPtrOutput
}

GoogleCloudMlV1__AcceleratorConfigPtrInput is an input type that accepts GoogleCloudMlV1__AcceleratorConfigArgs, GoogleCloudMlV1__AcceleratorConfigPtr and GoogleCloudMlV1__AcceleratorConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__AcceleratorConfigPtrInput` via: 

        GoogleCloudMlV1__AcceleratorConfigArgs{...}

or:

        nil

func GoogleCloudMlV1__AcceleratorConfigPtr 

func GoogleCloudMlV1__AcceleratorConfigPtr(v *GoogleCloudMlV1__AcceleratorConfigArgs) GoogleCloudMlV1__AcceleratorConfigPtrInput

type GoogleCloudMlV1__AcceleratorConfigPtrOutput 

type GoogleCloudMlV1__AcceleratorConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__AcceleratorConfigPtrOutput) Count 

func (o GoogleCloudMlV1__AcceleratorConfigPtrOutput) Count() pulumi.StringPtrOutput

The number of accelerators to attach to each machine running the job.

func (GoogleCloudMlV1__AcceleratorConfigPtrOutput) Elem 

func (o GoogleCloudMlV1__AcceleratorConfigPtrOutput) Elem() GoogleCloudMlV1__AcceleratorConfigOutput

func (GoogleCloudMlV1__AcceleratorConfigPtrOutput) ElementType 

func (GoogleCloudMlV1__AcceleratorConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AcceleratorConfigPtrOutput) ToGoogleCloudMlV1__AcceleratorConfigPtrOutput 

func (o GoogleCloudMlV1__AcceleratorConfigPtrOutput) ToGoogleCloudMlV1__AcceleratorConfigPtrOutput() GoogleCloudMlV1__AcceleratorConfigPtrOutput

func (GoogleCloudMlV1__AcceleratorConfigPtrOutput) ToGoogleCloudMlV1__AcceleratorConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__AcceleratorConfigPtrOutput) ToGoogleCloudMlV1__AcceleratorConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigPtrOutput

func (GoogleCloudMlV1__AcceleratorConfigPtrOutput) Type 

func (o GoogleCloudMlV1__AcceleratorConfigPtrOutput) Type() GoogleCloudMlV1__AcceleratorConfigTypePtrOutput

The type of accelerator to use.

type GoogleCloudMlV1__AcceleratorConfigResponse 

type GoogleCloudMlV1__AcceleratorConfigResponse struct {
	// The number of accelerators to attach to each machine running the job.
	Count string `pulumi:"count"`
	// The type of accelerator to use.
	Type string `pulumi:"type"`
}

Represents a hardware accelerator request config. Note that the AcceleratorConfig can be used in both Jobs and Versions. Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and [accelerators for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).

type GoogleCloudMlV1__AcceleratorConfigResponseOutput 

type GoogleCloudMlV1__AcceleratorConfigResponseOutput struct{ *pulumi.OutputState }

Represents a hardware accelerator request config. Note that the AcceleratorConfig can be used in both Jobs and Versions. Learn more about [accelerators for training](/ml-engine/docs/using-gpus) and [accelerators for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).

func (GoogleCloudMlV1__AcceleratorConfigResponseOutput) Count 

func (o GoogleCloudMlV1__AcceleratorConfigResponseOutput) Count() pulumi.StringOutput

The number of accelerators to attach to each machine running the job.

func (GoogleCloudMlV1__AcceleratorConfigResponseOutput) ElementType 

func (GoogleCloudMlV1__AcceleratorConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AcceleratorConfigResponseOutput) ToGoogleCloudMlV1__AcceleratorConfigResponseOutput 

func (o GoogleCloudMlV1__AcceleratorConfigResponseOutput) ToGoogleCloudMlV1__AcceleratorConfigResponseOutput() GoogleCloudMlV1__AcceleratorConfigResponseOutput

func (GoogleCloudMlV1__AcceleratorConfigResponseOutput) ToGoogleCloudMlV1__AcceleratorConfigResponseOutputWithContext 

func (o GoogleCloudMlV1__AcceleratorConfigResponseOutput) ToGoogleCloudMlV1__AcceleratorConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigResponseOutput

func (GoogleCloudMlV1__AcceleratorConfigResponseOutput) Type 

func (o GoogleCloudMlV1__AcceleratorConfigResponseOutput) Type() pulumi.StringOutput

The type of accelerator to use.

type GoogleCloudMlV1__AcceleratorConfigType added in v0.4.0 

type GoogleCloudMlV1__AcceleratorConfigType string

The type of accelerator to use.

func (GoogleCloudMlV1__AcceleratorConfigType) ElementType added in v0.4.0 

func (GoogleCloudMlV1__AcceleratorConfigType) ElementType() reflect.Type

func (GoogleCloudMlV1__AcceleratorConfigType) ToGoogleCloudMlV1__AcceleratorConfigTypeOutput added in v0.6.0 

func (e GoogleCloudMlV1__AcceleratorConfigType) ToGoogleCloudMlV1__AcceleratorConfigTypeOutput() GoogleCloudMlV1__AcceleratorConfigTypeOutput

func (GoogleCloudMlV1__AcceleratorConfigType) ToGoogleCloudMlV1__AcceleratorConfigTypeOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__AcceleratorConfigType) ToGoogleCloudMlV1__AcceleratorConfigTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigTypeOutput

func (GoogleCloudMlV1__AcceleratorConfigType) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__AcceleratorConfigType) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutput() GoogleCloudMlV1__AcceleratorConfigTypePtrOutput

func (GoogleCloudMlV1__AcceleratorConfigType) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__AcceleratorConfigType) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigTypePtrOutput

func (GoogleCloudMlV1__AcceleratorConfigType) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__AcceleratorConfigType) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__AcceleratorConfigType) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__AcceleratorConfigType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__AcceleratorConfigType) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__AcceleratorConfigType) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__AcceleratorConfigType) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__AcceleratorConfigType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__AcceleratorConfigTypeInput added in v0.6.0 

type GoogleCloudMlV1__AcceleratorConfigTypeInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__AcceleratorConfigTypeOutput() GoogleCloudMlV1__AcceleratorConfigTypeOutput
	ToGoogleCloudMlV1__AcceleratorConfigTypeOutputWithContext(context.Context) GoogleCloudMlV1__AcceleratorConfigTypeOutput
}

GoogleCloudMlV1__AcceleratorConfigTypeInput is an input type that accepts GoogleCloudMlV1__AcceleratorConfigTypeArgs and GoogleCloudMlV1__AcceleratorConfigTypeOutput values. You can construct a concrete instance of `GoogleCloudMlV1__AcceleratorConfigTypeInput` via: 

GoogleCloudMlV1__AcceleratorConfigTypeArgs{...}

type GoogleCloudMlV1__AcceleratorConfigTypeOutput added in v0.6.0 

type GoogleCloudMlV1__AcceleratorConfigTypeOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToGoogleCloudMlV1__AcceleratorConfigTypeOutput added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToGoogleCloudMlV1__AcceleratorConfigTypeOutput() GoogleCloudMlV1__AcceleratorConfigTypeOutput

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToGoogleCloudMlV1__AcceleratorConfigTypeOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToGoogleCloudMlV1__AcceleratorConfigTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigTypeOutput

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutput() GoogleCloudMlV1__AcceleratorConfigTypePtrOutput

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigTypePtrOutput

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__AcceleratorConfigTypePtrInput added in v0.6.0 

type GoogleCloudMlV1__AcceleratorConfigTypePtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutput() GoogleCloudMlV1__AcceleratorConfigTypePtrOutput
	ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutputWithContext(context.Context) GoogleCloudMlV1__AcceleratorConfigTypePtrOutput
}

func GoogleCloudMlV1__AcceleratorConfigTypePtr added in v0.6.0 

func GoogleCloudMlV1__AcceleratorConfigTypePtr(v string) GoogleCloudMlV1__AcceleratorConfigTypePtrInput

type GoogleCloudMlV1__AcceleratorConfigTypePtrOutput added in v0.6.0 

type GoogleCloudMlV1__AcceleratorConfigTypePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) Elem() GoogleCloudMlV1__AcceleratorConfigTypeOutput

func (GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutput() GoogleCloudMlV1__AcceleratorConfigTypePtrOutput

func (GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ToGoogleCloudMlV1__AcceleratorConfigTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AcceleratorConfigTypePtrOutput

func (GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__AcceleratorConfigTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__AutoScaling 

type GoogleCloudMlV1__AutoScaling struct {
	// The maximum number of nodes to scale this model under load. The actual value will depend on resource quota and availability.
	MaxNodes *int `pulumi:"maxNodes"`
	// MetricSpec contains the specifications to use to calculate the desired nodes count.
	Metrics []GoogleCloudMlV1__MetricSpec `pulumi:"metrics"`
	// Optional. The minimum number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed. Therefore, the cost of operating this model will be at least `rate` * `min_nodes` * number of hours since last billing cycle, where `rate` is the cost per node-hour as documented in the [pricing guide](/ml-engine/docs/pricing), even if no predictions are performed. There is additional cost for each prediction performed. Unlike manual scaling, if the load gets too heavy for the nodes that are up, the service will automatically add nodes to handle the increased load as well as scale back as traffic drops, always maintaining at least `min_nodes`. You will be charged for the time in which additional nodes are used. If `min_nodes` is not specified and AutoScaling is used with a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 0, in which case, when traffic to a model stops (and after a cool-down period), nodes will be shut down and no charges will be incurred until traffic to the model resumes. If `min_nodes` is not specified and AutoScaling is used with a [Compute Engine (N1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 1. `min_nodes` must be at least 1 for use with a Compute Engine machine type. You can set `min_nodes` when creating the model version, and you can also update `min_nodes` for an existing version: update_body.json: { 'autoScaling': { 'minNodes': 5 } } HTTP request: PATCH https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes -d @./update_body.json
	MinNodes *int `pulumi:"minNodes"`
}

Options for automatically scaling a model.

type GoogleCloudMlV1__AutoScalingArgs 

type GoogleCloudMlV1__AutoScalingArgs struct {
	// The maximum number of nodes to scale this model under load. The actual value will depend on resource quota and availability.
	MaxNodes pulumi.IntPtrInput `pulumi:"maxNodes"`
	// MetricSpec contains the specifications to use to calculate the desired nodes count.
	Metrics GoogleCloudMlV1__MetricSpecArrayInput `pulumi:"metrics"`
	// Optional. The minimum number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed. Therefore, the cost of operating this model will be at least `rate` * `min_nodes` * number of hours since last billing cycle, where `rate` is the cost per node-hour as documented in the [pricing guide](/ml-engine/docs/pricing), even if no predictions are performed. There is additional cost for each prediction performed. Unlike manual scaling, if the load gets too heavy for the nodes that are up, the service will automatically add nodes to handle the increased load as well as scale back as traffic drops, always maintaining at least `min_nodes`. You will be charged for the time in which additional nodes are used. If `min_nodes` is not specified and AutoScaling is used with a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 0, in which case, when traffic to a model stops (and after a cool-down period), nodes will be shut down and no charges will be incurred until traffic to the model resumes. If `min_nodes` is not specified and AutoScaling is used with a [Compute Engine (N1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 1. `min_nodes` must be at least 1 for use with a Compute Engine machine type. You can set `min_nodes` when creating the model version, and you can also update `min_nodes` for an existing version: update_body.json: { 'autoScaling': { 'minNodes': 5 } } HTTP request: PATCH https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes -d @./update_body.json
	MinNodes pulumi.IntPtrInput `pulumi:"minNodes"`
}

Options for automatically scaling a model.

func (GoogleCloudMlV1__AutoScalingArgs) ElementType 

func (GoogleCloudMlV1__AutoScalingArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__AutoScalingArgs) ToGoogleCloudMlV1__AutoScalingOutput 

func (i GoogleCloudMlV1__AutoScalingArgs) ToGoogleCloudMlV1__AutoScalingOutput() GoogleCloudMlV1__AutoScalingOutput

func (GoogleCloudMlV1__AutoScalingArgs) ToGoogleCloudMlV1__AutoScalingOutputWithContext 

func (i GoogleCloudMlV1__AutoScalingArgs) ToGoogleCloudMlV1__AutoScalingOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutoScalingOutput

func (GoogleCloudMlV1__AutoScalingArgs) ToGoogleCloudMlV1__AutoScalingPtrOutput 

func (i GoogleCloudMlV1__AutoScalingArgs) ToGoogleCloudMlV1__AutoScalingPtrOutput() GoogleCloudMlV1__AutoScalingPtrOutput

func (GoogleCloudMlV1__AutoScalingArgs) ToGoogleCloudMlV1__AutoScalingPtrOutputWithContext 

func (i GoogleCloudMlV1__AutoScalingArgs) ToGoogleCloudMlV1__AutoScalingPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutoScalingPtrOutput

type GoogleCloudMlV1__AutoScalingInput 

type GoogleCloudMlV1__AutoScalingInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__AutoScalingOutput() GoogleCloudMlV1__AutoScalingOutput
	ToGoogleCloudMlV1__AutoScalingOutputWithContext(context.Context) GoogleCloudMlV1__AutoScalingOutput
}

GoogleCloudMlV1__AutoScalingInput is an input type that accepts GoogleCloudMlV1__AutoScalingArgs and GoogleCloudMlV1__AutoScalingOutput values. You can construct a concrete instance of `GoogleCloudMlV1__AutoScalingInput` via: 

GoogleCloudMlV1__AutoScalingArgs{...}

type GoogleCloudMlV1__AutoScalingOutput 

type GoogleCloudMlV1__AutoScalingOutput struct{ *pulumi.OutputState }

Options for automatically scaling a model.

func (GoogleCloudMlV1__AutoScalingOutput) ElementType 

func (GoogleCloudMlV1__AutoScalingOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AutoScalingOutput) MaxNodes 

func (o GoogleCloudMlV1__AutoScalingOutput) MaxNodes() pulumi.IntPtrOutput

The maximum number of nodes to scale this model under load. The actual value will depend on resource quota and availability.

func (GoogleCloudMlV1__AutoScalingOutput) Metrics 

func (o GoogleCloudMlV1__AutoScalingOutput) Metrics() GoogleCloudMlV1__MetricSpecArrayOutput

MetricSpec contains the specifications to use to calculate the desired nodes count.

func (GoogleCloudMlV1__AutoScalingOutput) MinNodes 

func (o GoogleCloudMlV1__AutoScalingOutput) MinNodes() pulumi.IntPtrOutput

Optional. The minimum number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed. Therefore, the cost of operating this model will be at least `rate` * `min_nodes` * number of hours since last billing cycle, where `rate` is the cost per node-hour as documented in the [pricing guide](/ml-engine/docs/pricing), even if no predictions are performed. There is additional cost for each prediction performed. Unlike manual scaling, if the load gets too heavy for the nodes that are up, the service will automatically add nodes to handle the increased load as well as scale back as traffic drops, always maintaining at least `min_nodes`. You will be charged for the time in which additional nodes are used. If `min_nodes` is not specified and AutoScaling is used with a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 0, in which case, when traffic to a model stops (and after a cool-down period), nodes will be shut down and no charges will be incurred until traffic to the model resumes. If `min_nodes` is not specified and AutoScaling is used with a [Compute Engine (N1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 1. `min_nodes` must be at least 1 for use with a Compute Engine machine type. You can set `min_nodes` when creating the model version, and you can also update `min_nodes` for an existing version: update_body.json: { 'autoScaling': { 'minNodes': 5 } } HTTP request: PATCH https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes -d @./update_body.json

func (GoogleCloudMlV1__AutoScalingOutput) ToGoogleCloudMlV1__AutoScalingOutput 

func (o GoogleCloudMlV1__AutoScalingOutput) ToGoogleCloudMlV1__AutoScalingOutput() GoogleCloudMlV1__AutoScalingOutput

func (GoogleCloudMlV1__AutoScalingOutput) ToGoogleCloudMlV1__AutoScalingOutputWithContext 

func (o GoogleCloudMlV1__AutoScalingOutput) ToGoogleCloudMlV1__AutoScalingOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutoScalingOutput

func (GoogleCloudMlV1__AutoScalingOutput) ToGoogleCloudMlV1__AutoScalingPtrOutput 

func (o GoogleCloudMlV1__AutoScalingOutput) ToGoogleCloudMlV1__AutoScalingPtrOutput() GoogleCloudMlV1__AutoScalingPtrOutput

func (GoogleCloudMlV1__AutoScalingOutput) ToGoogleCloudMlV1__AutoScalingPtrOutputWithContext 

func (o GoogleCloudMlV1__AutoScalingOutput) ToGoogleCloudMlV1__AutoScalingPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutoScalingPtrOutput

type GoogleCloudMlV1__AutoScalingPtrInput 

type GoogleCloudMlV1__AutoScalingPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__AutoScalingPtrOutput() GoogleCloudMlV1__AutoScalingPtrOutput
	ToGoogleCloudMlV1__AutoScalingPtrOutputWithContext(context.Context) GoogleCloudMlV1__AutoScalingPtrOutput
}

GoogleCloudMlV1__AutoScalingPtrInput is an input type that accepts GoogleCloudMlV1__AutoScalingArgs, GoogleCloudMlV1__AutoScalingPtr and GoogleCloudMlV1__AutoScalingPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__AutoScalingPtrInput` via: 

        GoogleCloudMlV1__AutoScalingArgs{...}

or:

        nil

func GoogleCloudMlV1__AutoScalingPtr 

func GoogleCloudMlV1__AutoScalingPtr(v *GoogleCloudMlV1__AutoScalingArgs) GoogleCloudMlV1__AutoScalingPtrInput

type GoogleCloudMlV1__AutoScalingPtrOutput 

type GoogleCloudMlV1__AutoScalingPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__AutoScalingPtrOutput) Elem 

func (o GoogleCloudMlV1__AutoScalingPtrOutput) Elem() GoogleCloudMlV1__AutoScalingOutput

func (GoogleCloudMlV1__AutoScalingPtrOutput) ElementType 

func (GoogleCloudMlV1__AutoScalingPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AutoScalingPtrOutput) MaxNodes 

func (o GoogleCloudMlV1__AutoScalingPtrOutput) MaxNodes() pulumi.IntPtrOutput

The maximum number of nodes to scale this model under load. The actual value will depend on resource quota and availability.

func (GoogleCloudMlV1__AutoScalingPtrOutput) Metrics 

func (o GoogleCloudMlV1__AutoScalingPtrOutput) Metrics() GoogleCloudMlV1__MetricSpecArrayOutput

MetricSpec contains the specifications to use to calculate the desired nodes count.

func (GoogleCloudMlV1__AutoScalingPtrOutput) MinNodes 

func (o GoogleCloudMlV1__AutoScalingPtrOutput) MinNodes() pulumi.IntPtrOutput

Optional. The minimum number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed. Therefore, the cost of operating this model will be at least `rate` * `min_nodes` * number of hours since last billing cycle, where `rate` is the cost per node-hour as documented in the [pricing guide](/ml-engine/docs/pricing), even if no predictions are performed. There is additional cost for each prediction performed. Unlike manual scaling, if the load gets too heavy for the nodes that are up, the service will automatically add nodes to handle the increased load as well as scale back as traffic drops, always maintaining at least `min_nodes`. You will be charged for the time in which additional nodes are used. If `min_nodes` is not specified and AutoScaling is used with a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 0, in which case, when traffic to a model stops (and after a cool-down period), nodes will be shut down and no charges will be incurred until traffic to the model resumes. If `min_nodes` is not specified and AutoScaling is used with a [Compute Engine (N1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 1. `min_nodes` must be at least 1 for use with a Compute Engine machine type. You can set `min_nodes` when creating the model version, and you can also update `min_nodes` for an existing version: update_body.json: { 'autoScaling': { 'minNodes': 5 } } HTTP request: PATCH https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes -d @./update_body.json

func (GoogleCloudMlV1__AutoScalingPtrOutput) ToGoogleCloudMlV1__AutoScalingPtrOutput 

func (o GoogleCloudMlV1__AutoScalingPtrOutput) ToGoogleCloudMlV1__AutoScalingPtrOutput() GoogleCloudMlV1__AutoScalingPtrOutput

func (GoogleCloudMlV1__AutoScalingPtrOutput) ToGoogleCloudMlV1__AutoScalingPtrOutputWithContext 

func (o GoogleCloudMlV1__AutoScalingPtrOutput) ToGoogleCloudMlV1__AutoScalingPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutoScalingPtrOutput

type GoogleCloudMlV1__AutoScalingResponse 

type GoogleCloudMlV1__AutoScalingResponse struct {
	// The maximum number of nodes to scale this model under load. The actual value will depend on resource quota and availability.
	MaxNodes int `pulumi:"maxNodes"`
	// MetricSpec contains the specifications to use to calculate the desired nodes count.
	Metrics []GoogleCloudMlV1__MetricSpecResponse `pulumi:"metrics"`
	// Optional. The minimum number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed. Therefore, the cost of operating this model will be at least `rate` * `min_nodes` * number of hours since last billing cycle, where `rate` is the cost per node-hour as documented in the [pricing guide](/ml-engine/docs/pricing), even if no predictions are performed. There is additional cost for each prediction performed. Unlike manual scaling, if the load gets too heavy for the nodes that are up, the service will automatically add nodes to handle the increased load as well as scale back as traffic drops, always maintaining at least `min_nodes`. You will be charged for the time in which additional nodes are used. If `min_nodes` is not specified and AutoScaling is used with a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 0, in which case, when traffic to a model stops (and after a cool-down period), nodes will be shut down and no charges will be incurred until traffic to the model resumes. If `min_nodes` is not specified and AutoScaling is used with a [Compute Engine (N1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 1. `min_nodes` must be at least 1 for use with a Compute Engine machine type. You can set `min_nodes` when creating the model version, and you can also update `min_nodes` for an existing version: update_body.json: { 'autoScaling': { 'minNodes': 5 } } HTTP request: PATCH https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes -d @./update_body.json
	MinNodes int `pulumi:"minNodes"`
}

Options for automatically scaling a model.

type GoogleCloudMlV1__AutoScalingResponseOutput 

type GoogleCloudMlV1__AutoScalingResponseOutput struct{ *pulumi.OutputState }

Options for automatically scaling a model.

func (GoogleCloudMlV1__AutoScalingResponseOutput) ElementType 

func (GoogleCloudMlV1__AutoScalingResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AutoScalingResponseOutput) MaxNodes 

func (o GoogleCloudMlV1__AutoScalingResponseOutput) MaxNodes() pulumi.IntOutput

The maximum number of nodes to scale this model under load. The actual value will depend on resource quota and availability.

func (GoogleCloudMlV1__AutoScalingResponseOutput) Metrics 

func (o GoogleCloudMlV1__AutoScalingResponseOutput) Metrics() GoogleCloudMlV1__MetricSpecResponseArrayOutput

MetricSpec contains the specifications to use to calculate the desired nodes count.

func (GoogleCloudMlV1__AutoScalingResponseOutput) MinNodes 

func (o GoogleCloudMlV1__AutoScalingResponseOutput) MinNodes() pulumi.IntOutput

Optional. The minimum number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed. Therefore, the cost of operating this model will be at least `rate` * `min_nodes` * number of hours since last billing cycle, where `rate` is the cost per node-hour as documented in the [pricing guide](/ml-engine/docs/pricing), even if no predictions are performed. There is additional cost for each prediction performed. Unlike manual scaling, if the load gets too heavy for the nodes that are up, the service will automatically add nodes to handle the increased load as well as scale back as traffic drops, always maintaining at least `min_nodes`. You will be charged for the time in which additional nodes are used. If `min_nodes` is not specified and AutoScaling is used with a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 0, in which case, when traffic to a model stops (and after a cool-down period), nodes will be shut down and no charges will be incurred until traffic to the model resumes. If `min_nodes` is not specified and AutoScaling is used with a [Compute Engine (N1) machine type](/ml-engine/docs/machine-types-online-prediction), `min_nodes` defaults to 1. `min_nodes` must be at least 1 for use with a Compute Engine machine type. You can set `min_nodes` when creating the model version, and you can also update `min_nodes` for an existing version: update_body.json: { 'autoScaling': { 'minNodes': 5 } } HTTP request: PATCH https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes -d @./update_body.json

func (GoogleCloudMlV1__AutoScalingResponseOutput) ToGoogleCloudMlV1__AutoScalingResponseOutput 

func (o GoogleCloudMlV1__AutoScalingResponseOutput) ToGoogleCloudMlV1__AutoScalingResponseOutput() GoogleCloudMlV1__AutoScalingResponseOutput

func (GoogleCloudMlV1__AutoScalingResponseOutput) ToGoogleCloudMlV1__AutoScalingResponseOutputWithContext 

func (o GoogleCloudMlV1__AutoScalingResponseOutput) ToGoogleCloudMlV1__AutoScalingResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutoScalingResponseOutput

type GoogleCloudMlV1__AutomatedStoppingConfig 

type GoogleCloudMlV1__AutomatedStoppingConfig struct {
	DecayCurveStoppingConfig      *GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfig `pulumi:"decayCurveStoppingConfig"`
	MedianAutomatedStoppingConfig *GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfig     `pulumi:"medianAutomatedStoppingConfig"`
}

Configuration for Automated Early Stopping of Trials. If no implementation_config is set, automated early stopping will not be run.

type GoogleCloudMlV1__AutomatedStoppingConfigArgs 

type GoogleCloudMlV1__AutomatedStoppingConfigArgs struct {
	DecayCurveStoppingConfig      GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrInput `pulumi:"decayCurveStoppingConfig"`
	MedianAutomatedStoppingConfig GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrInput     `pulumi:"medianAutomatedStoppingConfig"`
}

Configuration for Automated Early Stopping of Trials. If no implementation_config is set, automated early stopping will not be run.

func (GoogleCloudMlV1__AutomatedStoppingConfigArgs) ElementType 

func (GoogleCloudMlV1__AutomatedStoppingConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__AutomatedStoppingConfigArgs) ToGoogleCloudMlV1__AutomatedStoppingConfigOutput 

func (i GoogleCloudMlV1__AutomatedStoppingConfigArgs) ToGoogleCloudMlV1__AutomatedStoppingConfigOutput() GoogleCloudMlV1__AutomatedStoppingConfigOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigArgs) ToGoogleCloudMlV1__AutomatedStoppingConfigOutputWithContext 

func (i GoogleCloudMlV1__AutomatedStoppingConfigArgs) ToGoogleCloudMlV1__AutomatedStoppingConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutomatedStoppingConfigOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigArgs) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutput 

func (i GoogleCloudMlV1__AutomatedStoppingConfigArgs) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutput() GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigArgs) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutputWithContext 

func (i GoogleCloudMlV1__AutomatedStoppingConfigArgs) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput

type GoogleCloudMlV1__AutomatedStoppingConfigInput 

type GoogleCloudMlV1__AutomatedStoppingConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__AutomatedStoppingConfigOutput() GoogleCloudMlV1__AutomatedStoppingConfigOutput
	ToGoogleCloudMlV1__AutomatedStoppingConfigOutputWithContext(context.Context) GoogleCloudMlV1__AutomatedStoppingConfigOutput
}

GoogleCloudMlV1__AutomatedStoppingConfigInput is an input type that accepts GoogleCloudMlV1__AutomatedStoppingConfigArgs and GoogleCloudMlV1__AutomatedStoppingConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1__AutomatedStoppingConfigInput` via: 

GoogleCloudMlV1__AutomatedStoppingConfigArgs{...}

type GoogleCloudMlV1__AutomatedStoppingConfigOutput 

type GoogleCloudMlV1__AutomatedStoppingConfigOutput struct{ *pulumi.OutputState }

Configuration for Automated Early Stopping of Trials. If no implementation_config is set, automated early stopping will not be run.

func (GoogleCloudMlV1__AutomatedStoppingConfigOutput) DecayCurveStoppingConfig 

func (o GoogleCloudMlV1__AutomatedStoppingConfigOutput) DecayCurveStoppingConfig() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigOutput) ElementType 

func (GoogleCloudMlV1__AutomatedStoppingConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AutomatedStoppingConfigOutput) MedianAutomatedStoppingConfig 

func (o GoogleCloudMlV1__AutomatedStoppingConfigOutput) MedianAutomatedStoppingConfig() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigOutput 

func (o GoogleCloudMlV1__AutomatedStoppingConfigOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigOutput() GoogleCloudMlV1__AutomatedStoppingConfigOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigOutputWithContext 

func (o GoogleCloudMlV1__AutomatedStoppingConfigOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutomatedStoppingConfigOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutput 

func (o GoogleCloudMlV1__AutomatedStoppingConfigOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutput() GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__AutomatedStoppingConfigOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput

type GoogleCloudMlV1__AutomatedStoppingConfigPtrInput 

type GoogleCloudMlV1__AutomatedStoppingConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutput() GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput
	ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutputWithContext(context.Context) GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput
}

GoogleCloudMlV1__AutomatedStoppingConfigPtrInput is an input type that accepts GoogleCloudMlV1__AutomatedStoppingConfigArgs, GoogleCloudMlV1__AutomatedStoppingConfigPtr and GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__AutomatedStoppingConfigPtrInput` via: 

        GoogleCloudMlV1__AutomatedStoppingConfigArgs{...}

or:

        nil

func GoogleCloudMlV1__AutomatedStoppingConfigPtr 

func GoogleCloudMlV1__AutomatedStoppingConfigPtr(v *GoogleCloudMlV1__AutomatedStoppingConfigArgs) GoogleCloudMlV1__AutomatedStoppingConfigPtrInput

type GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput 

type GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) DecayCurveStoppingConfig 

func (o GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) DecayCurveStoppingConfig() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) Elem 

func (o GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) Elem() GoogleCloudMlV1__AutomatedStoppingConfigOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) ElementType 

func (GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) MedianAutomatedStoppingConfig 

func (o GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) MedianAutomatedStoppingConfig() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutput 

func (o GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutput() GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput

type GoogleCloudMlV1__AutomatedStoppingConfigResponse 

type GoogleCloudMlV1__AutomatedStoppingConfigResponse struct {
	DecayCurveStoppingConfig      GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponse `pulumi:"decayCurveStoppingConfig"`
	MedianAutomatedStoppingConfig GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponse     `pulumi:"medianAutomatedStoppingConfig"`
}

Configuration for Automated Early Stopping of Trials. If no implementation_config is set, automated early stopping will not be run.

type GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput 

type GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput struct{ *pulumi.OutputState }

Configuration for Automated Early Stopping of Trials. If no implementation_config is set, automated early stopping will not be run.

func (GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) DecayCurveStoppingConfig 

func (o GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) DecayCurveStoppingConfig() GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) ElementType 

func (GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) MedianAutomatedStoppingConfig 

func (o GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) MedianAutomatedStoppingConfig() GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigResponseOutput 

func (o GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigResponseOutput() GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput

func (GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigResponseOutputWithContext 

func (o GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput) ToGoogleCloudMlV1__AutomatedStoppingConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput

type GoogleCloudMlV1__BuiltInAlgorithmOutput 

type GoogleCloudMlV1__BuiltInAlgorithmOutput struct {
	// Framework on which the built-in algorithm was trained.
	Framework *string `pulumi:"framework"`
	// The Cloud Storage path to the `model/` directory where the training job saves the trained model. Only set for successful jobs that don't use hyperparameter tuning.
	ModelPath *string `pulumi:"modelPath"`
	// Python version on which the built-in algorithm was trained.
	PythonVersion *string `pulumi:"pythonVersion"`
	// AI Platform runtime version on which the built-in algorithm was trained.
	RuntimeVersion *string `pulumi:"runtimeVersion"`
}

Represents output related to a built-in algorithm Job.

type GoogleCloudMlV1__BuiltInAlgorithmOutputArgs 

type GoogleCloudMlV1__BuiltInAlgorithmOutputArgs struct {
	// Framework on which the built-in algorithm was trained.
	Framework pulumi.StringPtrInput `pulumi:"framework"`
	// The Cloud Storage path to the `model/` directory where the training job saves the trained model. Only set for successful jobs that don't use hyperparameter tuning.
	ModelPath pulumi.StringPtrInput `pulumi:"modelPath"`
	// Python version on which the built-in algorithm was trained.
	PythonVersion pulumi.StringPtrInput `pulumi:"pythonVersion"`
	// AI Platform runtime version on which the built-in algorithm was trained.
	RuntimeVersion pulumi.StringPtrInput `pulumi:"runtimeVersion"`
}

Represents output related to a built-in algorithm Job.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ElementType 

func (GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutput 

func (i GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputOutput

func (GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutputWithContext 

func (i GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutputWithContext(ctx context.Context) GoogleCloudMlV1__BuiltInAlgorithmOutputOutput

func (GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput 

func (i GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput

func (GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutputWithContext 

func (i GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput

type GoogleCloudMlV1__BuiltInAlgorithmOutputInput 

type GoogleCloudMlV1__BuiltInAlgorithmOutputInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputOutput
	ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutputWithContext(context.Context) GoogleCloudMlV1__BuiltInAlgorithmOutputOutput
}

GoogleCloudMlV1__BuiltInAlgorithmOutputInput is an input type that accepts GoogleCloudMlV1__BuiltInAlgorithmOutputArgs and GoogleCloudMlV1__BuiltInAlgorithmOutputOutput values. You can construct a concrete instance of `GoogleCloudMlV1__BuiltInAlgorithmOutputInput` via: 

GoogleCloudMlV1__BuiltInAlgorithmOutputArgs{...}

type GoogleCloudMlV1__BuiltInAlgorithmOutputOutput 

type GoogleCloudMlV1__BuiltInAlgorithmOutputOutput struct{ *pulumi.OutputState }

Represents output related to a built-in algorithm Job.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ElementType 

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) Framework 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) Framework() pulumi.StringPtrOutput

Framework on which the built-in algorithm was trained.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ModelPath 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ModelPath() pulumi.StringPtrOutput

The Cloud Storage path to the `model/` directory where the training job saves the trained model. Only set for successful jobs that don't use hyperparameter tuning.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) PythonVersion 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) PythonVersion() pulumi.StringPtrOutput

Python version on which the built-in algorithm was trained.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) RuntimeVersion 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) RuntimeVersion() pulumi.StringPtrOutput

AI Platform runtime version on which the built-in algorithm was trained.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutput 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputOutput

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutputWithContext 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputOutputWithContext(ctx context.Context) GoogleCloudMlV1__BuiltInAlgorithmOutputOutput

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput

func (GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutputWithContext 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput

type GoogleCloudMlV1__BuiltInAlgorithmOutputPtrInput 

type GoogleCloudMlV1__BuiltInAlgorithmOutputPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput
	ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutputWithContext(context.Context) GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput
}

GoogleCloudMlV1__BuiltInAlgorithmOutputPtrInput is an input type that accepts GoogleCloudMlV1__BuiltInAlgorithmOutputArgs, GoogleCloudMlV1__BuiltInAlgorithmOutputPtr and GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__BuiltInAlgorithmOutputPtrInput` via: 

        GoogleCloudMlV1__BuiltInAlgorithmOutputArgs{...}

or:

        nil

func GoogleCloudMlV1__BuiltInAlgorithmOutputPtr 

func GoogleCloudMlV1__BuiltInAlgorithmOutputPtr(v *GoogleCloudMlV1__BuiltInAlgorithmOutputArgs) GoogleCloudMlV1__BuiltInAlgorithmOutputPtrInput

type GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput 

type GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) Elem 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) Elem() GoogleCloudMlV1__BuiltInAlgorithmOutputOutput

func (GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) ElementType 

func (GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) Framework 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) Framework() pulumi.StringPtrOutput

Framework on which the built-in algorithm was trained.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) ModelPath 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) ModelPath() pulumi.StringPtrOutput

The Cloud Storage path to the `model/` directory where the training job saves the trained model. Only set for successful jobs that don't use hyperparameter tuning.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) PythonVersion 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) PythonVersion() pulumi.StringPtrOutput

Python version on which the built-in algorithm was trained.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) RuntimeVersion 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) RuntimeVersion() pulumi.StringPtrOutput

AI Platform runtime version on which the built-in algorithm was trained.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput

func (GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutputWithContext 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput

type GoogleCloudMlV1__BuiltInAlgorithmOutputResponse 

type GoogleCloudMlV1__BuiltInAlgorithmOutputResponse struct {
	// Framework on which the built-in algorithm was trained.
	Framework string `pulumi:"framework"`
	// The Cloud Storage path to the `model/` directory where the training job saves the trained model. Only set for successful jobs that don't use hyperparameter tuning.
	ModelPath string `pulumi:"modelPath"`
	// Python version on which the built-in algorithm was trained.
	PythonVersion string `pulumi:"pythonVersion"`
	// AI Platform runtime version on which the built-in algorithm was trained.
	RuntimeVersion string `pulumi:"runtimeVersion"`
}

Represents output related to a built-in algorithm Job.

type GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput 

type GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput struct{ *pulumi.OutputState }

Represents output related to a built-in algorithm Job.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) ElementType 

func (GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) Framework 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) Framework() pulumi.StringOutput

Framework on which the built-in algorithm was trained.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) ModelPath 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) ModelPath() pulumi.StringOutput

The Cloud Storage path to the `model/` directory where the training job saves the trained model. Only set for successful jobs that don't use hyperparameter tuning.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) PythonVersion 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) PythonVersion() pulumi.StringOutput

Python version on which the built-in algorithm was trained.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) RuntimeVersion 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) RuntimeVersion() pulumi.StringOutput

AI Platform runtime version on which the built-in algorithm was trained.

func (GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput

func (GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutputWithContext 

func (o GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput) ToGoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput

type GoogleCloudMlV1__ContainerPort 

type GoogleCloudMlV1__ContainerPort struct {
	// Number of the port to expose on the container. This must be a valid port number: 0 < PORT_NUMBER < 65536.
	ContainerPort *int `pulumi:"containerPort"`
}

Represents a network port in a single container. This message is a subset of the [Kubernetes ContainerPort v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#containerport-v1-core).

type GoogleCloudMlV1__ContainerPortArgs 

type GoogleCloudMlV1__ContainerPortArgs struct {
	// Number of the port to expose on the container. This must be a valid port number: 0 < PORT_NUMBER < 65536.
	ContainerPort pulumi.IntPtrInput `pulumi:"containerPort"`
}

Represents a network port in a single container. This message is a subset of the [Kubernetes ContainerPort v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#containerport-v1-core).

func (GoogleCloudMlV1__ContainerPortArgs) ElementType 

func (GoogleCloudMlV1__ContainerPortArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerPortArgs) ToGoogleCloudMlV1__ContainerPortOutput 

func (i GoogleCloudMlV1__ContainerPortArgs) ToGoogleCloudMlV1__ContainerPortOutput() GoogleCloudMlV1__ContainerPortOutput

func (GoogleCloudMlV1__ContainerPortArgs) ToGoogleCloudMlV1__ContainerPortOutputWithContext 

func (i GoogleCloudMlV1__ContainerPortArgs) ToGoogleCloudMlV1__ContainerPortOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerPortOutput

type GoogleCloudMlV1__ContainerPortArray 

type GoogleCloudMlV1__ContainerPortArray []GoogleCloudMlV1__ContainerPortInput

func (GoogleCloudMlV1__ContainerPortArray) ElementType 

func (GoogleCloudMlV1__ContainerPortArray) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerPortArray) ToGoogleCloudMlV1__ContainerPortArrayOutput 

func (i GoogleCloudMlV1__ContainerPortArray) ToGoogleCloudMlV1__ContainerPortArrayOutput() GoogleCloudMlV1__ContainerPortArrayOutput

func (GoogleCloudMlV1__ContainerPortArray) ToGoogleCloudMlV1__ContainerPortArrayOutputWithContext 

func (i GoogleCloudMlV1__ContainerPortArray) ToGoogleCloudMlV1__ContainerPortArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerPortArrayOutput

type GoogleCloudMlV1__ContainerPortArrayInput 

type GoogleCloudMlV1__ContainerPortArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ContainerPortArrayOutput() GoogleCloudMlV1__ContainerPortArrayOutput
	ToGoogleCloudMlV1__ContainerPortArrayOutputWithContext(context.Context) GoogleCloudMlV1__ContainerPortArrayOutput
}

GoogleCloudMlV1__ContainerPortArrayInput is an input type that accepts GoogleCloudMlV1__ContainerPortArray and GoogleCloudMlV1__ContainerPortArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ContainerPortArrayInput` via: 

GoogleCloudMlV1__ContainerPortArray{ GoogleCloudMlV1__ContainerPortArgs{...} }

type GoogleCloudMlV1__ContainerPortArrayOutput 

type GoogleCloudMlV1__ContainerPortArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ContainerPortArrayOutput) ElementType 

func (GoogleCloudMlV1__ContainerPortArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerPortArrayOutput) Index 

func (o GoogleCloudMlV1__ContainerPortArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__ContainerPortOutput

func (GoogleCloudMlV1__ContainerPortArrayOutput) ToGoogleCloudMlV1__ContainerPortArrayOutput 

func (o GoogleCloudMlV1__ContainerPortArrayOutput) ToGoogleCloudMlV1__ContainerPortArrayOutput() GoogleCloudMlV1__ContainerPortArrayOutput

func (GoogleCloudMlV1__ContainerPortArrayOutput) ToGoogleCloudMlV1__ContainerPortArrayOutputWithContext 

func (o GoogleCloudMlV1__ContainerPortArrayOutput) ToGoogleCloudMlV1__ContainerPortArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerPortArrayOutput

type GoogleCloudMlV1__ContainerPortInput 

type GoogleCloudMlV1__ContainerPortInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ContainerPortOutput() GoogleCloudMlV1__ContainerPortOutput
	ToGoogleCloudMlV1__ContainerPortOutputWithContext(context.Context) GoogleCloudMlV1__ContainerPortOutput
}

GoogleCloudMlV1__ContainerPortInput is an input type that accepts GoogleCloudMlV1__ContainerPortArgs and GoogleCloudMlV1__ContainerPortOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ContainerPortInput` via: 

GoogleCloudMlV1__ContainerPortArgs{...}

type GoogleCloudMlV1__ContainerPortOutput 

type GoogleCloudMlV1__ContainerPortOutput struct{ *pulumi.OutputState }

Represents a network port in a single container. This message is a subset of the [Kubernetes ContainerPort v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#containerport-v1-core).

func (GoogleCloudMlV1__ContainerPortOutput) ContainerPort 

func (o GoogleCloudMlV1__ContainerPortOutput) ContainerPort() pulumi.IntPtrOutput

Number of the port to expose on the container. This must be a valid port number: 0 < PORT_NUMBER < 65536.

func (GoogleCloudMlV1__ContainerPortOutput) ElementType 

func (GoogleCloudMlV1__ContainerPortOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerPortOutput) ToGoogleCloudMlV1__ContainerPortOutput 

func (o GoogleCloudMlV1__ContainerPortOutput) ToGoogleCloudMlV1__ContainerPortOutput() GoogleCloudMlV1__ContainerPortOutput

func (GoogleCloudMlV1__ContainerPortOutput) ToGoogleCloudMlV1__ContainerPortOutputWithContext 

func (o GoogleCloudMlV1__ContainerPortOutput) ToGoogleCloudMlV1__ContainerPortOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerPortOutput

type GoogleCloudMlV1__ContainerPortResponse 

type GoogleCloudMlV1__ContainerPortResponse struct {
	// Number of the port to expose on the container. This must be a valid port number: 0 < PORT_NUMBER < 65536.
	ContainerPort int `pulumi:"containerPort"`
}

Represents a network port in a single container. This message is a subset of the [Kubernetes ContainerPort v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#containerport-v1-core).

type GoogleCloudMlV1__ContainerPortResponseArrayOutput 

type GoogleCloudMlV1__ContainerPortResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ContainerPortResponseArrayOutput) ElementType 

func (GoogleCloudMlV1__ContainerPortResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerPortResponseArrayOutput) Index 

func (o GoogleCloudMlV1__ContainerPortResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__ContainerPortResponseOutput

func (GoogleCloudMlV1__ContainerPortResponseArrayOutput) ToGoogleCloudMlV1__ContainerPortResponseArrayOutput 

func (o GoogleCloudMlV1__ContainerPortResponseArrayOutput) ToGoogleCloudMlV1__ContainerPortResponseArrayOutput() GoogleCloudMlV1__ContainerPortResponseArrayOutput

func (GoogleCloudMlV1__ContainerPortResponseArrayOutput) ToGoogleCloudMlV1__ContainerPortResponseArrayOutputWithContext 

func (o GoogleCloudMlV1__ContainerPortResponseArrayOutput) ToGoogleCloudMlV1__ContainerPortResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerPortResponseArrayOutput

type GoogleCloudMlV1__ContainerPortResponseOutput 

type GoogleCloudMlV1__ContainerPortResponseOutput struct{ *pulumi.OutputState }

Represents a network port in a single container. This message is a subset of the [Kubernetes ContainerPort v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#containerport-v1-core).

func (GoogleCloudMlV1__ContainerPortResponseOutput) ContainerPort 

func (o GoogleCloudMlV1__ContainerPortResponseOutput) ContainerPort() pulumi.IntOutput

Number of the port to expose on the container. This must be a valid port number: 0 < PORT_NUMBER < 65536.

func (GoogleCloudMlV1__ContainerPortResponseOutput) ElementType 

func (GoogleCloudMlV1__ContainerPortResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerPortResponseOutput) ToGoogleCloudMlV1__ContainerPortResponseOutput 

func (o GoogleCloudMlV1__ContainerPortResponseOutput) ToGoogleCloudMlV1__ContainerPortResponseOutput() GoogleCloudMlV1__ContainerPortResponseOutput

func (GoogleCloudMlV1__ContainerPortResponseOutput) ToGoogleCloudMlV1__ContainerPortResponseOutputWithContext 

func (o GoogleCloudMlV1__ContainerPortResponseOutput) ToGoogleCloudMlV1__ContainerPortResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerPortResponseOutput

type GoogleCloudMlV1__ContainerSpec 

type GoogleCloudMlV1__ContainerSpec struct {
	// Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `commmand` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Args []string `pulumi:"args"`
	// Immutable. Specifies the command that runs when the container starts. This overrides the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Command []string `pulumi:"command"`
	// Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: “` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ]  “` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Env []GoogleCloudMlV1__EnvVar `pulumi:"env"`
	// URI of the Docker image to be used as the custom container for serving predictions. This URI must identify [an image in Artifact Registry](/artifact-registry/docs/overview) and begin with the hostname `{REGION}-docker.pkg.dev`, where `{REGION}` is replaced by the region that matches AI Platform Prediction [regional endpoint](/ai-platform/prediction/docs/regional-endpoints) that you are using. For example, if you are using the `us-central1-ml.googleapis.com` endpoint, then this URI must begin with `us-central1-docker.pkg.dev`. To use a custom container, the [AI Platform Google-managed service account](/ai-platform/prediction/docs/custom-service-account#default) must have permission to pull (read) the Docker image at this URI. The AI Platform Google-managed service account has the following format: `service-{PROJECT_NUMBER}@cloud-ml.google.com.iam.gserviceaccount.com` {PROJECT_NUMBER} is replaced by your Google Cloud project number. By default, this service account has necessary permissions to pull an Artifact Registry image in the same Google Cloud project where you are using AI Platform Prediction. In this case, no configuration is necessary. If you want to use an image from a different Google Cloud project, learn how to [grant the Artifact Registry Reader (roles/artifactregistry.reader) role for a repository](/artifact-registry/docs/access-control#grant-repo) to your projet's AI Platform Google-managed service account. To learn about the requirements for the Docker image itself, read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements).
	Image *string `pulumi:"image"`
	// Immutable. List of ports to expose from the container. AI Platform Prediction sends any prediction requests that it receives to the first port on this list. AI Platform Prediction also sends [liveness and health checks](/ai-platform/prediction/docs/custom-container-requirements#health) to this port. If you do not specify this field, it defaults to following value: “` json [ { "containerPort": 8080 } ]  “` AI Platform Prediction does not use ports other than the first one listed. This field corresponds to the `ports` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Ports []GoogleCloudMlV1__ContainerPort `pulumi:"ports"`
}

Specification of a custom container for serving predictions. This message is a subset of the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

type GoogleCloudMlV1__ContainerSpecArgs 

type GoogleCloudMlV1__ContainerSpecArgs struct {
	// Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `commmand` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Args pulumi.StringArrayInput `pulumi:"args"`
	// Immutable. Specifies the command that runs when the container starts. This overrides the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Command pulumi.StringArrayInput `pulumi:"command"`
	// Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: “` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ]  “` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Env GoogleCloudMlV1__EnvVarArrayInput `pulumi:"env"`
	// URI of the Docker image to be used as the custom container for serving predictions. This URI must identify [an image in Artifact Registry](/artifact-registry/docs/overview) and begin with the hostname `{REGION}-docker.pkg.dev`, where `{REGION}` is replaced by the region that matches AI Platform Prediction [regional endpoint](/ai-platform/prediction/docs/regional-endpoints) that you are using. For example, if you are using the `us-central1-ml.googleapis.com` endpoint, then this URI must begin with `us-central1-docker.pkg.dev`. To use a custom container, the [AI Platform Google-managed service account](/ai-platform/prediction/docs/custom-service-account#default) must have permission to pull (read) the Docker image at this URI. The AI Platform Google-managed service account has the following format: `service-{PROJECT_NUMBER}@cloud-ml.google.com.iam.gserviceaccount.com` {PROJECT_NUMBER} is replaced by your Google Cloud project number. By default, this service account has necessary permissions to pull an Artifact Registry image in the same Google Cloud project where you are using AI Platform Prediction. In this case, no configuration is necessary. If you want to use an image from a different Google Cloud project, learn how to [grant the Artifact Registry Reader (roles/artifactregistry.reader) role for a repository](/artifact-registry/docs/access-control#grant-repo) to your projet's AI Platform Google-managed service account. To learn about the requirements for the Docker image itself, read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements).
	Image pulumi.StringPtrInput `pulumi:"image"`
	// Immutable. List of ports to expose from the container. AI Platform Prediction sends any prediction requests that it receives to the first port on this list. AI Platform Prediction also sends [liveness and health checks](/ai-platform/prediction/docs/custom-container-requirements#health) to this port. If you do not specify this field, it defaults to following value: “` json [ { "containerPort": 8080 } ]  “` AI Platform Prediction does not use ports other than the first one listed. This field corresponds to the `ports` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Ports GoogleCloudMlV1__ContainerPortArrayInput `pulumi:"ports"`
}

Specification of a custom container for serving predictions. This message is a subset of the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecArgs) ElementType 

func (GoogleCloudMlV1__ContainerSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerSpecArgs) ToGoogleCloudMlV1__ContainerSpecOutput 

func (i GoogleCloudMlV1__ContainerSpecArgs) ToGoogleCloudMlV1__ContainerSpecOutput() GoogleCloudMlV1__ContainerSpecOutput

func (GoogleCloudMlV1__ContainerSpecArgs) ToGoogleCloudMlV1__ContainerSpecOutputWithContext 

func (i GoogleCloudMlV1__ContainerSpecArgs) ToGoogleCloudMlV1__ContainerSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerSpecOutput

func (GoogleCloudMlV1__ContainerSpecArgs) ToGoogleCloudMlV1__ContainerSpecPtrOutput 

func (i GoogleCloudMlV1__ContainerSpecArgs) ToGoogleCloudMlV1__ContainerSpecPtrOutput() GoogleCloudMlV1__ContainerSpecPtrOutput

func (GoogleCloudMlV1__ContainerSpecArgs) ToGoogleCloudMlV1__ContainerSpecPtrOutputWithContext 

func (i GoogleCloudMlV1__ContainerSpecArgs) ToGoogleCloudMlV1__ContainerSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerSpecPtrOutput

type GoogleCloudMlV1__ContainerSpecInput 

type GoogleCloudMlV1__ContainerSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ContainerSpecOutput() GoogleCloudMlV1__ContainerSpecOutput
	ToGoogleCloudMlV1__ContainerSpecOutputWithContext(context.Context) GoogleCloudMlV1__ContainerSpecOutput
}

GoogleCloudMlV1__ContainerSpecInput is an input type that accepts GoogleCloudMlV1__ContainerSpecArgs and GoogleCloudMlV1__ContainerSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ContainerSpecInput` via: 

GoogleCloudMlV1__ContainerSpecArgs{...}

type GoogleCloudMlV1__ContainerSpecOutput 

type GoogleCloudMlV1__ContainerSpecOutput struct{ *pulumi.OutputState }

Specification of a custom container for serving predictions. This message is a subset of the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecOutput) Args 

func (o GoogleCloudMlV1__ContainerSpecOutput) Args() pulumi.StringArrayOutput

Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `commmand` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecOutput) Command 

func (o GoogleCloudMlV1__ContainerSpecOutput) Command() pulumi.StringArrayOutput

Immutable. Specifies the command that runs when the container starts. This overrides the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecOutput) ElementType 

func (GoogleCloudMlV1__ContainerSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerSpecOutput) Env 

func (o GoogleCloudMlV1__ContainerSpecOutput) Env() GoogleCloudMlV1__EnvVarArrayOutput

Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ``` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecOutput) Image 

func (o GoogleCloudMlV1__ContainerSpecOutput) Image() pulumi.StringPtrOutput

URI of the Docker image to be used as the custom container for serving predictions. This URI must identify [an image in Artifact Registry](/artifact-registry/docs/overview) and begin with the hostname `{REGION}-docker.pkg.dev`, where `{REGION}` is replaced by the region that matches AI Platform Prediction [regional endpoint](/ai-platform/prediction/docs/regional-endpoints) that you are using. For example, if you are using the `us-central1-ml.googleapis.com` endpoint, then this URI must begin with `us-central1-docker.pkg.dev`. To use a custom container, the [AI Platform Google-managed service account](/ai-platform/prediction/docs/custom-service-account#default) must have permission to pull (read) the Docker image at this URI. The AI Platform Google-managed service account has the following format: `service-{PROJECT_NUMBER}@cloud-ml.google.com.iam.gserviceaccount.com` {PROJECT_NUMBER} is replaced by your Google Cloud project number. By default, this service account has necessary permissions to pull an Artifact Registry image in the same Google Cloud project where you are using AI Platform Prediction. In this case, no configuration is necessary. If you want to use an image from a different Google Cloud project, learn how to [grant the Artifact Registry Reader (roles/artifactregistry.reader) role for a repository](/artifact-registry/docs/access-control#grant-repo) to your projet's AI Platform Google-managed service account. To learn about the requirements for the Docker image itself, read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements).

func (GoogleCloudMlV1__ContainerSpecOutput) Ports 

func (o GoogleCloudMlV1__ContainerSpecOutput) Ports() GoogleCloudMlV1__ContainerPortArrayOutput

Immutable. List of ports to expose from the container. AI Platform Prediction sends any prediction requests that it receives to the first port on this list. AI Platform Prediction also sends [liveness and health checks](/ai-platform/prediction/docs/custom-container-requirements#health) to this port. If you do not specify this field, it defaults to following value: ``` json [ { "containerPort": 8080 } ] ``` AI Platform Prediction does not use ports other than the first one listed. This field corresponds to the `ports` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecOutput) ToGoogleCloudMlV1__ContainerSpecOutput 

func (o GoogleCloudMlV1__ContainerSpecOutput) ToGoogleCloudMlV1__ContainerSpecOutput() GoogleCloudMlV1__ContainerSpecOutput

func (GoogleCloudMlV1__ContainerSpecOutput) ToGoogleCloudMlV1__ContainerSpecOutputWithContext 

func (o GoogleCloudMlV1__ContainerSpecOutput) ToGoogleCloudMlV1__ContainerSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerSpecOutput

func (GoogleCloudMlV1__ContainerSpecOutput) ToGoogleCloudMlV1__ContainerSpecPtrOutput 

func (o GoogleCloudMlV1__ContainerSpecOutput) ToGoogleCloudMlV1__ContainerSpecPtrOutput() GoogleCloudMlV1__ContainerSpecPtrOutput

func (GoogleCloudMlV1__ContainerSpecOutput) ToGoogleCloudMlV1__ContainerSpecPtrOutputWithContext 

func (o GoogleCloudMlV1__ContainerSpecOutput) ToGoogleCloudMlV1__ContainerSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerSpecPtrOutput

type GoogleCloudMlV1__ContainerSpecPtrInput 

type GoogleCloudMlV1__ContainerSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ContainerSpecPtrOutput() GoogleCloudMlV1__ContainerSpecPtrOutput
	ToGoogleCloudMlV1__ContainerSpecPtrOutputWithContext(context.Context) GoogleCloudMlV1__ContainerSpecPtrOutput
}

GoogleCloudMlV1__ContainerSpecPtrInput is an input type that accepts GoogleCloudMlV1__ContainerSpecArgs, GoogleCloudMlV1__ContainerSpecPtr and GoogleCloudMlV1__ContainerSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ContainerSpecPtrInput` via: 

        GoogleCloudMlV1__ContainerSpecArgs{...}

or:

        nil

func GoogleCloudMlV1__ContainerSpecPtr 

func GoogleCloudMlV1__ContainerSpecPtr(v *GoogleCloudMlV1__ContainerSpecArgs) GoogleCloudMlV1__ContainerSpecPtrInput

type GoogleCloudMlV1__ContainerSpecPtrOutput 

type GoogleCloudMlV1__ContainerSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ContainerSpecPtrOutput) Args 

func (o GoogleCloudMlV1__ContainerSpecPtrOutput) Args() pulumi.StringArrayOutput

Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `commmand` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecPtrOutput) Command 

func (o GoogleCloudMlV1__ContainerSpecPtrOutput) Command() pulumi.StringArrayOutput

Immutable. Specifies the command that runs when the container starts. This overrides the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecPtrOutput) Elem 

func (o GoogleCloudMlV1__ContainerSpecPtrOutput) Elem() GoogleCloudMlV1__ContainerSpecOutput

func (GoogleCloudMlV1__ContainerSpecPtrOutput) ElementType 

func (GoogleCloudMlV1__ContainerSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerSpecPtrOutput) Env 

func (o GoogleCloudMlV1__ContainerSpecPtrOutput) Env() GoogleCloudMlV1__EnvVarArrayOutput

Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ``` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecPtrOutput) Image 

func (o GoogleCloudMlV1__ContainerSpecPtrOutput) Image() pulumi.StringPtrOutput

URI of the Docker image to be used as the custom container for serving predictions. This URI must identify [an image in Artifact Registry](/artifact-registry/docs/overview) and begin with the hostname `{REGION}-docker.pkg.dev`, where `{REGION}` is replaced by the region that matches AI Platform Prediction [regional endpoint](/ai-platform/prediction/docs/regional-endpoints) that you are using. For example, if you are using the `us-central1-ml.googleapis.com` endpoint, then this URI must begin with `us-central1-docker.pkg.dev`. To use a custom container, the [AI Platform Google-managed service account](/ai-platform/prediction/docs/custom-service-account#default) must have permission to pull (read) the Docker image at this URI. The AI Platform Google-managed service account has the following format: `service-{PROJECT_NUMBER}@cloud-ml.google.com.iam.gserviceaccount.com` {PROJECT_NUMBER} is replaced by your Google Cloud project number. By default, this service account has necessary permissions to pull an Artifact Registry image in the same Google Cloud project where you are using AI Platform Prediction. In this case, no configuration is necessary. If you want to use an image from a different Google Cloud project, learn how to [grant the Artifact Registry Reader (roles/artifactregistry.reader) role for a repository](/artifact-registry/docs/access-control#grant-repo) to your projet's AI Platform Google-managed service account. To learn about the requirements for the Docker image itself, read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements).

func (GoogleCloudMlV1__ContainerSpecPtrOutput) Ports 

func (o GoogleCloudMlV1__ContainerSpecPtrOutput) Ports() GoogleCloudMlV1__ContainerPortArrayOutput

Immutable. List of ports to expose from the container. AI Platform Prediction sends any prediction requests that it receives to the first port on this list. AI Platform Prediction also sends [liveness and health checks](/ai-platform/prediction/docs/custom-container-requirements#health) to this port. If you do not specify this field, it defaults to following value: ``` json [ { "containerPort": 8080 } ] ``` AI Platform Prediction does not use ports other than the first one listed. This field corresponds to the `ports` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecPtrOutput) ToGoogleCloudMlV1__ContainerSpecPtrOutput 

func (o GoogleCloudMlV1__ContainerSpecPtrOutput) ToGoogleCloudMlV1__ContainerSpecPtrOutput() GoogleCloudMlV1__ContainerSpecPtrOutput

func (GoogleCloudMlV1__ContainerSpecPtrOutput) ToGoogleCloudMlV1__ContainerSpecPtrOutputWithContext 

func (o GoogleCloudMlV1__ContainerSpecPtrOutput) ToGoogleCloudMlV1__ContainerSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerSpecPtrOutput

type GoogleCloudMlV1__ContainerSpecResponse 

type GoogleCloudMlV1__ContainerSpecResponse struct {
	// Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `commmand` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Args []string `pulumi:"args"`
	// Immutable. Specifies the command that runs when the container starts. This overrides the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Command []string `pulumi:"command"`
	// Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: “` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ]  “` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Env []GoogleCloudMlV1__EnvVarResponse `pulumi:"env"`
	// URI of the Docker image to be used as the custom container for serving predictions. This URI must identify [an image in Artifact Registry](/artifact-registry/docs/overview) and begin with the hostname `{REGION}-docker.pkg.dev`, where `{REGION}` is replaced by the region that matches AI Platform Prediction [regional endpoint](/ai-platform/prediction/docs/regional-endpoints) that you are using. For example, if you are using the `us-central1-ml.googleapis.com` endpoint, then this URI must begin with `us-central1-docker.pkg.dev`. To use a custom container, the [AI Platform Google-managed service account](/ai-platform/prediction/docs/custom-service-account#default) must have permission to pull (read) the Docker image at this URI. The AI Platform Google-managed service account has the following format: `service-{PROJECT_NUMBER}@cloud-ml.google.com.iam.gserviceaccount.com` {PROJECT_NUMBER} is replaced by your Google Cloud project number. By default, this service account has necessary permissions to pull an Artifact Registry image in the same Google Cloud project where you are using AI Platform Prediction. In this case, no configuration is necessary. If you want to use an image from a different Google Cloud project, learn how to [grant the Artifact Registry Reader (roles/artifactregistry.reader) role for a repository](/artifact-registry/docs/access-control#grant-repo) to your projet's AI Platform Google-managed service account. To learn about the requirements for the Docker image itself, read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements).
	Image string `pulumi:"image"`
	// Immutable. List of ports to expose from the container. AI Platform Prediction sends any prediction requests that it receives to the first port on this list. AI Platform Prediction also sends [liveness and health checks](/ai-platform/prediction/docs/custom-container-requirements#health) to this port. If you do not specify this field, it defaults to following value: “` json [ { "containerPort": 8080 } ]  “` AI Platform Prediction does not use ports other than the first one listed. This field corresponds to the `ports` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).
	Ports []GoogleCloudMlV1__ContainerPortResponse `pulumi:"ports"`
}

Specification of a custom container for serving predictions. This message is a subset of the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

type GoogleCloudMlV1__ContainerSpecResponseOutput 

type GoogleCloudMlV1__ContainerSpecResponseOutput struct{ *pulumi.OutputState }

Specification of a custom container for serving predictions. This message is a subset of the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecResponseOutput) Args 

func (o GoogleCloudMlV1__ContainerSpecResponseOutput) Args() pulumi.StringArrayOutput

Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `commmand` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecResponseOutput) Command 

func (o GoogleCloudMlV1__ContainerSpecResponseOutput) Command() pulumi.StringArrayOutput

Immutable. Specifies the command that runs when the container starts. This overrides the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the [Docker documentation about how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand-how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define-command-argument-container/#notes). In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecResponseOutput) ElementType 

func (GoogleCloudMlV1__ContainerSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ContainerSpecResponseOutput) Env 

func (o GoogleCloudMlV1__ContainerSpecResponseOutput) Env() GoogleCloudMlV1__EnvVarResponseArrayOutput

Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ``` json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecResponseOutput) Image 

func (o GoogleCloudMlV1__ContainerSpecResponseOutput) Image() pulumi.StringOutput

URI of the Docker image to be used as the custom container for serving predictions. This URI must identify [an image in Artifact Registry](/artifact-registry/docs/overview) and begin with the hostname `{REGION}-docker.pkg.dev`, where `{REGION}` is replaced by the region that matches AI Platform Prediction [regional endpoint](/ai-platform/prediction/docs/regional-endpoints) that you are using. For example, if you are using the `us-central1-ml.googleapis.com` endpoint, then this URI must begin with `us-central1-docker.pkg.dev`. To use a custom container, the [AI Platform Google-managed service account](/ai-platform/prediction/docs/custom-service-account#default) must have permission to pull (read) the Docker image at this URI. The AI Platform Google-managed service account has the following format: `service-{PROJECT_NUMBER}@cloud-ml.google.com.iam.gserviceaccount.com` {PROJECT_NUMBER} is replaced by your Google Cloud project number. By default, this service account has necessary permissions to pull an Artifact Registry image in the same Google Cloud project where you are using AI Platform Prediction. In this case, no configuration is necessary. If you want to use an image from a different Google Cloud project, learn how to [grant the Artifact Registry Reader (roles/artifactregistry.reader) role for a repository](/artifact-registry/docs/access-control#grant-repo) to your projet's AI Platform Google-managed service account. To learn about the requirements for the Docker image itself, read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements).

func (GoogleCloudMlV1__ContainerSpecResponseOutput) Ports 

func (o GoogleCloudMlV1__ContainerSpecResponseOutput) Ports() GoogleCloudMlV1__ContainerPortResponseArrayOutput

Immutable. List of ports to expose from the container. AI Platform Prediction sends any prediction requests that it receives to the first port on this list. AI Platform Prediction also sends [liveness and health checks](/ai-platform/prediction/docs/custom-container-requirements#health) to this port. If you do not specify this field, it defaults to following value: ``` json [ { "containerPort": 8080 } ] ``` AI Platform Prediction does not use ports other than the first one listed. This field corresponds to the `ports` field of the [Kubernetes Containers v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#container-v1-core).

func (GoogleCloudMlV1__ContainerSpecResponseOutput) ToGoogleCloudMlV1__ContainerSpecResponseOutput 

func (o GoogleCloudMlV1__ContainerSpecResponseOutput) ToGoogleCloudMlV1__ContainerSpecResponseOutput() GoogleCloudMlV1__ContainerSpecResponseOutput

func (GoogleCloudMlV1__ContainerSpecResponseOutput) ToGoogleCloudMlV1__ContainerSpecResponseOutputWithContext 

func (o GoogleCloudMlV1__ContainerSpecResponseOutput) ToGoogleCloudMlV1__ContainerSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__ContainerSpecResponseOutput

type GoogleCloudMlV1__DiskConfig 

type GoogleCloudMlV1__DiskConfig struct {
	// Size in GB of the boot disk (default is 100GB).
	BootDiskSizeGb *int `pulumi:"bootDiskSizeGb"`
	// Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
	BootDiskType *string `pulumi:"bootDiskType"`
}

Represents the config of disk options.

type GoogleCloudMlV1__DiskConfigArgs 

type GoogleCloudMlV1__DiskConfigArgs struct {
	// Size in GB of the boot disk (default is 100GB).
	BootDiskSizeGb pulumi.IntPtrInput `pulumi:"bootDiskSizeGb"`
	// Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
	BootDiskType pulumi.StringPtrInput `pulumi:"bootDiskType"`
}

Represents the config of disk options.

func (GoogleCloudMlV1__DiskConfigArgs) ElementType 

func (GoogleCloudMlV1__DiskConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__DiskConfigArgs) ToGoogleCloudMlV1__DiskConfigOutput 

func (i GoogleCloudMlV1__DiskConfigArgs) ToGoogleCloudMlV1__DiskConfigOutput() GoogleCloudMlV1__DiskConfigOutput

func (GoogleCloudMlV1__DiskConfigArgs) ToGoogleCloudMlV1__DiskConfigOutputWithContext 

func (i GoogleCloudMlV1__DiskConfigArgs) ToGoogleCloudMlV1__DiskConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__DiskConfigOutput

func (GoogleCloudMlV1__DiskConfigArgs) ToGoogleCloudMlV1__DiskConfigPtrOutput 

func (i GoogleCloudMlV1__DiskConfigArgs) ToGoogleCloudMlV1__DiskConfigPtrOutput() GoogleCloudMlV1__DiskConfigPtrOutput

func (GoogleCloudMlV1__DiskConfigArgs) ToGoogleCloudMlV1__DiskConfigPtrOutputWithContext 

func (i GoogleCloudMlV1__DiskConfigArgs) ToGoogleCloudMlV1__DiskConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__DiskConfigPtrOutput

type GoogleCloudMlV1__DiskConfigInput 

type GoogleCloudMlV1__DiskConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__DiskConfigOutput() GoogleCloudMlV1__DiskConfigOutput
	ToGoogleCloudMlV1__DiskConfigOutputWithContext(context.Context) GoogleCloudMlV1__DiskConfigOutput
}

GoogleCloudMlV1__DiskConfigInput is an input type that accepts GoogleCloudMlV1__DiskConfigArgs and GoogleCloudMlV1__DiskConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1__DiskConfigInput` via: 

GoogleCloudMlV1__DiskConfigArgs{...}

type GoogleCloudMlV1__DiskConfigOutput 

type GoogleCloudMlV1__DiskConfigOutput struct{ *pulumi.OutputState }

Represents the config of disk options.

func (GoogleCloudMlV1__DiskConfigOutput) BootDiskSizeGb 

func (o GoogleCloudMlV1__DiskConfigOutput) BootDiskSizeGb() pulumi.IntPtrOutput

Size in GB of the boot disk (default is 100GB).

func (GoogleCloudMlV1__DiskConfigOutput) BootDiskType 

func (o GoogleCloudMlV1__DiskConfigOutput) BootDiskType() pulumi.StringPtrOutput

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

func (GoogleCloudMlV1__DiskConfigOutput) ElementType 

func (GoogleCloudMlV1__DiskConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__DiskConfigOutput) ToGoogleCloudMlV1__DiskConfigOutput 

func (o GoogleCloudMlV1__DiskConfigOutput) ToGoogleCloudMlV1__DiskConfigOutput() GoogleCloudMlV1__DiskConfigOutput

func (GoogleCloudMlV1__DiskConfigOutput) ToGoogleCloudMlV1__DiskConfigOutputWithContext 

func (o GoogleCloudMlV1__DiskConfigOutput) ToGoogleCloudMlV1__DiskConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__DiskConfigOutput

func (GoogleCloudMlV1__DiskConfigOutput) ToGoogleCloudMlV1__DiskConfigPtrOutput 

func (o GoogleCloudMlV1__DiskConfigOutput) ToGoogleCloudMlV1__DiskConfigPtrOutput() GoogleCloudMlV1__DiskConfigPtrOutput

func (GoogleCloudMlV1__DiskConfigOutput) ToGoogleCloudMlV1__DiskConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__DiskConfigOutput) ToGoogleCloudMlV1__DiskConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__DiskConfigPtrOutput

type GoogleCloudMlV1__DiskConfigPtrInput 

type GoogleCloudMlV1__DiskConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__DiskConfigPtrOutput() GoogleCloudMlV1__DiskConfigPtrOutput
	ToGoogleCloudMlV1__DiskConfigPtrOutputWithContext(context.Context) GoogleCloudMlV1__DiskConfigPtrOutput
}

GoogleCloudMlV1__DiskConfigPtrInput is an input type that accepts GoogleCloudMlV1__DiskConfigArgs, GoogleCloudMlV1__DiskConfigPtr and GoogleCloudMlV1__DiskConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__DiskConfigPtrInput` via: 

        GoogleCloudMlV1__DiskConfigArgs{...}

or:

        nil

func GoogleCloudMlV1__DiskConfigPtr 

func GoogleCloudMlV1__DiskConfigPtr(v *GoogleCloudMlV1__DiskConfigArgs) GoogleCloudMlV1__DiskConfigPtrInput

type GoogleCloudMlV1__DiskConfigPtrOutput 

type GoogleCloudMlV1__DiskConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__DiskConfigPtrOutput) BootDiskSizeGb 

func (o GoogleCloudMlV1__DiskConfigPtrOutput) BootDiskSizeGb() pulumi.IntPtrOutput

Size in GB of the boot disk (default is 100GB).

func (GoogleCloudMlV1__DiskConfigPtrOutput) BootDiskType 

func (o GoogleCloudMlV1__DiskConfigPtrOutput) BootDiskType() pulumi.StringPtrOutput

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

func (GoogleCloudMlV1__DiskConfigPtrOutput) Elem 

func (o GoogleCloudMlV1__DiskConfigPtrOutput) Elem() GoogleCloudMlV1__DiskConfigOutput

func (GoogleCloudMlV1__DiskConfigPtrOutput) ElementType 

func (GoogleCloudMlV1__DiskConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__DiskConfigPtrOutput) ToGoogleCloudMlV1__DiskConfigPtrOutput 

func (o GoogleCloudMlV1__DiskConfigPtrOutput) ToGoogleCloudMlV1__DiskConfigPtrOutput() GoogleCloudMlV1__DiskConfigPtrOutput

func (GoogleCloudMlV1__DiskConfigPtrOutput) ToGoogleCloudMlV1__DiskConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__DiskConfigPtrOutput) ToGoogleCloudMlV1__DiskConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__DiskConfigPtrOutput

type GoogleCloudMlV1__DiskConfigResponse 

type GoogleCloudMlV1__DiskConfigResponse struct {
	// Size in GB of the boot disk (default is 100GB).
	BootDiskSizeGb int `pulumi:"bootDiskSizeGb"`
	// Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).
	BootDiskType string `pulumi:"bootDiskType"`
}

Represents the config of disk options.

type GoogleCloudMlV1__DiskConfigResponseOutput 

type GoogleCloudMlV1__DiskConfigResponseOutput struct{ *pulumi.OutputState }

Represents the config of disk options.

func (GoogleCloudMlV1__DiskConfigResponseOutput) BootDiskSizeGb 

func (o GoogleCloudMlV1__DiskConfigResponseOutput) BootDiskSizeGb() pulumi.IntOutput

Size in GB of the boot disk (default is 100GB).

func (GoogleCloudMlV1__DiskConfigResponseOutput) BootDiskType 

func (o GoogleCloudMlV1__DiskConfigResponseOutput) BootDiskType() pulumi.StringOutput

Type of the boot disk (default is "pd-ssd"). Valid values: "pd-ssd" (Persistent Disk Solid State Drive) or "pd-standard" (Persistent Disk Hard Disk Drive).

func (GoogleCloudMlV1__DiskConfigResponseOutput) ElementType 

func (GoogleCloudMlV1__DiskConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__DiskConfigResponseOutput) ToGoogleCloudMlV1__DiskConfigResponseOutput 

func (o GoogleCloudMlV1__DiskConfigResponseOutput) ToGoogleCloudMlV1__DiskConfigResponseOutput() GoogleCloudMlV1__DiskConfigResponseOutput

func (GoogleCloudMlV1__DiskConfigResponseOutput) ToGoogleCloudMlV1__DiskConfigResponseOutputWithContext 

func (o GoogleCloudMlV1__DiskConfigResponseOutput) ToGoogleCloudMlV1__DiskConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__DiskConfigResponseOutput

type GoogleCloudMlV1__EncryptionConfig 

type GoogleCloudMlV1__EncryptionConfig struct {
	// The Cloud KMS resource identifier of the customer-managed encryption key used to protect a resource, such as a training job. It has the following format: `projects/{PROJECT_ID}/locations/{REGION}/keyRings/{KEY_RING_NAME}/cryptoKeys/{KEY_NAME}`
	KmsKeyName *string `pulumi:"kmsKeyName"`
}

Represents a custom encryption key configuration that can be applied to a resource.

type GoogleCloudMlV1__EncryptionConfigArgs 

type GoogleCloudMlV1__EncryptionConfigArgs struct {
	// The Cloud KMS resource identifier of the customer-managed encryption key used to protect a resource, such as a training job. It has the following format: `projects/{PROJECT_ID}/locations/{REGION}/keyRings/{KEY_RING_NAME}/cryptoKeys/{KEY_NAME}`
	KmsKeyName pulumi.StringPtrInput `pulumi:"kmsKeyName"`
}

Represents a custom encryption key configuration that can be applied to a resource.

func (GoogleCloudMlV1__EncryptionConfigArgs) ElementType 

func (GoogleCloudMlV1__EncryptionConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__EncryptionConfigArgs) ToGoogleCloudMlV1__EncryptionConfigOutput 

func (i GoogleCloudMlV1__EncryptionConfigArgs) ToGoogleCloudMlV1__EncryptionConfigOutput() GoogleCloudMlV1__EncryptionConfigOutput

func (GoogleCloudMlV1__EncryptionConfigArgs) ToGoogleCloudMlV1__EncryptionConfigOutputWithContext 

func (i GoogleCloudMlV1__EncryptionConfigArgs) ToGoogleCloudMlV1__EncryptionConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__EncryptionConfigOutput

func (GoogleCloudMlV1__EncryptionConfigArgs) ToGoogleCloudMlV1__EncryptionConfigPtrOutput 

func (i GoogleCloudMlV1__EncryptionConfigArgs) ToGoogleCloudMlV1__EncryptionConfigPtrOutput() GoogleCloudMlV1__EncryptionConfigPtrOutput

func (GoogleCloudMlV1__EncryptionConfigArgs) ToGoogleCloudMlV1__EncryptionConfigPtrOutputWithContext 

func (i GoogleCloudMlV1__EncryptionConfigArgs) ToGoogleCloudMlV1__EncryptionConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__EncryptionConfigPtrOutput

type GoogleCloudMlV1__EncryptionConfigInput 

type GoogleCloudMlV1__EncryptionConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__EncryptionConfigOutput() GoogleCloudMlV1__EncryptionConfigOutput
	ToGoogleCloudMlV1__EncryptionConfigOutputWithContext(context.Context) GoogleCloudMlV1__EncryptionConfigOutput
}

GoogleCloudMlV1__EncryptionConfigInput is an input type that accepts GoogleCloudMlV1__EncryptionConfigArgs and GoogleCloudMlV1__EncryptionConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1__EncryptionConfigInput` via: 

GoogleCloudMlV1__EncryptionConfigArgs{...}

type GoogleCloudMlV1__EncryptionConfigOutput 

type GoogleCloudMlV1__EncryptionConfigOutput struct{ *pulumi.OutputState }

Represents a custom encryption key configuration that can be applied to a resource.

func (GoogleCloudMlV1__EncryptionConfigOutput) ElementType 

func (GoogleCloudMlV1__EncryptionConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__EncryptionConfigOutput) KmsKeyName 

func (o GoogleCloudMlV1__EncryptionConfigOutput) KmsKeyName() pulumi.StringPtrOutput

The Cloud KMS resource identifier of the customer-managed encryption key used to protect a resource, such as a training job. It has the following format: `projects/{PROJECT_ID}/locations/{REGION}/keyRings/{KEY_RING_NAME}/cryptoKeys/{KEY_NAME}`

func (GoogleCloudMlV1__EncryptionConfigOutput) ToGoogleCloudMlV1__EncryptionConfigOutput 

func (o GoogleCloudMlV1__EncryptionConfigOutput) ToGoogleCloudMlV1__EncryptionConfigOutput() GoogleCloudMlV1__EncryptionConfigOutput

func (GoogleCloudMlV1__EncryptionConfigOutput) ToGoogleCloudMlV1__EncryptionConfigOutputWithContext 

func (o GoogleCloudMlV1__EncryptionConfigOutput) ToGoogleCloudMlV1__EncryptionConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__EncryptionConfigOutput

func (GoogleCloudMlV1__EncryptionConfigOutput) ToGoogleCloudMlV1__EncryptionConfigPtrOutput 

func (o GoogleCloudMlV1__EncryptionConfigOutput) ToGoogleCloudMlV1__EncryptionConfigPtrOutput() GoogleCloudMlV1__EncryptionConfigPtrOutput

func (GoogleCloudMlV1__EncryptionConfigOutput) ToGoogleCloudMlV1__EncryptionConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__EncryptionConfigOutput) ToGoogleCloudMlV1__EncryptionConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__EncryptionConfigPtrOutput

type GoogleCloudMlV1__EncryptionConfigPtrInput 

type GoogleCloudMlV1__EncryptionConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__EncryptionConfigPtrOutput() GoogleCloudMlV1__EncryptionConfigPtrOutput
	ToGoogleCloudMlV1__EncryptionConfigPtrOutputWithContext(context.Context) GoogleCloudMlV1__EncryptionConfigPtrOutput
}

GoogleCloudMlV1__EncryptionConfigPtrInput is an input type that accepts GoogleCloudMlV1__EncryptionConfigArgs, GoogleCloudMlV1__EncryptionConfigPtr and GoogleCloudMlV1__EncryptionConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__EncryptionConfigPtrInput` via: 

        GoogleCloudMlV1__EncryptionConfigArgs{...}

or:

        nil

func GoogleCloudMlV1__EncryptionConfigPtr 

func GoogleCloudMlV1__EncryptionConfigPtr(v *GoogleCloudMlV1__EncryptionConfigArgs) GoogleCloudMlV1__EncryptionConfigPtrInput

type GoogleCloudMlV1__EncryptionConfigPtrOutput 

type GoogleCloudMlV1__EncryptionConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__EncryptionConfigPtrOutput) Elem 

func (o GoogleCloudMlV1__EncryptionConfigPtrOutput) Elem() GoogleCloudMlV1__EncryptionConfigOutput

func (GoogleCloudMlV1__EncryptionConfigPtrOutput) ElementType 

func (GoogleCloudMlV1__EncryptionConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__EncryptionConfigPtrOutput) KmsKeyName 

func (o GoogleCloudMlV1__EncryptionConfigPtrOutput) KmsKeyName() pulumi.StringPtrOutput

The Cloud KMS resource identifier of the customer-managed encryption key used to protect a resource, such as a training job. It has the following format: `projects/{PROJECT_ID}/locations/{REGION}/keyRings/{KEY_RING_NAME}/cryptoKeys/{KEY_NAME}`

func (GoogleCloudMlV1__EncryptionConfigPtrOutput) ToGoogleCloudMlV1__EncryptionConfigPtrOutput 

func (o GoogleCloudMlV1__EncryptionConfigPtrOutput) ToGoogleCloudMlV1__EncryptionConfigPtrOutput() GoogleCloudMlV1__EncryptionConfigPtrOutput

func (GoogleCloudMlV1__EncryptionConfigPtrOutput) ToGoogleCloudMlV1__EncryptionConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__EncryptionConfigPtrOutput) ToGoogleCloudMlV1__EncryptionConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__EncryptionConfigPtrOutput

type GoogleCloudMlV1__EncryptionConfigResponse 

type GoogleCloudMlV1__EncryptionConfigResponse struct {
	// The Cloud KMS resource identifier of the customer-managed encryption key used to protect a resource, such as a training job. It has the following format: `projects/{PROJECT_ID}/locations/{REGION}/keyRings/{KEY_RING_NAME}/cryptoKeys/{KEY_NAME}`
	KmsKeyName string `pulumi:"kmsKeyName"`
}

Represents a custom encryption key configuration that can be applied to a resource.

type GoogleCloudMlV1__EncryptionConfigResponseOutput 

type GoogleCloudMlV1__EncryptionConfigResponseOutput struct{ *pulumi.OutputState }

Represents a custom encryption key configuration that can be applied to a resource.

func (GoogleCloudMlV1__EncryptionConfigResponseOutput) ElementType 

func (GoogleCloudMlV1__EncryptionConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__EncryptionConfigResponseOutput) KmsKeyName 

func (o GoogleCloudMlV1__EncryptionConfigResponseOutput) KmsKeyName() pulumi.StringOutput

The Cloud KMS resource identifier of the customer-managed encryption key used to protect a resource, such as a training job. It has the following format: `projects/{PROJECT_ID}/locations/{REGION}/keyRings/{KEY_RING_NAME}/cryptoKeys/{KEY_NAME}`

func (GoogleCloudMlV1__EncryptionConfigResponseOutput) ToGoogleCloudMlV1__EncryptionConfigResponseOutput 

func (o GoogleCloudMlV1__EncryptionConfigResponseOutput) ToGoogleCloudMlV1__EncryptionConfigResponseOutput() GoogleCloudMlV1__EncryptionConfigResponseOutput

func (GoogleCloudMlV1__EncryptionConfigResponseOutput) ToGoogleCloudMlV1__EncryptionConfigResponseOutputWithContext 

func (o GoogleCloudMlV1__EncryptionConfigResponseOutput) ToGoogleCloudMlV1__EncryptionConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__EncryptionConfigResponseOutput

type GoogleCloudMlV1__EnvVar 

type GoogleCloudMlV1__EnvVar struct {
	// Name of the environment variable. Must be a [valid C identifier](https://github.com/kubernetes/kubernetes/blob/v1.18.8/staging/src/k8s.io/apimachinery/pkg/util/validation/validation.go#L258) and must not begin with the prefix `AIP_`.
	Name *string `pulumi:"name"`
	// Value of the environment variable. Defaults to an empty string. In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set earlier in the same env field as where this message occurs. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $(VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME)
	Value *string `pulumi:"value"`
}

Represents an environment variable to be made available in a container. This message is a subset of the [Kubernetes EnvVar v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#envvar-v1-core).

type GoogleCloudMlV1__EnvVarArgs 

type GoogleCloudMlV1__EnvVarArgs struct {
	// Name of the environment variable. Must be a [valid C identifier](https://github.com/kubernetes/kubernetes/blob/v1.18.8/staging/src/k8s.io/apimachinery/pkg/util/validation/validation.go#L258) and must not begin with the prefix `AIP_`.
	Name pulumi.StringPtrInput `pulumi:"name"`
	// Value of the environment variable. Defaults to an empty string. In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set earlier in the same env field as where this message occurs. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $(VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME)
	Value pulumi.StringPtrInput `pulumi:"value"`
}

Represents an environment variable to be made available in a container. This message is a subset of the [Kubernetes EnvVar v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#envvar-v1-core).

func (GoogleCloudMlV1__EnvVarArgs) ElementType 

func (GoogleCloudMlV1__EnvVarArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__EnvVarArgs) ToGoogleCloudMlV1__EnvVarOutput 

func (i GoogleCloudMlV1__EnvVarArgs) ToGoogleCloudMlV1__EnvVarOutput() GoogleCloudMlV1__EnvVarOutput

func (GoogleCloudMlV1__EnvVarArgs) ToGoogleCloudMlV1__EnvVarOutputWithContext 

func (i GoogleCloudMlV1__EnvVarArgs) ToGoogleCloudMlV1__EnvVarOutputWithContext(ctx context.Context) GoogleCloudMlV1__EnvVarOutput

type GoogleCloudMlV1__EnvVarArray 

type GoogleCloudMlV1__EnvVarArray []GoogleCloudMlV1__EnvVarInput

func (GoogleCloudMlV1__EnvVarArray) ElementType 

func (GoogleCloudMlV1__EnvVarArray) ElementType() reflect.Type

func (GoogleCloudMlV1__EnvVarArray) ToGoogleCloudMlV1__EnvVarArrayOutput 

func (i GoogleCloudMlV1__EnvVarArray) ToGoogleCloudMlV1__EnvVarArrayOutput() GoogleCloudMlV1__EnvVarArrayOutput

func (GoogleCloudMlV1__EnvVarArray) ToGoogleCloudMlV1__EnvVarArrayOutputWithContext 

func (i GoogleCloudMlV1__EnvVarArray) ToGoogleCloudMlV1__EnvVarArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__EnvVarArrayOutput

type GoogleCloudMlV1__EnvVarArrayInput 

type GoogleCloudMlV1__EnvVarArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__EnvVarArrayOutput() GoogleCloudMlV1__EnvVarArrayOutput
	ToGoogleCloudMlV1__EnvVarArrayOutputWithContext(context.Context) GoogleCloudMlV1__EnvVarArrayOutput
}

GoogleCloudMlV1__EnvVarArrayInput is an input type that accepts GoogleCloudMlV1__EnvVarArray and GoogleCloudMlV1__EnvVarArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1__EnvVarArrayInput` via: 

GoogleCloudMlV1__EnvVarArray{ GoogleCloudMlV1__EnvVarArgs{...} }

type GoogleCloudMlV1__EnvVarArrayOutput 

type GoogleCloudMlV1__EnvVarArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__EnvVarArrayOutput) ElementType 

func (GoogleCloudMlV1__EnvVarArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__EnvVarArrayOutput) Index 

func (o GoogleCloudMlV1__EnvVarArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__EnvVarOutput

func (GoogleCloudMlV1__EnvVarArrayOutput) ToGoogleCloudMlV1__EnvVarArrayOutput 

func (o GoogleCloudMlV1__EnvVarArrayOutput) ToGoogleCloudMlV1__EnvVarArrayOutput() GoogleCloudMlV1__EnvVarArrayOutput

func (GoogleCloudMlV1__EnvVarArrayOutput) ToGoogleCloudMlV1__EnvVarArrayOutputWithContext 

func (o GoogleCloudMlV1__EnvVarArrayOutput) ToGoogleCloudMlV1__EnvVarArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__EnvVarArrayOutput

type GoogleCloudMlV1__EnvVarInput 

type GoogleCloudMlV1__EnvVarInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__EnvVarOutput() GoogleCloudMlV1__EnvVarOutput
	ToGoogleCloudMlV1__EnvVarOutputWithContext(context.Context) GoogleCloudMlV1__EnvVarOutput
}

GoogleCloudMlV1__EnvVarInput is an input type that accepts GoogleCloudMlV1__EnvVarArgs and GoogleCloudMlV1__EnvVarOutput values. You can construct a concrete instance of `GoogleCloudMlV1__EnvVarInput` via: 

GoogleCloudMlV1__EnvVarArgs{...}

type GoogleCloudMlV1__EnvVarOutput 

type GoogleCloudMlV1__EnvVarOutput struct{ *pulumi.OutputState }

Represents an environment variable to be made available in a container. This message is a subset of the [Kubernetes EnvVar v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#envvar-v1-core).

func (GoogleCloudMlV1__EnvVarOutput) ElementType 

func (GoogleCloudMlV1__EnvVarOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__EnvVarOutput) Name 

func (o GoogleCloudMlV1__EnvVarOutput) Name() pulumi.StringPtrOutput

Name of the environment variable. Must be a [valid C identifier](https://github.com/kubernetes/kubernetes/blob/v1.18.8/staging/src/k8s.io/apimachinery/pkg/util/validation/validation.go#L258) and must not begin with the prefix `AIP_`.

func (GoogleCloudMlV1__EnvVarOutput) ToGoogleCloudMlV1__EnvVarOutput 

func (o GoogleCloudMlV1__EnvVarOutput) ToGoogleCloudMlV1__EnvVarOutput() GoogleCloudMlV1__EnvVarOutput

func (GoogleCloudMlV1__EnvVarOutput) ToGoogleCloudMlV1__EnvVarOutputWithContext 

func (o GoogleCloudMlV1__EnvVarOutput) ToGoogleCloudMlV1__EnvVarOutputWithContext(ctx context.Context) GoogleCloudMlV1__EnvVarOutput

func (GoogleCloudMlV1__EnvVarOutput) Value 

func (o GoogleCloudMlV1__EnvVarOutput) Value() pulumi.StringPtrOutput

Value of the environment variable. Defaults to an empty string. In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set earlier in the same env field as where this message occurs. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $(VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME)

type GoogleCloudMlV1__EnvVarResponse 

type GoogleCloudMlV1__EnvVarResponse struct {
	// Name of the environment variable. Must be a [valid C identifier](https://github.com/kubernetes/kubernetes/blob/v1.18.8/staging/src/k8s.io/apimachinery/pkg/util/validation/validation.go#L258) and must not begin with the prefix `AIP_`.
	Name string `pulumi:"name"`
	// Value of the environment variable. Defaults to an empty string. In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set earlier in the same env field as where this message occurs. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $(VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME)
	Value string `pulumi:"value"`
}

Represents an environment variable to be made available in a container. This message is a subset of the [Kubernetes EnvVar v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#envvar-v1-core).

type GoogleCloudMlV1__EnvVarResponseArrayOutput 

type GoogleCloudMlV1__EnvVarResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__EnvVarResponseArrayOutput) ElementType 

func (GoogleCloudMlV1__EnvVarResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__EnvVarResponseArrayOutput) Index 

func (o GoogleCloudMlV1__EnvVarResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__EnvVarResponseOutput

func (GoogleCloudMlV1__EnvVarResponseArrayOutput) ToGoogleCloudMlV1__EnvVarResponseArrayOutput 

func (o GoogleCloudMlV1__EnvVarResponseArrayOutput) ToGoogleCloudMlV1__EnvVarResponseArrayOutput() GoogleCloudMlV1__EnvVarResponseArrayOutput

func (GoogleCloudMlV1__EnvVarResponseArrayOutput) ToGoogleCloudMlV1__EnvVarResponseArrayOutputWithContext 

func (o GoogleCloudMlV1__EnvVarResponseArrayOutput) ToGoogleCloudMlV1__EnvVarResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__EnvVarResponseArrayOutput

type GoogleCloudMlV1__EnvVarResponseOutput 

type GoogleCloudMlV1__EnvVarResponseOutput struct{ *pulumi.OutputState }

Represents an environment variable to be made available in a container. This message is a subset of the [Kubernetes EnvVar v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.18/#envvar-v1-core).

func (GoogleCloudMlV1__EnvVarResponseOutput) ElementType 

func (GoogleCloudMlV1__EnvVarResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__EnvVarResponseOutput) Name 

func (o GoogleCloudMlV1__EnvVarResponseOutput) Name() pulumi.StringOutput

Name of the environment variable. Must be a [valid C identifier](https://github.com/kubernetes/kubernetes/blob/v1.18.8/staging/src/k8s.io/apimachinery/pkg/util/validation/validation.go#L258) and must not begin with the prefix `AIP_`.

func (GoogleCloudMlV1__EnvVarResponseOutput) ToGoogleCloudMlV1__EnvVarResponseOutput 

func (o GoogleCloudMlV1__EnvVarResponseOutput) ToGoogleCloudMlV1__EnvVarResponseOutput() GoogleCloudMlV1__EnvVarResponseOutput

func (GoogleCloudMlV1__EnvVarResponseOutput) ToGoogleCloudMlV1__EnvVarResponseOutputWithContext 

func (o GoogleCloudMlV1__EnvVarResponseOutput) ToGoogleCloudMlV1__EnvVarResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__EnvVarResponseOutput

func (GoogleCloudMlV1__EnvVarResponseOutput) Value 

func (o GoogleCloudMlV1__EnvVarResponseOutput) Value() pulumi.StringOutput

Value of the environment variable. Defaults to an empty string. In this field, you can reference [environment variables set by AI Platform Prediction](/ai-platform/prediction/docs/custom-container-requirements#aip-variables) and environment variables set earlier in the same env field as where this message occurs. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $(VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME)

type GoogleCloudMlV1__ExplanationConfig 

type GoogleCloudMlV1__ExplanationConfig struct {
	// Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
	IntegratedGradientsAttribution *GoogleCloudMlV1__IntegratedGradientsAttribution `pulumi:"integratedGradientsAttribution"`
	// An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.
	SampledShapleyAttribution *GoogleCloudMlV1__SampledShapleyAttribution `pulumi:"sampledShapleyAttribution"`
	// Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.
	XraiAttribution *GoogleCloudMlV1__XraiAttribution `pulumi:"xraiAttribution"`
}

Message holding configuration options for explaining model predictions. There are three feature attribution methods supported for TensorFlow models: integrated gradients, sampled Shapley, and XRAI. [Learn more about feature attributions.](/ai-platform/prediction/docs/ai-explanations/overview)

type GoogleCloudMlV1__ExplanationConfigArgs 

type GoogleCloudMlV1__ExplanationConfigArgs struct {
	// Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
	IntegratedGradientsAttribution GoogleCloudMlV1__IntegratedGradientsAttributionPtrInput `pulumi:"integratedGradientsAttribution"`
	// An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.
	SampledShapleyAttribution GoogleCloudMlV1__SampledShapleyAttributionPtrInput `pulumi:"sampledShapleyAttribution"`
	// Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.
	XraiAttribution GoogleCloudMlV1__XraiAttributionPtrInput `pulumi:"xraiAttribution"`
}

Message holding configuration options for explaining model predictions. There are three feature attribution methods supported for TensorFlow models: integrated gradients, sampled Shapley, and XRAI. [Learn more about feature attributions.](/ai-platform/prediction/docs/ai-explanations/overview)

func (GoogleCloudMlV1__ExplanationConfigArgs) ElementType 

func (GoogleCloudMlV1__ExplanationConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__ExplanationConfigArgs) ToGoogleCloudMlV1__ExplanationConfigOutput 

func (i GoogleCloudMlV1__ExplanationConfigArgs) ToGoogleCloudMlV1__ExplanationConfigOutput() GoogleCloudMlV1__ExplanationConfigOutput

func (GoogleCloudMlV1__ExplanationConfigArgs) ToGoogleCloudMlV1__ExplanationConfigOutputWithContext 

func (i GoogleCloudMlV1__ExplanationConfigArgs) ToGoogleCloudMlV1__ExplanationConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__ExplanationConfigOutput

func (GoogleCloudMlV1__ExplanationConfigArgs) ToGoogleCloudMlV1__ExplanationConfigPtrOutput 

func (i GoogleCloudMlV1__ExplanationConfigArgs) ToGoogleCloudMlV1__ExplanationConfigPtrOutput() GoogleCloudMlV1__ExplanationConfigPtrOutput

func (GoogleCloudMlV1__ExplanationConfigArgs) ToGoogleCloudMlV1__ExplanationConfigPtrOutputWithContext 

func (i GoogleCloudMlV1__ExplanationConfigArgs) ToGoogleCloudMlV1__ExplanationConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ExplanationConfigPtrOutput

type GoogleCloudMlV1__ExplanationConfigInput 

type GoogleCloudMlV1__ExplanationConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ExplanationConfigOutput() GoogleCloudMlV1__ExplanationConfigOutput
	ToGoogleCloudMlV1__ExplanationConfigOutputWithContext(context.Context) GoogleCloudMlV1__ExplanationConfigOutput
}

GoogleCloudMlV1__ExplanationConfigInput is an input type that accepts GoogleCloudMlV1__ExplanationConfigArgs and GoogleCloudMlV1__ExplanationConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ExplanationConfigInput` via: 

GoogleCloudMlV1__ExplanationConfigArgs{...}

type GoogleCloudMlV1__ExplanationConfigOutput 

type GoogleCloudMlV1__ExplanationConfigOutput struct{ *pulumi.OutputState }

Message holding configuration options for explaining model predictions. There are three feature attribution methods supported for TensorFlow models: integrated gradients, sampled Shapley, and XRAI. [Learn more about feature attributions.](/ai-platform/prediction/docs/ai-explanations/overview)

func (GoogleCloudMlV1__ExplanationConfigOutput) ElementType 

func (GoogleCloudMlV1__ExplanationConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ExplanationConfigOutput) IntegratedGradientsAttribution 

func (o GoogleCloudMlV1__ExplanationConfigOutput) IntegratedGradientsAttribution() GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput

Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudMlV1__ExplanationConfigOutput) SampledShapleyAttribution 

func (o GoogleCloudMlV1__ExplanationConfigOutput) SampledShapleyAttribution() GoogleCloudMlV1__SampledShapleyAttributionPtrOutput

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

func (GoogleCloudMlV1__ExplanationConfigOutput) ToGoogleCloudMlV1__ExplanationConfigOutput 

func (o GoogleCloudMlV1__ExplanationConfigOutput) ToGoogleCloudMlV1__ExplanationConfigOutput() GoogleCloudMlV1__ExplanationConfigOutput

func (GoogleCloudMlV1__ExplanationConfigOutput) ToGoogleCloudMlV1__ExplanationConfigOutputWithContext 

func (o GoogleCloudMlV1__ExplanationConfigOutput) ToGoogleCloudMlV1__ExplanationConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__ExplanationConfigOutput

func (GoogleCloudMlV1__ExplanationConfigOutput) ToGoogleCloudMlV1__ExplanationConfigPtrOutput 

func (o GoogleCloudMlV1__ExplanationConfigOutput) ToGoogleCloudMlV1__ExplanationConfigPtrOutput() GoogleCloudMlV1__ExplanationConfigPtrOutput

func (GoogleCloudMlV1__ExplanationConfigOutput) ToGoogleCloudMlV1__ExplanationConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__ExplanationConfigOutput) ToGoogleCloudMlV1__ExplanationConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ExplanationConfigPtrOutput

func (GoogleCloudMlV1__ExplanationConfigOutput) XraiAttribution 

func (o GoogleCloudMlV1__ExplanationConfigOutput) XraiAttribution() GoogleCloudMlV1__XraiAttributionPtrOutput

Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.

type GoogleCloudMlV1__ExplanationConfigPtrInput 

type GoogleCloudMlV1__ExplanationConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ExplanationConfigPtrOutput() GoogleCloudMlV1__ExplanationConfigPtrOutput
	ToGoogleCloudMlV1__ExplanationConfigPtrOutputWithContext(context.Context) GoogleCloudMlV1__ExplanationConfigPtrOutput
}

GoogleCloudMlV1__ExplanationConfigPtrInput is an input type that accepts GoogleCloudMlV1__ExplanationConfigArgs, GoogleCloudMlV1__ExplanationConfigPtr and GoogleCloudMlV1__ExplanationConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ExplanationConfigPtrInput` via: 

        GoogleCloudMlV1__ExplanationConfigArgs{...}

or:

        nil

func GoogleCloudMlV1__ExplanationConfigPtr 

func GoogleCloudMlV1__ExplanationConfigPtr(v *GoogleCloudMlV1__ExplanationConfigArgs) GoogleCloudMlV1__ExplanationConfigPtrInput

type GoogleCloudMlV1__ExplanationConfigPtrOutput 

type GoogleCloudMlV1__ExplanationConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ExplanationConfigPtrOutput) Elem 

func (o GoogleCloudMlV1__ExplanationConfigPtrOutput) Elem() GoogleCloudMlV1__ExplanationConfigOutput

func (GoogleCloudMlV1__ExplanationConfigPtrOutput) ElementType 

func (GoogleCloudMlV1__ExplanationConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ExplanationConfigPtrOutput) IntegratedGradientsAttribution 

func (o GoogleCloudMlV1__ExplanationConfigPtrOutput) IntegratedGradientsAttribution() GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput

Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudMlV1__ExplanationConfigPtrOutput) SampledShapleyAttribution 

func (o GoogleCloudMlV1__ExplanationConfigPtrOutput) SampledShapleyAttribution() GoogleCloudMlV1__SampledShapleyAttributionPtrOutput

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

func (GoogleCloudMlV1__ExplanationConfigPtrOutput) ToGoogleCloudMlV1__ExplanationConfigPtrOutput 

func (o GoogleCloudMlV1__ExplanationConfigPtrOutput) ToGoogleCloudMlV1__ExplanationConfigPtrOutput() GoogleCloudMlV1__ExplanationConfigPtrOutput

func (GoogleCloudMlV1__ExplanationConfigPtrOutput) ToGoogleCloudMlV1__ExplanationConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__ExplanationConfigPtrOutput) ToGoogleCloudMlV1__ExplanationConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ExplanationConfigPtrOutput

func (GoogleCloudMlV1__ExplanationConfigPtrOutput) XraiAttribution 

func (o GoogleCloudMlV1__ExplanationConfigPtrOutput) XraiAttribution() GoogleCloudMlV1__XraiAttributionPtrOutput

Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.

type GoogleCloudMlV1__ExplanationConfigResponse 

type GoogleCloudMlV1__ExplanationConfigResponse struct {
	// Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
	IntegratedGradientsAttribution GoogleCloudMlV1__IntegratedGradientsAttributionResponse `pulumi:"integratedGradientsAttribution"`
	// An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.
	SampledShapleyAttribution GoogleCloudMlV1__SampledShapleyAttributionResponse `pulumi:"sampledShapleyAttribution"`
	// Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.
	XraiAttribution GoogleCloudMlV1__XraiAttributionResponse `pulumi:"xraiAttribution"`
}

Message holding configuration options for explaining model predictions. There are three feature attribution methods supported for TensorFlow models: integrated gradients, sampled Shapley, and XRAI. [Learn more about feature attributions.](/ai-platform/prediction/docs/ai-explanations/overview)

type GoogleCloudMlV1__ExplanationConfigResponseOutput 

type GoogleCloudMlV1__ExplanationConfigResponseOutput struct{ *pulumi.OutputState }

Message holding configuration options for explaining model predictions. There are three feature attribution methods supported for TensorFlow models: integrated gradients, sampled Shapley, and XRAI. [Learn more about feature attributions.](/ai-platform/prediction/docs/ai-explanations/overview)

func (GoogleCloudMlV1__ExplanationConfigResponseOutput) ElementType 

func (GoogleCloudMlV1__ExplanationConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ExplanationConfigResponseOutput) IntegratedGradientsAttribution 

func (o GoogleCloudMlV1__ExplanationConfigResponseOutput) IntegratedGradientsAttribution() GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput

Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudMlV1__ExplanationConfigResponseOutput) SampledShapleyAttribution 

func (o GoogleCloudMlV1__ExplanationConfigResponseOutput) SampledShapleyAttribution() GoogleCloudMlV1__SampledShapleyAttributionResponseOutput

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

func (GoogleCloudMlV1__ExplanationConfigResponseOutput) ToGoogleCloudMlV1__ExplanationConfigResponseOutput 

func (o GoogleCloudMlV1__ExplanationConfigResponseOutput) ToGoogleCloudMlV1__ExplanationConfigResponseOutput() GoogleCloudMlV1__ExplanationConfigResponseOutput

func (GoogleCloudMlV1__ExplanationConfigResponseOutput) ToGoogleCloudMlV1__ExplanationConfigResponseOutputWithContext 

func (o GoogleCloudMlV1__ExplanationConfigResponseOutput) ToGoogleCloudMlV1__ExplanationConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__ExplanationConfigResponseOutput

func (GoogleCloudMlV1__ExplanationConfigResponseOutput) XraiAttribution 

func (o GoogleCloudMlV1__ExplanationConfigResponseOutput) XraiAttribution() GoogleCloudMlV1__XraiAttributionResponseOutput

Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.

type GoogleCloudMlV1__HyperparameterOutput 

type GoogleCloudMlV1__HyperparameterOutput struct {
	// All recorded object metrics for this trial. This field is not currently populated.
	AllMetrics []GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric `pulumi:"allMetrics"`
	// Details related to built-in algorithms jobs. Only set for trials of built-in algorithms jobs that have succeeded.
	BuiltInAlgorithmOutput *GoogleCloudMlV1__BuiltInAlgorithmOutput `pulumi:"builtInAlgorithmOutput"`
	// The final objective metric seen for this trial.
	FinalMetric *GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetric `pulumi:"finalMetric"`
	// The hyperparameters given to this trial.
	Hyperparameters map[string]string `pulumi:"hyperparameters"`
	// True if the trial is stopped early.
	IsTrialStoppedEarly *bool `pulumi:"isTrialStoppedEarly"`
	// The trial id for these results.
	TrialId *string `pulumi:"trialId"`
	// URIs for accessing [interactive shells](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a hyperparameter tuning job and the job's training_input.enable_web_access is `true`. The keys are names of each node in the training job; for example, `master-replica-0` for the master node, `worker-replica-0` for the first worker, and `ps-replica-0` for the first parameter server. The values are the URIs for each node's interactive shell.
	WebAccessUris map[string]string `pulumi:"webAccessUris"`
}

Represents the result of a single hyperparameter tuning trial from a training job. The TrainingOutput object that is returned on successful completion of a training job with hyperparameter tuning includes a list of HyperparameterOutput objects, one for each successful trial.

type GoogleCloudMlV1__HyperparameterOutputArgs 

type GoogleCloudMlV1__HyperparameterOutputArgs struct {
	// All recorded object metrics for this trial. This field is not currently populated.
	AllMetrics GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayInput `pulumi:"allMetrics"`
	// Details related to built-in algorithms jobs. Only set for trials of built-in algorithms jobs that have succeeded.
	BuiltInAlgorithmOutput GoogleCloudMlV1__BuiltInAlgorithmOutputPtrInput `pulumi:"builtInAlgorithmOutput"`
	// The final objective metric seen for this trial.
	FinalMetric GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrInput `pulumi:"finalMetric"`
	// The hyperparameters given to this trial.
	Hyperparameters pulumi.StringMapInput `pulumi:"hyperparameters"`
	// True if the trial is stopped early.
	IsTrialStoppedEarly pulumi.BoolPtrInput `pulumi:"isTrialStoppedEarly"`
	// The trial id for these results.
	TrialId pulumi.StringPtrInput `pulumi:"trialId"`
	// URIs for accessing [interactive shells](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a hyperparameter tuning job and the job's training_input.enable_web_access is `true`. The keys are names of each node in the training job; for example, `master-replica-0` for the master node, `worker-replica-0` for the first worker, and `ps-replica-0` for the first parameter server. The values are the URIs for each node's interactive shell.
	WebAccessUris pulumi.StringMapInput `pulumi:"webAccessUris"`
}

Represents the result of a single hyperparameter tuning trial from a training job. The TrainingOutput object that is returned on successful completion of a training job with hyperparameter tuning includes a list of HyperparameterOutput objects, one for each successful trial.

func (GoogleCloudMlV1__HyperparameterOutputArgs) ElementType 

func (GoogleCloudMlV1__HyperparameterOutputArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterOutputArgs) ToGoogleCloudMlV1__HyperparameterOutputOutput 

func (i GoogleCloudMlV1__HyperparameterOutputArgs) ToGoogleCloudMlV1__HyperparameterOutputOutput() GoogleCloudMlV1__HyperparameterOutputOutput

func (GoogleCloudMlV1__HyperparameterOutputArgs) ToGoogleCloudMlV1__HyperparameterOutputOutputWithContext 

func (i GoogleCloudMlV1__HyperparameterOutputArgs) ToGoogleCloudMlV1__HyperparameterOutputOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterOutputOutput

type GoogleCloudMlV1__HyperparameterOutputArray 

type GoogleCloudMlV1__HyperparameterOutputArray []GoogleCloudMlV1__HyperparameterOutputInput

func (GoogleCloudMlV1__HyperparameterOutputArray) ElementType 

func (GoogleCloudMlV1__HyperparameterOutputArray) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterOutputArray) ToGoogleCloudMlV1__HyperparameterOutputArrayOutput 

func (i GoogleCloudMlV1__HyperparameterOutputArray) ToGoogleCloudMlV1__HyperparameterOutputArrayOutput() GoogleCloudMlV1__HyperparameterOutputArrayOutput

func (GoogleCloudMlV1__HyperparameterOutputArray) ToGoogleCloudMlV1__HyperparameterOutputArrayOutputWithContext 

func (i GoogleCloudMlV1__HyperparameterOutputArray) ToGoogleCloudMlV1__HyperparameterOutputArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterOutputArrayOutput

type GoogleCloudMlV1__HyperparameterOutputArrayInput 

type GoogleCloudMlV1__HyperparameterOutputArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__HyperparameterOutputArrayOutput() GoogleCloudMlV1__HyperparameterOutputArrayOutput
	ToGoogleCloudMlV1__HyperparameterOutputArrayOutputWithContext(context.Context) GoogleCloudMlV1__HyperparameterOutputArrayOutput
}

GoogleCloudMlV1__HyperparameterOutputArrayInput is an input type that accepts GoogleCloudMlV1__HyperparameterOutputArray and GoogleCloudMlV1__HyperparameterOutputArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1__HyperparameterOutputArrayInput` via: 

GoogleCloudMlV1__HyperparameterOutputArray{ GoogleCloudMlV1__HyperparameterOutputArgs{...} }

type GoogleCloudMlV1__HyperparameterOutputArrayOutput 

type GoogleCloudMlV1__HyperparameterOutputArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__HyperparameterOutputArrayOutput) ElementType 

func (GoogleCloudMlV1__HyperparameterOutputArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterOutputArrayOutput) Index 

func (o GoogleCloudMlV1__HyperparameterOutputArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__HyperparameterOutputOutput

func (GoogleCloudMlV1__HyperparameterOutputArrayOutput) ToGoogleCloudMlV1__HyperparameterOutputArrayOutput 

func (o GoogleCloudMlV1__HyperparameterOutputArrayOutput) ToGoogleCloudMlV1__HyperparameterOutputArrayOutput() GoogleCloudMlV1__HyperparameterOutputArrayOutput

func (GoogleCloudMlV1__HyperparameterOutputArrayOutput) ToGoogleCloudMlV1__HyperparameterOutputArrayOutputWithContext 

func (o GoogleCloudMlV1__HyperparameterOutputArrayOutput) ToGoogleCloudMlV1__HyperparameterOutputArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterOutputArrayOutput

type GoogleCloudMlV1__HyperparameterOutputInput 

type GoogleCloudMlV1__HyperparameterOutputInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__HyperparameterOutputOutput() GoogleCloudMlV1__HyperparameterOutputOutput
	ToGoogleCloudMlV1__HyperparameterOutputOutputWithContext(context.Context) GoogleCloudMlV1__HyperparameterOutputOutput
}

GoogleCloudMlV1__HyperparameterOutputInput is an input type that accepts GoogleCloudMlV1__HyperparameterOutputArgs and GoogleCloudMlV1__HyperparameterOutputOutput values. You can construct a concrete instance of `GoogleCloudMlV1__HyperparameterOutputInput` via: 

GoogleCloudMlV1__HyperparameterOutputArgs{...}

type GoogleCloudMlV1__HyperparameterOutputOutput 

type GoogleCloudMlV1__HyperparameterOutputOutput struct{ *pulumi.OutputState }

Represents the result of a single hyperparameter tuning trial from a training job. The TrainingOutput object that is returned on successful completion of a training job with hyperparameter tuning includes a list of HyperparameterOutput objects, one for each successful trial.

func (GoogleCloudMlV1__HyperparameterOutputOutput) AllMetrics 

func (o GoogleCloudMlV1__HyperparameterOutputOutput) AllMetrics() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricArrayOutput

All recorded object metrics for this trial. This field is not currently populated.

func (GoogleCloudMlV1__HyperparameterOutputOutput) BuiltInAlgorithmOutput 

func (o GoogleCloudMlV1__HyperparameterOutputOutput) BuiltInAlgorithmOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput

Details related to built-in algorithms jobs. Only set for trials of built-in algorithms jobs that have succeeded.

func (GoogleCloudMlV1__HyperparameterOutputOutput) ElementType 

func (GoogleCloudMlV1__HyperparameterOutputOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterOutputOutput) FinalMetric 

func (o GoogleCloudMlV1__HyperparameterOutputOutput) FinalMetric() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricPtrOutput

The final objective metric seen for this trial.

func (GoogleCloudMlV1__HyperparameterOutputOutput) Hyperparameters 

func (o GoogleCloudMlV1__HyperparameterOutputOutput) Hyperparameters() pulumi.StringMapOutput

The hyperparameters given to this trial.

func (GoogleCloudMlV1__HyperparameterOutputOutput) IsTrialStoppedEarly 

func (o GoogleCloudMlV1__HyperparameterOutputOutput) IsTrialStoppedEarly() pulumi.BoolPtrOutput

True if the trial is stopped early.

func (GoogleCloudMlV1__HyperparameterOutputOutput) ToGoogleCloudMlV1__HyperparameterOutputOutput 

func (o GoogleCloudMlV1__HyperparameterOutputOutput) ToGoogleCloudMlV1__HyperparameterOutputOutput() GoogleCloudMlV1__HyperparameterOutputOutput

func (GoogleCloudMlV1__HyperparameterOutputOutput) ToGoogleCloudMlV1__HyperparameterOutputOutputWithContext 

func (o GoogleCloudMlV1__HyperparameterOutputOutput) ToGoogleCloudMlV1__HyperparameterOutputOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterOutputOutput

func (GoogleCloudMlV1__HyperparameterOutputOutput) TrialId 

func (o GoogleCloudMlV1__HyperparameterOutputOutput) TrialId() pulumi.StringPtrOutput

The trial id for these results.

func (GoogleCloudMlV1__HyperparameterOutputOutput) WebAccessUris added in v0.5.0 

func (o GoogleCloudMlV1__HyperparameterOutputOutput) WebAccessUris() pulumi.StringMapOutput

URIs for accessing [interactive shells](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a hyperparameter tuning job and the job's training_input.enable_web_access is `true`. The keys are names of each node in the training job; for example, `master-replica-0` for the master node, `worker-replica-0` for the first worker, and `ps-replica-0` for the first parameter server. The values are the URIs for each node's interactive shell.

type GoogleCloudMlV1__HyperparameterOutputResponse 

type GoogleCloudMlV1__HyperparameterOutputResponse struct {
	// All recorded object metrics for this trial. This field is not currently populated.
	AllMetrics []GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponse `pulumi:"allMetrics"`
	// Details related to built-in algorithms jobs. Only set for trials of built-in algorithms jobs that have succeeded.
	BuiltInAlgorithmOutput GoogleCloudMlV1__BuiltInAlgorithmOutputResponse `pulumi:"builtInAlgorithmOutput"`
	// End time for the trial.
	EndTime string `pulumi:"endTime"`
	// The final objective metric seen for this trial.
	FinalMetric GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponse `pulumi:"finalMetric"`
	// The hyperparameters given to this trial.
	Hyperparameters map[string]string `pulumi:"hyperparameters"`
	// True if the trial is stopped early.
	IsTrialStoppedEarly bool `pulumi:"isTrialStoppedEarly"`
	// Start time for the trial.
	StartTime string `pulumi:"startTime"`
	// The detailed state of the trial.
	State string `pulumi:"state"`
	// The trial id for these results.
	TrialId string `pulumi:"trialId"`
	// URIs for accessing [interactive shells](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a hyperparameter tuning job and the job's training_input.enable_web_access is `true`. The keys are names of each node in the training job; for example, `master-replica-0` for the master node, `worker-replica-0` for the first worker, and `ps-replica-0` for the first parameter server. The values are the URIs for each node's interactive shell.
	WebAccessUris map[string]string `pulumi:"webAccessUris"`
}

Represents the result of a single hyperparameter tuning trial from a training job. The TrainingOutput object that is returned on successful completion of a training job with hyperparameter tuning includes a list of HyperparameterOutput objects, one for each successful trial.

type GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput 

type GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput) ElementType 

func (GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput) Index 

func (o GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__HyperparameterOutputResponseOutput

func (GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput) ToGoogleCloudMlV1__HyperparameterOutputResponseArrayOutput 

func (o GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput) ToGoogleCloudMlV1__HyperparameterOutputResponseArrayOutput() GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput

func (GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput) ToGoogleCloudMlV1__HyperparameterOutputResponseArrayOutputWithContext 

func (o GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput) ToGoogleCloudMlV1__HyperparameterOutputResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput

type GoogleCloudMlV1__HyperparameterOutputResponseOutput 

type GoogleCloudMlV1__HyperparameterOutputResponseOutput struct{ *pulumi.OutputState }

Represents the result of a single hyperparameter tuning trial from a training job. The TrainingOutput object that is returned on successful completion of a training job with hyperparameter tuning includes a list of HyperparameterOutput objects, one for each successful trial.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) AllMetrics 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) AllMetrics() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseArrayOutput

All recorded object metrics for this trial. This field is not currently populated.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) BuiltInAlgorithmOutput 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) BuiltInAlgorithmOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput

Details related to built-in algorithms jobs. Only set for trials of built-in algorithms jobs that have succeeded.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) ElementType 

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) EndTime 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) EndTime() pulumi.StringOutput

End time for the trial.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) FinalMetric 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) FinalMetric() GoogleCloudMlV1_HyperparameterOutput_HyperparameterMetricResponseOutput

The final objective metric seen for this trial.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) Hyperparameters 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) Hyperparameters() pulumi.StringMapOutput

The hyperparameters given to this trial.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) IsTrialStoppedEarly 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) IsTrialStoppedEarly() pulumi.BoolOutput

True if the trial is stopped early.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) StartTime 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) StartTime() pulumi.StringOutput

Start time for the trial.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) State 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) State() pulumi.StringOutput

The detailed state of the trial.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) ToGoogleCloudMlV1__HyperparameterOutputResponseOutput 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) ToGoogleCloudMlV1__HyperparameterOutputResponseOutput() GoogleCloudMlV1__HyperparameterOutputResponseOutput

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) ToGoogleCloudMlV1__HyperparameterOutputResponseOutputWithContext 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) ToGoogleCloudMlV1__HyperparameterOutputResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterOutputResponseOutput

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) TrialId 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) TrialId() pulumi.StringOutput

The trial id for these results.

func (GoogleCloudMlV1__HyperparameterOutputResponseOutput) WebAccessUris added in v0.5.0 

func (o GoogleCloudMlV1__HyperparameterOutputResponseOutput) WebAccessUris() pulumi.StringMapOutput

URIs for accessing [interactive shells](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) (one URI for each training node). Only available if this trial is part of a hyperparameter tuning job and the job's training_input.enable_web_access is `true`. The keys are names of each node in the training job; for example, `master-replica-0` for the master node, `worker-replica-0` for the first worker, and `ps-replica-0` for the first parameter server. The values are the URIs for each node's interactive shell.

type GoogleCloudMlV1__HyperparameterSpec 

type GoogleCloudMlV1__HyperparameterSpec struct {
	// Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.
	Algorithm *GoogleCloudMlV1__HyperparameterSpecAlgorithm `pulumi:"algorithm"`
	// Optional. Indicates if the hyperparameter tuning job enables auto trial early stopping.
	EnableTrialEarlyStopping *bool `pulumi:"enableTrialEarlyStopping"`
	// The type of goal to use for tuning. Available types are `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`.
	Goal GoogleCloudMlV1__HyperparameterSpecGoal `pulumi:"goal"`
	// Optional. The TensorFlow summary tag name to use for optimizing trials. For current versions of TensorFlow, this tag name should exactly match what is shown in TensorBoard, including all scopes. For versions of TensorFlow prior to 0.12, this should be only the tag passed to tf.Summary. By default, "training/hptuning/metric" will be used.
	HyperparameterMetricTag *string `pulumi:"hyperparameterMetricTag"`
	// Optional. The number of failed trials that need to be seen before failing the hyperparameter tuning job. You can specify this field to override the default failing criteria for AI Platform hyperparameter tuning jobs. Defaults to zero, which means the service decides when a hyperparameter job should fail.
	MaxFailedTrials *int `pulumi:"maxFailedTrials"`
	// Optional. The number of training trials to run concurrently. You can reduce the time it takes to perform hyperparameter tuning by adding trials in parallel. However, each trail only benefits from the information gained in completed trials. That means that a trial does not get access to the results of trials running at the same time, which could reduce the quality of the overall optimization. Each trial will use the same scale tier and machine types. Defaults to one.
	MaxParallelTrials *int `pulumi:"maxParallelTrials"`
	// Optional. How many training trials should be attempted to optimize the specified hyperparameters. Defaults to one.
	MaxTrials *int `pulumi:"maxTrials"`
	// The set of parameters to tune.
	Params []GoogleCloudMlV1__ParameterSpec `pulumi:"params"`
	// Optional. The prior hyperparameter tuning job id that users hope to continue with. The job id will be used to find the corresponding vizier study guid and resume the study.
	ResumePreviousJobId *string `pulumi:"resumePreviousJobId"`
}

Represents a set of hyperparameters to optimize.

type GoogleCloudMlV1__HyperparameterSpecAlgorithm added in v0.4.0 

type GoogleCloudMlV1__HyperparameterSpecAlgorithm string

Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ElementType added in v0.4.0 

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutput added in v0.6.0 

func (e GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutput() GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput() GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__HyperparameterSpecAlgorithm) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__HyperparameterSpecAlgorithmInput added in v0.6.0 

type GoogleCloudMlV1__HyperparameterSpecAlgorithmInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutput() GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput
	ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutputWithContext(context.Context) GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput
}

GoogleCloudMlV1__HyperparameterSpecAlgorithmInput is an input type that accepts GoogleCloudMlV1__HyperparameterSpecAlgorithmArgs and GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput values. You can construct a concrete instance of `GoogleCloudMlV1__HyperparameterSpecAlgorithmInput` via: 

GoogleCloudMlV1__HyperparameterSpecAlgorithmArgs{...}

type GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput added in v0.6.0 

type GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutput() GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput() GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrInput added in v0.6.0 

type GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput() GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput
	ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutputWithContext(context.Context) GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput
}

func GoogleCloudMlV1__HyperparameterSpecAlgorithmPtr added in v0.6.0 

func GoogleCloudMlV1__HyperparameterSpecAlgorithmPtr(v string) GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrInput

type GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput added in v0.6.0 

type GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) Elem() GoogleCloudMlV1__HyperparameterSpecAlgorithmOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput() GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__HyperparameterSpecArgs 

type GoogleCloudMlV1__HyperparameterSpecArgs struct {
	// Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.
	Algorithm GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrInput `pulumi:"algorithm"`
	// Optional. Indicates if the hyperparameter tuning job enables auto trial early stopping.
	EnableTrialEarlyStopping pulumi.BoolPtrInput `pulumi:"enableTrialEarlyStopping"`
	// The type of goal to use for tuning. Available types are `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`.
	Goal GoogleCloudMlV1__HyperparameterSpecGoalInput `pulumi:"goal"`
	// Optional. The TensorFlow summary tag name to use for optimizing trials. For current versions of TensorFlow, this tag name should exactly match what is shown in TensorBoard, including all scopes. For versions of TensorFlow prior to 0.12, this should be only the tag passed to tf.Summary. By default, "training/hptuning/metric" will be used.
	HyperparameterMetricTag pulumi.StringPtrInput `pulumi:"hyperparameterMetricTag"`
	// Optional. The number of failed trials that need to be seen before failing the hyperparameter tuning job. You can specify this field to override the default failing criteria for AI Platform hyperparameter tuning jobs. Defaults to zero, which means the service decides when a hyperparameter job should fail.
	MaxFailedTrials pulumi.IntPtrInput `pulumi:"maxFailedTrials"`
	// Optional. The number of training trials to run concurrently. You can reduce the time it takes to perform hyperparameter tuning by adding trials in parallel. However, each trail only benefits from the information gained in completed trials. That means that a trial does not get access to the results of trials running at the same time, which could reduce the quality of the overall optimization. Each trial will use the same scale tier and machine types. Defaults to one.
	MaxParallelTrials pulumi.IntPtrInput `pulumi:"maxParallelTrials"`
	// Optional. How many training trials should be attempted to optimize the specified hyperparameters. Defaults to one.
	MaxTrials pulumi.IntPtrInput `pulumi:"maxTrials"`
	// The set of parameters to tune.
	Params GoogleCloudMlV1__ParameterSpecArrayInput `pulumi:"params"`
	// Optional. The prior hyperparameter tuning job id that users hope to continue with. The job id will be used to find the corresponding vizier study guid and resume the study.
	ResumePreviousJobId pulumi.StringPtrInput `pulumi:"resumePreviousJobId"`
}

Represents a set of hyperparameters to optimize.

func (GoogleCloudMlV1__HyperparameterSpecArgs) ElementType 

func (GoogleCloudMlV1__HyperparameterSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecArgs) ToGoogleCloudMlV1__HyperparameterSpecOutput 

func (i GoogleCloudMlV1__HyperparameterSpecArgs) ToGoogleCloudMlV1__HyperparameterSpecOutput() GoogleCloudMlV1__HyperparameterSpecOutput

func (GoogleCloudMlV1__HyperparameterSpecArgs) ToGoogleCloudMlV1__HyperparameterSpecOutputWithContext 

func (i GoogleCloudMlV1__HyperparameterSpecArgs) ToGoogleCloudMlV1__HyperparameterSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecOutput

func (GoogleCloudMlV1__HyperparameterSpecArgs) ToGoogleCloudMlV1__HyperparameterSpecPtrOutput 

func (i GoogleCloudMlV1__HyperparameterSpecArgs) ToGoogleCloudMlV1__HyperparameterSpecPtrOutput() GoogleCloudMlV1__HyperparameterSpecPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecArgs) ToGoogleCloudMlV1__HyperparameterSpecPtrOutputWithContext 

func (i GoogleCloudMlV1__HyperparameterSpecArgs) ToGoogleCloudMlV1__HyperparameterSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecPtrOutput

type GoogleCloudMlV1__HyperparameterSpecGoal added in v0.4.0 

type GoogleCloudMlV1__HyperparameterSpecGoal string

Required. The type of goal to use for tuning. Available types are `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`.

func (GoogleCloudMlV1__HyperparameterSpecGoal) ElementType added in v0.4.0 

func (GoogleCloudMlV1__HyperparameterSpecGoal) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecGoal) ToGoogleCloudMlV1__HyperparameterSpecGoalOutput added in v0.6.0 

func (e GoogleCloudMlV1__HyperparameterSpecGoal) ToGoogleCloudMlV1__HyperparameterSpecGoalOutput() GoogleCloudMlV1__HyperparameterSpecGoalOutput

func (GoogleCloudMlV1__HyperparameterSpecGoal) ToGoogleCloudMlV1__HyperparameterSpecGoalOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__HyperparameterSpecGoal) ToGoogleCloudMlV1__HyperparameterSpecGoalOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecGoalOutput

func (GoogleCloudMlV1__HyperparameterSpecGoal) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__HyperparameterSpecGoal) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutput() GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecGoal) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__HyperparameterSpecGoal) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecGoal) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__HyperparameterSpecGoal) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__HyperparameterSpecGoal) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__HyperparameterSpecGoal) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__HyperparameterSpecGoal) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__HyperparameterSpecGoal) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecGoal) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__HyperparameterSpecGoal) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__HyperparameterSpecGoalInput added in v0.6.0 

type GoogleCloudMlV1__HyperparameterSpecGoalInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__HyperparameterSpecGoalOutput() GoogleCloudMlV1__HyperparameterSpecGoalOutput
	ToGoogleCloudMlV1__HyperparameterSpecGoalOutputWithContext(context.Context) GoogleCloudMlV1__HyperparameterSpecGoalOutput
}

GoogleCloudMlV1__HyperparameterSpecGoalInput is an input type that accepts GoogleCloudMlV1__HyperparameterSpecGoalArgs and GoogleCloudMlV1__HyperparameterSpecGoalOutput values. You can construct a concrete instance of `GoogleCloudMlV1__HyperparameterSpecGoalInput` via: 

GoogleCloudMlV1__HyperparameterSpecGoalArgs{...}

type GoogleCloudMlV1__HyperparameterSpecGoalOutput added in v0.6.0 

type GoogleCloudMlV1__HyperparameterSpecGoalOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalOutput() GoogleCloudMlV1__HyperparameterSpecGoalOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecGoalOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutput() GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__HyperparameterSpecGoalPtrInput added in v0.6.0 

type GoogleCloudMlV1__HyperparameterSpecGoalPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutput() GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput
	ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutputWithContext(context.Context) GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput
}

func GoogleCloudMlV1__HyperparameterSpecGoalPtr added in v0.6.0 

func GoogleCloudMlV1__HyperparameterSpecGoalPtr(v string) GoogleCloudMlV1__HyperparameterSpecGoalPtrInput

type GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput added in v0.6.0 

type GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) Elem() GoogleCloudMlV1__HyperparameterSpecGoalOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutput() GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecGoalPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__HyperparameterSpecInput 

type GoogleCloudMlV1__HyperparameterSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__HyperparameterSpecOutput() GoogleCloudMlV1__HyperparameterSpecOutput
	ToGoogleCloudMlV1__HyperparameterSpecOutputWithContext(context.Context) GoogleCloudMlV1__HyperparameterSpecOutput
}

GoogleCloudMlV1__HyperparameterSpecInput is an input type that accepts GoogleCloudMlV1__HyperparameterSpecArgs and GoogleCloudMlV1__HyperparameterSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1__HyperparameterSpecInput` via: 

GoogleCloudMlV1__HyperparameterSpecArgs{...}

type GoogleCloudMlV1__HyperparameterSpecOutput 

type GoogleCloudMlV1__HyperparameterSpecOutput struct{ *pulumi.OutputState }

Represents a set of hyperparameters to optimize.

func (GoogleCloudMlV1__HyperparameterSpecOutput) Algorithm 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) Algorithm() GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput

Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.

func (GoogleCloudMlV1__HyperparameterSpecOutput) ElementType 

func (GoogleCloudMlV1__HyperparameterSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecOutput) EnableTrialEarlyStopping 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) EnableTrialEarlyStopping() pulumi.BoolPtrOutput

Optional. Indicates if the hyperparameter tuning job enables auto trial early stopping.

func (GoogleCloudMlV1__HyperparameterSpecOutput) Goal 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) Goal() GoogleCloudMlV1__HyperparameterSpecGoalOutput

The type of goal to use for tuning. Available types are `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`.

func (GoogleCloudMlV1__HyperparameterSpecOutput) HyperparameterMetricTag 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) HyperparameterMetricTag() pulumi.StringPtrOutput

Optional. The TensorFlow summary tag name to use for optimizing trials. For current versions of TensorFlow, this tag name should exactly match what is shown in TensorBoard, including all scopes. For versions of TensorFlow prior to 0.12, this should be only the tag passed to tf.Summary. By default, "training/hptuning/metric" will be used.

func (GoogleCloudMlV1__HyperparameterSpecOutput) MaxFailedTrials 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) MaxFailedTrials() pulumi.IntPtrOutput

Optional. The number of failed trials that need to be seen before failing the hyperparameter tuning job. You can specify this field to override the default failing criteria for AI Platform hyperparameter tuning jobs. Defaults to zero, which means the service decides when a hyperparameter job should fail.

func (GoogleCloudMlV1__HyperparameterSpecOutput) MaxParallelTrials 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) MaxParallelTrials() pulumi.IntPtrOutput

Optional. The number of training trials to run concurrently. You can reduce the time it takes to perform hyperparameter tuning by adding trials in parallel. However, each trail only benefits from the information gained in completed trials. That means that a trial does not get access to the results of trials running at the same time, which could reduce the quality of the overall optimization. Each trial will use the same scale tier and machine types. Defaults to one.

func (GoogleCloudMlV1__HyperparameterSpecOutput) MaxTrials 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) MaxTrials() pulumi.IntPtrOutput

Optional. How many training trials should be attempted to optimize the specified hyperparameters. Defaults to one.

func (GoogleCloudMlV1__HyperparameterSpecOutput) Params 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) Params() GoogleCloudMlV1__ParameterSpecArrayOutput

The set of parameters to tune.

func (GoogleCloudMlV1__HyperparameterSpecOutput) ResumePreviousJobId 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) ResumePreviousJobId() pulumi.StringPtrOutput

Optional. The prior hyperparameter tuning job id that users hope to continue with. The job id will be used to find the corresponding vizier study guid and resume the study.

func (GoogleCloudMlV1__HyperparameterSpecOutput) ToGoogleCloudMlV1__HyperparameterSpecOutput 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) ToGoogleCloudMlV1__HyperparameterSpecOutput() GoogleCloudMlV1__HyperparameterSpecOutput

func (GoogleCloudMlV1__HyperparameterSpecOutput) ToGoogleCloudMlV1__HyperparameterSpecOutputWithContext 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) ToGoogleCloudMlV1__HyperparameterSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecOutput

func (GoogleCloudMlV1__HyperparameterSpecOutput) ToGoogleCloudMlV1__HyperparameterSpecPtrOutput 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) ToGoogleCloudMlV1__HyperparameterSpecPtrOutput() GoogleCloudMlV1__HyperparameterSpecPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecOutput) ToGoogleCloudMlV1__HyperparameterSpecPtrOutputWithContext 

func (o GoogleCloudMlV1__HyperparameterSpecOutput) ToGoogleCloudMlV1__HyperparameterSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecPtrOutput

type GoogleCloudMlV1__HyperparameterSpecPtrInput 

type GoogleCloudMlV1__HyperparameterSpecPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__HyperparameterSpecPtrOutput() GoogleCloudMlV1__HyperparameterSpecPtrOutput
	ToGoogleCloudMlV1__HyperparameterSpecPtrOutputWithContext(context.Context) GoogleCloudMlV1__HyperparameterSpecPtrOutput
}

GoogleCloudMlV1__HyperparameterSpecPtrInput is an input type that accepts GoogleCloudMlV1__HyperparameterSpecArgs, GoogleCloudMlV1__HyperparameterSpecPtr and GoogleCloudMlV1__HyperparameterSpecPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__HyperparameterSpecPtrInput` via: 

        GoogleCloudMlV1__HyperparameterSpecArgs{...}

or:

        nil

func GoogleCloudMlV1__HyperparameterSpecPtr 

func GoogleCloudMlV1__HyperparameterSpecPtr(v *GoogleCloudMlV1__HyperparameterSpecArgs) GoogleCloudMlV1__HyperparameterSpecPtrInput

type GoogleCloudMlV1__HyperparameterSpecPtrOutput 

type GoogleCloudMlV1__HyperparameterSpecPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) Algorithm 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) Algorithm() GoogleCloudMlV1__HyperparameterSpecAlgorithmPtrOutput

Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) Elem 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) Elem() GoogleCloudMlV1__HyperparameterSpecOutput

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) ElementType 

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) EnableTrialEarlyStopping 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) EnableTrialEarlyStopping() pulumi.BoolPtrOutput

Optional. Indicates if the hyperparameter tuning job enables auto trial early stopping.

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) Goal 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) Goal() GoogleCloudMlV1__HyperparameterSpecGoalPtrOutput

The type of goal to use for tuning. Available types are `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`.

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) HyperparameterMetricTag 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) HyperparameterMetricTag() pulumi.StringPtrOutput

Optional. The TensorFlow summary tag name to use for optimizing trials. For current versions of TensorFlow, this tag name should exactly match what is shown in TensorBoard, including all scopes. For versions of TensorFlow prior to 0.12, this should be only the tag passed to tf.Summary. By default, "training/hptuning/metric" will be used.

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) MaxFailedTrials 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) MaxFailedTrials() pulumi.IntPtrOutput

Optional. The number of failed trials that need to be seen before failing the hyperparameter tuning job. You can specify this field to override the default failing criteria for AI Platform hyperparameter tuning jobs. Defaults to zero, which means the service decides when a hyperparameter job should fail.

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) MaxParallelTrials 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) MaxParallelTrials() pulumi.IntPtrOutput

Optional. The number of training trials to run concurrently. You can reduce the time it takes to perform hyperparameter tuning by adding trials in parallel. However, each trail only benefits from the information gained in completed trials. That means that a trial does not get access to the results of trials running at the same time, which could reduce the quality of the overall optimization. Each trial will use the same scale tier and machine types. Defaults to one.

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) MaxTrials 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) MaxTrials() pulumi.IntPtrOutput

Optional. How many training trials should be attempted to optimize the specified hyperparameters. Defaults to one.

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) Params 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) Params() GoogleCloudMlV1__ParameterSpecArrayOutput

The set of parameters to tune.

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) ResumePreviousJobId 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) ResumePreviousJobId() pulumi.StringPtrOutput

Optional. The prior hyperparameter tuning job id that users hope to continue with. The job id will be used to find the corresponding vizier study guid and resume the study.

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecPtrOutput 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecPtrOutput() GoogleCloudMlV1__HyperparameterSpecPtrOutput

func (GoogleCloudMlV1__HyperparameterSpecPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecPtrOutputWithContext 

func (o GoogleCloudMlV1__HyperparameterSpecPtrOutput) ToGoogleCloudMlV1__HyperparameterSpecPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecPtrOutput

type GoogleCloudMlV1__HyperparameterSpecResponse 

type GoogleCloudMlV1__HyperparameterSpecResponse struct {
	// Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.
	Algorithm string `pulumi:"algorithm"`
	// Optional. Indicates if the hyperparameter tuning job enables auto trial early stopping.
	EnableTrialEarlyStopping bool `pulumi:"enableTrialEarlyStopping"`
	// The type of goal to use for tuning. Available types are `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`.
	Goal string `pulumi:"goal"`
	// Optional. The TensorFlow summary tag name to use for optimizing trials. For current versions of TensorFlow, this tag name should exactly match what is shown in TensorBoard, including all scopes. For versions of TensorFlow prior to 0.12, this should be only the tag passed to tf.Summary. By default, "training/hptuning/metric" will be used.
	HyperparameterMetricTag string `pulumi:"hyperparameterMetricTag"`
	// Optional. The number of failed trials that need to be seen before failing the hyperparameter tuning job. You can specify this field to override the default failing criteria for AI Platform hyperparameter tuning jobs. Defaults to zero, which means the service decides when a hyperparameter job should fail.
	MaxFailedTrials int `pulumi:"maxFailedTrials"`
	// Optional. The number of training trials to run concurrently. You can reduce the time it takes to perform hyperparameter tuning by adding trials in parallel. However, each trail only benefits from the information gained in completed trials. That means that a trial does not get access to the results of trials running at the same time, which could reduce the quality of the overall optimization. Each trial will use the same scale tier and machine types. Defaults to one.
	MaxParallelTrials int `pulumi:"maxParallelTrials"`
	// Optional. How many training trials should be attempted to optimize the specified hyperparameters. Defaults to one.
	MaxTrials int `pulumi:"maxTrials"`
	// The set of parameters to tune.
	Params []GoogleCloudMlV1__ParameterSpecResponse `pulumi:"params"`
	// Optional. The prior hyperparameter tuning job id that users hope to continue with. The job id will be used to find the corresponding vizier study guid and resume the study.
	ResumePreviousJobId string `pulumi:"resumePreviousJobId"`
}

Represents a set of hyperparameters to optimize.

type GoogleCloudMlV1__HyperparameterSpecResponseOutput 

type GoogleCloudMlV1__HyperparameterSpecResponseOutput struct{ *pulumi.OutputState }

Represents a set of hyperparameters to optimize.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) Algorithm 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) Algorithm() pulumi.StringOutput

Optional. The search algorithm specified for the hyperparameter tuning job. Uses the default AI Platform hyperparameter tuning algorithm if unspecified.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) ElementType 

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) EnableTrialEarlyStopping 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) EnableTrialEarlyStopping() pulumi.BoolOutput

Optional. Indicates if the hyperparameter tuning job enables auto trial early stopping.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) Goal 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) Goal() pulumi.StringOutput

The type of goal to use for tuning. Available types are `MAXIMIZE` and `MINIMIZE`. Defaults to `MAXIMIZE`.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) HyperparameterMetricTag 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) HyperparameterMetricTag() pulumi.StringOutput

Optional. The TensorFlow summary tag name to use for optimizing trials. For current versions of TensorFlow, this tag name should exactly match what is shown in TensorBoard, including all scopes. For versions of TensorFlow prior to 0.12, this should be only the tag passed to tf.Summary. By default, "training/hptuning/metric" will be used.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) MaxFailedTrials 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) MaxFailedTrials() pulumi.IntOutput

Optional. The number of failed trials that need to be seen before failing the hyperparameter tuning job. You can specify this field to override the default failing criteria for AI Platform hyperparameter tuning jobs. Defaults to zero, which means the service decides when a hyperparameter job should fail.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) MaxParallelTrials 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) MaxParallelTrials() pulumi.IntOutput

Optional. The number of training trials to run concurrently. You can reduce the time it takes to perform hyperparameter tuning by adding trials in parallel. However, each trail only benefits from the information gained in completed trials. That means that a trial does not get access to the results of trials running at the same time, which could reduce the quality of the overall optimization. Each trial will use the same scale tier and machine types. Defaults to one.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) MaxTrials 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) MaxTrials() pulumi.IntOutput

Optional. How many training trials should be attempted to optimize the specified hyperparameters. Defaults to one.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) Params 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) Params() GoogleCloudMlV1__ParameterSpecResponseArrayOutput

The set of parameters to tune.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) ResumePreviousJobId 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) ResumePreviousJobId() pulumi.StringOutput

Optional. The prior hyperparameter tuning job id that users hope to continue with. The job id will be used to find the corresponding vizier study guid and resume the study.

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) ToGoogleCloudMlV1__HyperparameterSpecResponseOutput 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) ToGoogleCloudMlV1__HyperparameterSpecResponseOutput() GoogleCloudMlV1__HyperparameterSpecResponseOutput

func (GoogleCloudMlV1__HyperparameterSpecResponseOutput) ToGoogleCloudMlV1__HyperparameterSpecResponseOutputWithContext 

func (o GoogleCloudMlV1__HyperparameterSpecResponseOutput) ToGoogleCloudMlV1__HyperparameterSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__HyperparameterSpecResponseOutput

type GoogleCloudMlV1__IntegratedGradientsAttribution 

type GoogleCloudMlV1__IntegratedGradientsAttribution struct {
	// Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.
	NumIntegralSteps *int `pulumi:"numIntegralSteps"`
}

Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

type GoogleCloudMlV1__IntegratedGradientsAttributionArgs 

type GoogleCloudMlV1__IntegratedGradientsAttributionArgs struct {
	// Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.
	NumIntegralSteps pulumi.IntPtrInput `pulumi:"numIntegralSteps"`
}

Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ElementType 

func (GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ToGoogleCloudMlV1__IntegratedGradientsAttributionOutput 

func (i GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ToGoogleCloudMlV1__IntegratedGradientsAttributionOutput() GoogleCloudMlV1__IntegratedGradientsAttributionOutput

func (GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ToGoogleCloudMlV1__IntegratedGradientsAttributionOutputWithContext 

func (i GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ToGoogleCloudMlV1__IntegratedGradientsAttributionOutputWithContext(ctx context.Context) GoogleCloudMlV1__IntegratedGradientsAttributionOutput

func (GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput 

func (i GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput() GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput

func (GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutputWithContext 

func (i GoogleCloudMlV1__IntegratedGradientsAttributionArgs) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput

type GoogleCloudMlV1__IntegratedGradientsAttributionInput 

type GoogleCloudMlV1__IntegratedGradientsAttributionInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__IntegratedGradientsAttributionOutput() GoogleCloudMlV1__IntegratedGradientsAttributionOutput
	ToGoogleCloudMlV1__IntegratedGradientsAttributionOutputWithContext(context.Context) GoogleCloudMlV1__IntegratedGradientsAttributionOutput
}

GoogleCloudMlV1__IntegratedGradientsAttributionInput is an input type that accepts GoogleCloudMlV1__IntegratedGradientsAttributionArgs and GoogleCloudMlV1__IntegratedGradientsAttributionOutput values. You can construct a concrete instance of `GoogleCloudMlV1__IntegratedGradientsAttributionInput` via: 

GoogleCloudMlV1__IntegratedGradientsAttributionArgs{...}

type GoogleCloudMlV1__IntegratedGradientsAttributionOutput 

type GoogleCloudMlV1__IntegratedGradientsAttributionOutput struct{ *pulumi.OutputState }

Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ElementType 

func (GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__IntegratedGradientsAttributionOutput) NumIntegralSteps 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionOutput) NumIntegralSteps() pulumi.IntPtrOutput

Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.

func (GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionOutput 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionOutput() GoogleCloudMlV1__IntegratedGradientsAttributionOutput

func (GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionOutputWithContext 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionOutputWithContext(ctx context.Context) GoogleCloudMlV1__IntegratedGradientsAttributionOutput

func (GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput() GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput

func (GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutputWithContext 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput

type GoogleCloudMlV1__IntegratedGradientsAttributionPtrInput 

type GoogleCloudMlV1__IntegratedGradientsAttributionPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput() GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput
	ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutputWithContext(context.Context) GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput
}

GoogleCloudMlV1__IntegratedGradientsAttributionPtrInput is an input type that accepts GoogleCloudMlV1__IntegratedGradientsAttributionArgs, GoogleCloudMlV1__IntegratedGradientsAttributionPtr and GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__IntegratedGradientsAttributionPtrInput` via: 

        GoogleCloudMlV1__IntegratedGradientsAttributionArgs{...}

or:

        nil

func GoogleCloudMlV1__IntegratedGradientsAttributionPtr 

func GoogleCloudMlV1__IntegratedGradientsAttributionPtr(v *GoogleCloudMlV1__IntegratedGradientsAttributionArgs) GoogleCloudMlV1__IntegratedGradientsAttributionPtrInput

type GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput 

type GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) Elem 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) Elem() GoogleCloudMlV1__IntegratedGradientsAttributionOutput

func (GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) ElementType 

func (GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) NumIntegralSteps 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) NumIntegralSteps() pulumi.IntPtrOutput

Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.

func (GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput() GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput

func (GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutputWithContext 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__IntegratedGradientsAttributionPtrOutput

type GoogleCloudMlV1__IntegratedGradientsAttributionResponse 

type GoogleCloudMlV1__IntegratedGradientsAttributionResponse struct {
	// Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.
	NumIntegralSteps int `pulumi:"numIntegralSteps"`
}

Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

type GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput 

type GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput struct{ *pulumi.OutputState }

Attributes credit by computing the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

func (GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput) ElementType 

func (GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput) NumIntegralSteps 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput) NumIntegralSteps() pulumi.IntOutput

Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.

func (GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput() GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput

func (GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionResponseOutputWithContext 

func (o GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput) ToGoogleCloudMlV1__IntegratedGradientsAttributionResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__IntegratedGradientsAttributionResponseOutput

type GoogleCloudMlV1__ManualScaling 

type GoogleCloudMlV1__ManualScaling struct {
	// The number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed, so the cost of operating this model will be proportional to `nodes` * number of hours since last billing cycle plus the cost for each prediction performed.
	Nodes *int `pulumi:"nodes"`
}

Options for manually scaling a model.

type GoogleCloudMlV1__ManualScalingArgs 

type GoogleCloudMlV1__ManualScalingArgs struct {
	// The number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed, so the cost of operating this model will be proportional to `nodes` * number of hours since last billing cycle plus the cost for each prediction performed.
	Nodes pulumi.IntPtrInput `pulumi:"nodes"`
}

Options for manually scaling a model.

func (GoogleCloudMlV1__ManualScalingArgs) ElementType 

func (GoogleCloudMlV1__ManualScalingArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__ManualScalingArgs) ToGoogleCloudMlV1__ManualScalingOutput 

func (i GoogleCloudMlV1__ManualScalingArgs) ToGoogleCloudMlV1__ManualScalingOutput() GoogleCloudMlV1__ManualScalingOutput

func (GoogleCloudMlV1__ManualScalingArgs) ToGoogleCloudMlV1__ManualScalingOutputWithContext 

func (i GoogleCloudMlV1__ManualScalingArgs) ToGoogleCloudMlV1__ManualScalingOutputWithContext(ctx context.Context) GoogleCloudMlV1__ManualScalingOutput

func (GoogleCloudMlV1__ManualScalingArgs) ToGoogleCloudMlV1__ManualScalingPtrOutput 

func (i GoogleCloudMlV1__ManualScalingArgs) ToGoogleCloudMlV1__ManualScalingPtrOutput() GoogleCloudMlV1__ManualScalingPtrOutput

func (GoogleCloudMlV1__ManualScalingArgs) ToGoogleCloudMlV1__ManualScalingPtrOutputWithContext 

func (i GoogleCloudMlV1__ManualScalingArgs) ToGoogleCloudMlV1__ManualScalingPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ManualScalingPtrOutput

type GoogleCloudMlV1__ManualScalingInput 

type GoogleCloudMlV1__ManualScalingInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ManualScalingOutput() GoogleCloudMlV1__ManualScalingOutput
	ToGoogleCloudMlV1__ManualScalingOutputWithContext(context.Context) GoogleCloudMlV1__ManualScalingOutput
}

GoogleCloudMlV1__ManualScalingInput is an input type that accepts GoogleCloudMlV1__ManualScalingArgs and GoogleCloudMlV1__ManualScalingOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ManualScalingInput` via: 

GoogleCloudMlV1__ManualScalingArgs{...}

type GoogleCloudMlV1__ManualScalingOutput 

type GoogleCloudMlV1__ManualScalingOutput struct{ *pulumi.OutputState }

Options for manually scaling a model.

func (GoogleCloudMlV1__ManualScalingOutput) ElementType 

func (GoogleCloudMlV1__ManualScalingOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ManualScalingOutput) Nodes 

func (o GoogleCloudMlV1__ManualScalingOutput) Nodes() pulumi.IntPtrOutput

The number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed, so the cost of operating this model will be proportional to `nodes` * number of hours since last billing cycle plus the cost for each prediction performed.

func (GoogleCloudMlV1__ManualScalingOutput) ToGoogleCloudMlV1__ManualScalingOutput 

func (o GoogleCloudMlV1__ManualScalingOutput) ToGoogleCloudMlV1__ManualScalingOutput() GoogleCloudMlV1__ManualScalingOutput

func (GoogleCloudMlV1__ManualScalingOutput) ToGoogleCloudMlV1__ManualScalingOutputWithContext 

func (o GoogleCloudMlV1__ManualScalingOutput) ToGoogleCloudMlV1__ManualScalingOutputWithContext(ctx context.Context) GoogleCloudMlV1__ManualScalingOutput

func (GoogleCloudMlV1__ManualScalingOutput) ToGoogleCloudMlV1__ManualScalingPtrOutput 

func (o GoogleCloudMlV1__ManualScalingOutput) ToGoogleCloudMlV1__ManualScalingPtrOutput() GoogleCloudMlV1__ManualScalingPtrOutput

func (GoogleCloudMlV1__ManualScalingOutput) ToGoogleCloudMlV1__ManualScalingPtrOutputWithContext 

func (o GoogleCloudMlV1__ManualScalingOutput) ToGoogleCloudMlV1__ManualScalingPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ManualScalingPtrOutput

type GoogleCloudMlV1__ManualScalingPtrInput 

type GoogleCloudMlV1__ManualScalingPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ManualScalingPtrOutput() GoogleCloudMlV1__ManualScalingPtrOutput
	ToGoogleCloudMlV1__ManualScalingPtrOutputWithContext(context.Context) GoogleCloudMlV1__ManualScalingPtrOutput
}

GoogleCloudMlV1__ManualScalingPtrInput is an input type that accepts GoogleCloudMlV1__ManualScalingArgs, GoogleCloudMlV1__ManualScalingPtr and GoogleCloudMlV1__ManualScalingPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ManualScalingPtrInput` via: 

        GoogleCloudMlV1__ManualScalingArgs{...}

or:

        nil

func GoogleCloudMlV1__ManualScalingPtr 

func GoogleCloudMlV1__ManualScalingPtr(v *GoogleCloudMlV1__ManualScalingArgs) GoogleCloudMlV1__ManualScalingPtrInput

type GoogleCloudMlV1__ManualScalingPtrOutput 

type GoogleCloudMlV1__ManualScalingPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ManualScalingPtrOutput) Elem 

func (o GoogleCloudMlV1__ManualScalingPtrOutput) Elem() GoogleCloudMlV1__ManualScalingOutput

func (GoogleCloudMlV1__ManualScalingPtrOutput) ElementType 

func (GoogleCloudMlV1__ManualScalingPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ManualScalingPtrOutput) Nodes 

func (o GoogleCloudMlV1__ManualScalingPtrOutput) Nodes() pulumi.IntPtrOutput

The number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed, so the cost of operating this model will be proportional to `nodes` * number of hours since last billing cycle plus the cost for each prediction performed.

func (GoogleCloudMlV1__ManualScalingPtrOutput) ToGoogleCloudMlV1__ManualScalingPtrOutput 

func (o GoogleCloudMlV1__ManualScalingPtrOutput) ToGoogleCloudMlV1__ManualScalingPtrOutput() GoogleCloudMlV1__ManualScalingPtrOutput

func (GoogleCloudMlV1__ManualScalingPtrOutput) ToGoogleCloudMlV1__ManualScalingPtrOutputWithContext 

func (o GoogleCloudMlV1__ManualScalingPtrOutput) ToGoogleCloudMlV1__ManualScalingPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ManualScalingPtrOutput

type GoogleCloudMlV1__ManualScalingResponse 

type GoogleCloudMlV1__ManualScalingResponse struct {
	// The number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed, so the cost of operating this model will be proportional to `nodes` * number of hours since last billing cycle plus the cost for each prediction performed.
	Nodes int `pulumi:"nodes"`
}

Options for manually scaling a model.

type GoogleCloudMlV1__ManualScalingResponseOutput 

type GoogleCloudMlV1__ManualScalingResponseOutput struct{ *pulumi.OutputState }

Options for manually scaling a model.

func (GoogleCloudMlV1__ManualScalingResponseOutput) ElementType 

func (GoogleCloudMlV1__ManualScalingResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ManualScalingResponseOutput) Nodes 

func (o GoogleCloudMlV1__ManualScalingResponseOutput) Nodes() pulumi.IntOutput

The number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed, so the cost of operating this model will be proportional to `nodes` * number of hours since last billing cycle plus the cost for each prediction performed.

func (GoogleCloudMlV1__ManualScalingResponseOutput) ToGoogleCloudMlV1__ManualScalingResponseOutput 

func (o GoogleCloudMlV1__ManualScalingResponseOutput) ToGoogleCloudMlV1__ManualScalingResponseOutput() GoogleCloudMlV1__ManualScalingResponseOutput

func (GoogleCloudMlV1__ManualScalingResponseOutput) ToGoogleCloudMlV1__ManualScalingResponseOutputWithContext 

func (o GoogleCloudMlV1__ManualScalingResponseOutput) ToGoogleCloudMlV1__ManualScalingResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__ManualScalingResponseOutput

type GoogleCloudMlV1__Measurement 

type GoogleCloudMlV1__Measurement struct {
	// Provides a list of metrics that act as inputs into the objective function.
	Metrics []GoogleCloudMlV1_Measurement_Metric `pulumi:"metrics"`
	// The number of steps a machine learning model has been trained for. Must be non-negative.
	StepCount *string `pulumi:"stepCount"`
}

A message representing a measurement.

type GoogleCloudMlV1__MeasurementArgs 

type GoogleCloudMlV1__MeasurementArgs struct {
	// Provides a list of metrics that act as inputs into the objective function.
	Metrics GoogleCloudMlV1_Measurement_MetricArrayInput `pulumi:"metrics"`
	// The number of steps a machine learning model has been trained for. Must be non-negative.
	StepCount pulumi.StringPtrInput `pulumi:"stepCount"`
}

A message representing a measurement.

func (GoogleCloudMlV1__MeasurementArgs) ElementType 

func (GoogleCloudMlV1__MeasurementArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__MeasurementArgs) ToGoogleCloudMlV1__MeasurementOutput 

func (i GoogleCloudMlV1__MeasurementArgs) ToGoogleCloudMlV1__MeasurementOutput() GoogleCloudMlV1__MeasurementOutput

func (GoogleCloudMlV1__MeasurementArgs) ToGoogleCloudMlV1__MeasurementOutputWithContext 

func (i GoogleCloudMlV1__MeasurementArgs) ToGoogleCloudMlV1__MeasurementOutputWithContext(ctx context.Context) GoogleCloudMlV1__MeasurementOutput

func (GoogleCloudMlV1__MeasurementArgs) ToGoogleCloudMlV1__MeasurementPtrOutput 

func (i GoogleCloudMlV1__MeasurementArgs) ToGoogleCloudMlV1__MeasurementPtrOutput() GoogleCloudMlV1__MeasurementPtrOutput

func (GoogleCloudMlV1__MeasurementArgs) ToGoogleCloudMlV1__MeasurementPtrOutputWithContext 

func (i GoogleCloudMlV1__MeasurementArgs) ToGoogleCloudMlV1__MeasurementPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__MeasurementPtrOutput

type GoogleCloudMlV1__MeasurementArray 

type GoogleCloudMlV1__MeasurementArray []GoogleCloudMlV1__MeasurementInput

func (GoogleCloudMlV1__MeasurementArray) ElementType 

func (GoogleCloudMlV1__MeasurementArray) ElementType() reflect.Type

func (GoogleCloudMlV1__MeasurementArray) ToGoogleCloudMlV1__MeasurementArrayOutput 

func (i GoogleCloudMlV1__MeasurementArray) ToGoogleCloudMlV1__MeasurementArrayOutput() GoogleCloudMlV1__MeasurementArrayOutput

func (GoogleCloudMlV1__MeasurementArray) ToGoogleCloudMlV1__MeasurementArrayOutputWithContext 

func (i GoogleCloudMlV1__MeasurementArray) ToGoogleCloudMlV1__MeasurementArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__MeasurementArrayOutput

type GoogleCloudMlV1__MeasurementArrayInput 

type GoogleCloudMlV1__MeasurementArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__MeasurementArrayOutput() GoogleCloudMlV1__MeasurementArrayOutput
	ToGoogleCloudMlV1__MeasurementArrayOutputWithContext(context.Context) GoogleCloudMlV1__MeasurementArrayOutput
}

GoogleCloudMlV1__MeasurementArrayInput is an input type that accepts GoogleCloudMlV1__MeasurementArray and GoogleCloudMlV1__MeasurementArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1__MeasurementArrayInput` via: 

GoogleCloudMlV1__MeasurementArray{ GoogleCloudMlV1__MeasurementArgs{...} }

type GoogleCloudMlV1__MeasurementArrayOutput 

type GoogleCloudMlV1__MeasurementArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__MeasurementArrayOutput) ElementType 

func (GoogleCloudMlV1__MeasurementArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MeasurementArrayOutput) Index 

func (o GoogleCloudMlV1__MeasurementArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__MeasurementOutput

func (GoogleCloudMlV1__MeasurementArrayOutput) ToGoogleCloudMlV1__MeasurementArrayOutput 

func (o GoogleCloudMlV1__MeasurementArrayOutput) ToGoogleCloudMlV1__MeasurementArrayOutput() GoogleCloudMlV1__MeasurementArrayOutput

func (GoogleCloudMlV1__MeasurementArrayOutput) ToGoogleCloudMlV1__MeasurementArrayOutputWithContext 

func (o GoogleCloudMlV1__MeasurementArrayOutput) ToGoogleCloudMlV1__MeasurementArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__MeasurementArrayOutput

type GoogleCloudMlV1__MeasurementInput 

type GoogleCloudMlV1__MeasurementInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__MeasurementOutput() GoogleCloudMlV1__MeasurementOutput
	ToGoogleCloudMlV1__MeasurementOutputWithContext(context.Context) GoogleCloudMlV1__MeasurementOutput
}

GoogleCloudMlV1__MeasurementInput is an input type that accepts GoogleCloudMlV1__MeasurementArgs and GoogleCloudMlV1__MeasurementOutput values. You can construct a concrete instance of `GoogleCloudMlV1__MeasurementInput` via: 

GoogleCloudMlV1__MeasurementArgs{...}

type GoogleCloudMlV1__MeasurementOutput 

type GoogleCloudMlV1__MeasurementOutput struct{ *pulumi.OutputState }

A message representing a measurement.

func (GoogleCloudMlV1__MeasurementOutput) ElementType 

func (GoogleCloudMlV1__MeasurementOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MeasurementOutput) Metrics 

func (o GoogleCloudMlV1__MeasurementOutput) Metrics() GoogleCloudMlV1_Measurement_MetricArrayOutput

Provides a list of metrics that act as inputs into the objective function.

func (GoogleCloudMlV1__MeasurementOutput) StepCount 

func (o GoogleCloudMlV1__MeasurementOutput) StepCount() pulumi.StringPtrOutput

The number of steps a machine learning model has been trained for. Must be non-negative.

func (GoogleCloudMlV1__MeasurementOutput) ToGoogleCloudMlV1__MeasurementOutput 

func (o GoogleCloudMlV1__MeasurementOutput) ToGoogleCloudMlV1__MeasurementOutput() GoogleCloudMlV1__MeasurementOutput

func (GoogleCloudMlV1__MeasurementOutput) ToGoogleCloudMlV1__MeasurementOutputWithContext 

func (o GoogleCloudMlV1__MeasurementOutput) ToGoogleCloudMlV1__MeasurementOutputWithContext(ctx context.Context) GoogleCloudMlV1__MeasurementOutput

func (GoogleCloudMlV1__MeasurementOutput) ToGoogleCloudMlV1__MeasurementPtrOutput 

func (o GoogleCloudMlV1__MeasurementOutput) ToGoogleCloudMlV1__MeasurementPtrOutput() GoogleCloudMlV1__MeasurementPtrOutput

func (GoogleCloudMlV1__MeasurementOutput) ToGoogleCloudMlV1__MeasurementPtrOutputWithContext 

func (o GoogleCloudMlV1__MeasurementOutput) ToGoogleCloudMlV1__MeasurementPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__MeasurementPtrOutput

type GoogleCloudMlV1__MeasurementPtrInput 

type GoogleCloudMlV1__MeasurementPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__MeasurementPtrOutput() GoogleCloudMlV1__MeasurementPtrOutput
	ToGoogleCloudMlV1__MeasurementPtrOutputWithContext(context.Context) GoogleCloudMlV1__MeasurementPtrOutput
}

GoogleCloudMlV1__MeasurementPtrInput is an input type that accepts GoogleCloudMlV1__MeasurementArgs, GoogleCloudMlV1__MeasurementPtr and GoogleCloudMlV1__MeasurementPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__MeasurementPtrInput` via: 

        GoogleCloudMlV1__MeasurementArgs{...}

or:

        nil

func GoogleCloudMlV1__MeasurementPtr 

func GoogleCloudMlV1__MeasurementPtr(v *GoogleCloudMlV1__MeasurementArgs) GoogleCloudMlV1__MeasurementPtrInput

type GoogleCloudMlV1__MeasurementPtrOutput 

type GoogleCloudMlV1__MeasurementPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__MeasurementPtrOutput) Elem 

func (o GoogleCloudMlV1__MeasurementPtrOutput) Elem() GoogleCloudMlV1__MeasurementOutput

func (GoogleCloudMlV1__MeasurementPtrOutput) ElementType 

func (GoogleCloudMlV1__MeasurementPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MeasurementPtrOutput) Metrics 

func (o GoogleCloudMlV1__MeasurementPtrOutput) Metrics() GoogleCloudMlV1_Measurement_MetricArrayOutput

Provides a list of metrics that act as inputs into the objective function.

func (GoogleCloudMlV1__MeasurementPtrOutput) StepCount 

func (o GoogleCloudMlV1__MeasurementPtrOutput) StepCount() pulumi.StringPtrOutput

The number of steps a machine learning model has been trained for. Must be non-negative.

func (GoogleCloudMlV1__MeasurementPtrOutput) ToGoogleCloudMlV1__MeasurementPtrOutput 

func (o GoogleCloudMlV1__MeasurementPtrOutput) ToGoogleCloudMlV1__MeasurementPtrOutput() GoogleCloudMlV1__MeasurementPtrOutput

func (GoogleCloudMlV1__MeasurementPtrOutput) ToGoogleCloudMlV1__MeasurementPtrOutputWithContext 

func (o GoogleCloudMlV1__MeasurementPtrOutput) ToGoogleCloudMlV1__MeasurementPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__MeasurementPtrOutput

type GoogleCloudMlV1__MeasurementResponse 

type GoogleCloudMlV1__MeasurementResponse struct {
	// Time that the trial has been running at the point of this measurement.
	ElapsedTime string `pulumi:"elapsedTime"`
	// Provides a list of metrics that act as inputs into the objective function.
	Metrics []GoogleCloudMlV1_Measurement_MetricResponse `pulumi:"metrics"`
	// The number of steps a machine learning model has been trained for. Must be non-negative.
	StepCount string `pulumi:"stepCount"`
}

A message representing a measurement.

type GoogleCloudMlV1__MeasurementResponseArrayOutput 

type GoogleCloudMlV1__MeasurementResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__MeasurementResponseArrayOutput) ElementType 

func (GoogleCloudMlV1__MeasurementResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MeasurementResponseArrayOutput) Index 

func (o GoogleCloudMlV1__MeasurementResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__MeasurementResponseOutput

func (GoogleCloudMlV1__MeasurementResponseArrayOutput) ToGoogleCloudMlV1__MeasurementResponseArrayOutput 

func (o GoogleCloudMlV1__MeasurementResponseArrayOutput) ToGoogleCloudMlV1__MeasurementResponseArrayOutput() GoogleCloudMlV1__MeasurementResponseArrayOutput

func (GoogleCloudMlV1__MeasurementResponseArrayOutput) ToGoogleCloudMlV1__MeasurementResponseArrayOutputWithContext 

func (o GoogleCloudMlV1__MeasurementResponseArrayOutput) ToGoogleCloudMlV1__MeasurementResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__MeasurementResponseArrayOutput

type GoogleCloudMlV1__MeasurementResponseOutput 

type GoogleCloudMlV1__MeasurementResponseOutput struct{ *pulumi.OutputState }

A message representing a measurement.

func (GoogleCloudMlV1__MeasurementResponseOutput) ElapsedTime 

func (o GoogleCloudMlV1__MeasurementResponseOutput) ElapsedTime() pulumi.StringOutput

Time that the trial has been running at the point of this measurement.

func (GoogleCloudMlV1__MeasurementResponseOutput) ElementType 

func (GoogleCloudMlV1__MeasurementResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MeasurementResponseOutput) Metrics 

func (o GoogleCloudMlV1__MeasurementResponseOutput) Metrics() GoogleCloudMlV1_Measurement_MetricResponseArrayOutput

Provides a list of metrics that act as inputs into the objective function.

func (GoogleCloudMlV1__MeasurementResponseOutput) StepCount 

func (o GoogleCloudMlV1__MeasurementResponseOutput) StepCount() pulumi.StringOutput

The number of steps a machine learning model has been trained for. Must be non-negative.

func (GoogleCloudMlV1__MeasurementResponseOutput) ToGoogleCloudMlV1__MeasurementResponseOutput 

func (o GoogleCloudMlV1__MeasurementResponseOutput) ToGoogleCloudMlV1__MeasurementResponseOutput() GoogleCloudMlV1__MeasurementResponseOutput

func (GoogleCloudMlV1__MeasurementResponseOutput) ToGoogleCloudMlV1__MeasurementResponseOutputWithContext 

func (o GoogleCloudMlV1__MeasurementResponseOutput) ToGoogleCloudMlV1__MeasurementResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__MeasurementResponseOutput

type GoogleCloudMlV1__MetricSpec 

type GoogleCloudMlV1__MetricSpec struct {
	// metric name.
	Name *GoogleCloudMlV1__MetricSpecName `pulumi:"name"`
	// Target specifies the target value for the given metric; once real metric deviates from the threshold by a certain percentage, the node count changes.
	Target *int `pulumi:"target"`
}

MetricSpec contains the specifications to use to calculate the desired nodes count when autoscaling is enabled.

type GoogleCloudMlV1__MetricSpecArgs 

type GoogleCloudMlV1__MetricSpecArgs struct {
	// metric name.
	Name GoogleCloudMlV1__MetricSpecNamePtrInput `pulumi:"name"`
	// Target specifies the target value for the given metric; once real metric deviates from the threshold by a certain percentage, the node count changes.
	Target pulumi.IntPtrInput `pulumi:"target"`
}

MetricSpec contains the specifications to use to calculate the desired nodes count when autoscaling is enabled.

func (GoogleCloudMlV1__MetricSpecArgs) ElementType 

func (GoogleCloudMlV1__MetricSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__MetricSpecArgs) ToGoogleCloudMlV1__MetricSpecOutput 

func (i GoogleCloudMlV1__MetricSpecArgs) ToGoogleCloudMlV1__MetricSpecOutput() GoogleCloudMlV1__MetricSpecOutput

func (GoogleCloudMlV1__MetricSpecArgs) ToGoogleCloudMlV1__MetricSpecOutputWithContext 

func (i GoogleCloudMlV1__MetricSpecArgs) ToGoogleCloudMlV1__MetricSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecOutput

type GoogleCloudMlV1__MetricSpecArray 

type GoogleCloudMlV1__MetricSpecArray []GoogleCloudMlV1__MetricSpecInput

func (GoogleCloudMlV1__MetricSpecArray) ElementType 

func (GoogleCloudMlV1__MetricSpecArray) ElementType() reflect.Type

func (GoogleCloudMlV1__MetricSpecArray) ToGoogleCloudMlV1__MetricSpecArrayOutput 

func (i GoogleCloudMlV1__MetricSpecArray) ToGoogleCloudMlV1__MetricSpecArrayOutput() GoogleCloudMlV1__MetricSpecArrayOutput

func (GoogleCloudMlV1__MetricSpecArray) ToGoogleCloudMlV1__MetricSpecArrayOutputWithContext 

func (i GoogleCloudMlV1__MetricSpecArray) ToGoogleCloudMlV1__MetricSpecArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecArrayOutput

type GoogleCloudMlV1__MetricSpecArrayInput 

type GoogleCloudMlV1__MetricSpecArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__MetricSpecArrayOutput() GoogleCloudMlV1__MetricSpecArrayOutput
	ToGoogleCloudMlV1__MetricSpecArrayOutputWithContext(context.Context) GoogleCloudMlV1__MetricSpecArrayOutput
}

GoogleCloudMlV1__MetricSpecArrayInput is an input type that accepts GoogleCloudMlV1__MetricSpecArray and GoogleCloudMlV1__MetricSpecArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1__MetricSpecArrayInput` via: 

GoogleCloudMlV1__MetricSpecArray{ GoogleCloudMlV1__MetricSpecArgs{...} }

type GoogleCloudMlV1__MetricSpecArrayOutput 

type GoogleCloudMlV1__MetricSpecArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__MetricSpecArrayOutput) ElementType 

func (GoogleCloudMlV1__MetricSpecArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MetricSpecArrayOutput) Index 

func (o GoogleCloudMlV1__MetricSpecArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__MetricSpecOutput

func (GoogleCloudMlV1__MetricSpecArrayOutput) ToGoogleCloudMlV1__MetricSpecArrayOutput 

func (o GoogleCloudMlV1__MetricSpecArrayOutput) ToGoogleCloudMlV1__MetricSpecArrayOutput() GoogleCloudMlV1__MetricSpecArrayOutput

func (GoogleCloudMlV1__MetricSpecArrayOutput) ToGoogleCloudMlV1__MetricSpecArrayOutputWithContext 

func (o GoogleCloudMlV1__MetricSpecArrayOutput) ToGoogleCloudMlV1__MetricSpecArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecArrayOutput

type GoogleCloudMlV1__MetricSpecInput 

type GoogleCloudMlV1__MetricSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__MetricSpecOutput() GoogleCloudMlV1__MetricSpecOutput
	ToGoogleCloudMlV1__MetricSpecOutputWithContext(context.Context) GoogleCloudMlV1__MetricSpecOutput
}

GoogleCloudMlV1__MetricSpecInput is an input type that accepts GoogleCloudMlV1__MetricSpecArgs and GoogleCloudMlV1__MetricSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1__MetricSpecInput` via: 

GoogleCloudMlV1__MetricSpecArgs{...}

type GoogleCloudMlV1__MetricSpecName added in v0.4.0 

type GoogleCloudMlV1__MetricSpecName string

metric name.

func (GoogleCloudMlV1__MetricSpecName) ElementType added in v0.4.0 

func (GoogleCloudMlV1__MetricSpecName) ElementType() reflect.Type

func (GoogleCloudMlV1__MetricSpecName) ToGoogleCloudMlV1__MetricSpecNameOutput added in v0.6.0 

func (e GoogleCloudMlV1__MetricSpecName) ToGoogleCloudMlV1__MetricSpecNameOutput() GoogleCloudMlV1__MetricSpecNameOutput

func (GoogleCloudMlV1__MetricSpecName) ToGoogleCloudMlV1__MetricSpecNameOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__MetricSpecName) ToGoogleCloudMlV1__MetricSpecNameOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecNameOutput

func (GoogleCloudMlV1__MetricSpecName) ToGoogleCloudMlV1__MetricSpecNamePtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__MetricSpecName) ToGoogleCloudMlV1__MetricSpecNamePtrOutput() GoogleCloudMlV1__MetricSpecNamePtrOutput

func (GoogleCloudMlV1__MetricSpecName) ToGoogleCloudMlV1__MetricSpecNamePtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__MetricSpecName) ToGoogleCloudMlV1__MetricSpecNamePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecNamePtrOutput

func (GoogleCloudMlV1__MetricSpecName) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__MetricSpecName) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__MetricSpecName) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__MetricSpecName) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__MetricSpecName) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__MetricSpecName) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__MetricSpecName) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__MetricSpecName) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__MetricSpecNameInput added in v0.6.0 

type GoogleCloudMlV1__MetricSpecNameInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__MetricSpecNameOutput() GoogleCloudMlV1__MetricSpecNameOutput
	ToGoogleCloudMlV1__MetricSpecNameOutputWithContext(context.Context) GoogleCloudMlV1__MetricSpecNameOutput
}

GoogleCloudMlV1__MetricSpecNameInput is an input type that accepts GoogleCloudMlV1__MetricSpecNameArgs and GoogleCloudMlV1__MetricSpecNameOutput values. You can construct a concrete instance of `GoogleCloudMlV1__MetricSpecNameInput` via: 

GoogleCloudMlV1__MetricSpecNameArgs{...}

type GoogleCloudMlV1__MetricSpecNameOutput added in v0.6.0 

type GoogleCloudMlV1__MetricSpecNameOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__MetricSpecNameOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__MetricSpecNameOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MetricSpecNameOutput) ToGoogleCloudMlV1__MetricSpecNameOutput added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNameOutput) ToGoogleCloudMlV1__MetricSpecNameOutput() GoogleCloudMlV1__MetricSpecNameOutput

func (GoogleCloudMlV1__MetricSpecNameOutput) ToGoogleCloudMlV1__MetricSpecNameOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNameOutput) ToGoogleCloudMlV1__MetricSpecNameOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecNameOutput

func (GoogleCloudMlV1__MetricSpecNameOutput) ToGoogleCloudMlV1__MetricSpecNamePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNameOutput) ToGoogleCloudMlV1__MetricSpecNamePtrOutput() GoogleCloudMlV1__MetricSpecNamePtrOutput

func (GoogleCloudMlV1__MetricSpecNameOutput) ToGoogleCloudMlV1__MetricSpecNamePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNameOutput) ToGoogleCloudMlV1__MetricSpecNamePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecNamePtrOutput

func (GoogleCloudMlV1__MetricSpecNameOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNameOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__MetricSpecNameOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNameOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__MetricSpecNameOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNameOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__MetricSpecNameOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNameOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__MetricSpecNamePtrInput added in v0.6.0 

type GoogleCloudMlV1__MetricSpecNamePtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__MetricSpecNamePtrOutput() GoogleCloudMlV1__MetricSpecNamePtrOutput
	ToGoogleCloudMlV1__MetricSpecNamePtrOutputWithContext(context.Context) GoogleCloudMlV1__MetricSpecNamePtrOutput
}

func GoogleCloudMlV1__MetricSpecNamePtr added in v0.6.0 

func GoogleCloudMlV1__MetricSpecNamePtr(v string) GoogleCloudMlV1__MetricSpecNamePtrInput

type GoogleCloudMlV1__MetricSpecNamePtrOutput added in v0.6.0 

type GoogleCloudMlV1__MetricSpecNamePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__MetricSpecNamePtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNamePtrOutput) Elem() GoogleCloudMlV1__MetricSpecNameOutput

func (GoogleCloudMlV1__MetricSpecNamePtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__MetricSpecNamePtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MetricSpecNamePtrOutput) ToGoogleCloudMlV1__MetricSpecNamePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNamePtrOutput) ToGoogleCloudMlV1__MetricSpecNamePtrOutput() GoogleCloudMlV1__MetricSpecNamePtrOutput

func (GoogleCloudMlV1__MetricSpecNamePtrOutput) ToGoogleCloudMlV1__MetricSpecNamePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNamePtrOutput) ToGoogleCloudMlV1__MetricSpecNamePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecNamePtrOutput

func (GoogleCloudMlV1__MetricSpecNamePtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNamePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__MetricSpecNamePtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__MetricSpecNamePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__MetricSpecOutput 

type GoogleCloudMlV1__MetricSpecOutput struct{ *pulumi.OutputState }

MetricSpec contains the specifications to use to calculate the desired nodes count when autoscaling is enabled.

func (GoogleCloudMlV1__MetricSpecOutput) ElementType 

func (GoogleCloudMlV1__MetricSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MetricSpecOutput) Name 

func (o GoogleCloudMlV1__MetricSpecOutput) Name() GoogleCloudMlV1__MetricSpecNamePtrOutput

metric name.

func (GoogleCloudMlV1__MetricSpecOutput) Target 

func (o GoogleCloudMlV1__MetricSpecOutput) Target() pulumi.IntPtrOutput

Target specifies the target value for the given metric; once real metric deviates from the threshold by a certain percentage, the node count changes.

func (GoogleCloudMlV1__MetricSpecOutput) ToGoogleCloudMlV1__MetricSpecOutput 

func (o GoogleCloudMlV1__MetricSpecOutput) ToGoogleCloudMlV1__MetricSpecOutput() GoogleCloudMlV1__MetricSpecOutput

func (GoogleCloudMlV1__MetricSpecOutput) ToGoogleCloudMlV1__MetricSpecOutputWithContext 

func (o GoogleCloudMlV1__MetricSpecOutput) ToGoogleCloudMlV1__MetricSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecOutput

type GoogleCloudMlV1__MetricSpecResponse 

type GoogleCloudMlV1__MetricSpecResponse struct {
	// metric name.
	Name string `pulumi:"name"`
	// Target specifies the target value for the given metric; once real metric deviates from the threshold by a certain percentage, the node count changes.
	Target int `pulumi:"target"`
}

MetricSpec contains the specifications to use to calculate the desired nodes count when autoscaling is enabled.

type GoogleCloudMlV1__MetricSpecResponseArrayOutput 

type GoogleCloudMlV1__MetricSpecResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__MetricSpecResponseArrayOutput) ElementType 

func (GoogleCloudMlV1__MetricSpecResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MetricSpecResponseArrayOutput) Index 

func (o GoogleCloudMlV1__MetricSpecResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__MetricSpecResponseOutput

func (GoogleCloudMlV1__MetricSpecResponseArrayOutput) ToGoogleCloudMlV1__MetricSpecResponseArrayOutput 

func (o GoogleCloudMlV1__MetricSpecResponseArrayOutput) ToGoogleCloudMlV1__MetricSpecResponseArrayOutput() GoogleCloudMlV1__MetricSpecResponseArrayOutput

func (GoogleCloudMlV1__MetricSpecResponseArrayOutput) ToGoogleCloudMlV1__MetricSpecResponseArrayOutputWithContext 

func (o GoogleCloudMlV1__MetricSpecResponseArrayOutput) ToGoogleCloudMlV1__MetricSpecResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecResponseArrayOutput

type GoogleCloudMlV1__MetricSpecResponseOutput 

type GoogleCloudMlV1__MetricSpecResponseOutput struct{ *pulumi.OutputState }

MetricSpec contains the specifications to use to calculate the desired nodes count when autoscaling is enabled.

func (GoogleCloudMlV1__MetricSpecResponseOutput) ElementType 

func (GoogleCloudMlV1__MetricSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__MetricSpecResponseOutput) Name 

func (o GoogleCloudMlV1__MetricSpecResponseOutput) Name() pulumi.StringOutput

metric name.

func (GoogleCloudMlV1__MetricSpecResponseOutput) Target 

func (o GoogleCloudMlV1__MetricSpecResponseOutput) Target() pulumi.IntOutput

Target specifies the target value for the given metric; once real metric deviates from the threshold by a certain percentage, the node count changes.

func (GoogleCloudMlV1__MetricSpecResponseOutput) ToGoogleCloudMlV1__MetricSpecResponseOutput 

func (o GoogleCloudMlV1__MetricSpecResponseOutput) ToGoogleCloudMlV1__MetricSpecResponseOutput() GoogleCloudMlV1__MetricSpecResponseOutput

func (GoogleCloudMlV1__MetricSpecResponseOutput) ToGoogleCloudMlV1__MetricSpecResponseOutputWithContext 

func (o GoogleCloudMlV1__MetricSpecResponseOutput) ToGoogleCloudMlV1__MetricSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__MetricSpecResponseOutput

type GoogleCloudMlV1__ParameterSpec 

type GoogleCloudMlV1__ParameterSpec struct {
	// Required if type is `CATEGORICAL`. The list of possible categories.
	CategoricalValues []string `pulumi:"categoricalValues"`
	// Required if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
	DiscreteValues []float64 `pulumi:"discreteValues"`
	// Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is `INTEGER`.
	MaxValue *float64 `pulumi:"maxValue"`
	// Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is INTEGER.
	MinValue *float64 `pulumi:"minValue"`
	// The parameter name must be unique amongst all ParameterConfigs in a HyperparameterSpec message. E.g., "learning_rate".
	ParameterName string `pulumi:"parameterName"`
	// Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., `UNIT_LINEAR_SCALE`).
	ScaleType *GoogleCloudMlV1__ParameterSpecScaleType `pulumi:"scaleType"`
	// The type of the parameter.
	Type GoogleCloudMlV1__ParameterSpecType `pulumi:"type"`
}

Represents a single hyperparameter to optimize.

type GoogleCloudMlV1__ParameterSpecArgs 

type GoogleCloudMlV1__ParameterSpecArgs struct {
	// Required if type is `CATEGORICAL`. The list of possible categories.
	CategoricalValues pulumi.StringArrayInput `pulumi:"categoricalValues"`
	// Required if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
	DiscreteValues pulumi.Float64ArrayInput `pulumi:"discreteValues"`
	// Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is `INTEGER`.
	MaxValue pulumi.Float64PtrInput `pulumi:"maxValue"`
	// Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is INTEGER.
	MinValue pulumi.Float64PtrInput `pulumi:"minValue"`
	// The parameter name must be unique amongst all ParameterConfigs in a HyperparameterSpec message. E.g., "learning_rate".
	ParameterName pulumi.StringInput `pulumi:"parameterName"`
	// Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., `UNIT_LINEAR_SCALE`).
	ScaleType GoogleCloudMlV1__ParameterSpecScaleTypePtrInput `pulumi:"scaleType"`
	// The type of the parameter.
	Type GoogleCloudMlV1__ParameterSpecTypeInput `pulumi:"type"`
}

Represents a single hyperparameter to optimize.

func (GoogleCloudMlV1__ParameterSpecArgs) ElementType 

func (GoogleCloudMlV1__ParameterSpecArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecArgs) ToGoogleCloudMlV1__ParameterSpecOutput 

func (i GoogleCloudMlV1__ParameterSpecArgs) ToGoogleCloudMlV1__ParameterSpecOutput() GoogleCloudMlV1__ParameterSpecOutput

func (GoogleCloudMlV1__ParameterSpecArgs) ToGoogleCloudMlV1__ParameterSpecOutputWithContext 

func (i GoogleCloudMlV1__ParameterSpecArgs) ToGoogleCloudMlV1__ParameterSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecOutput

type GoogleCloudMlV1__ParameterSpecArray 

type GoogleCloudMlV1__ParameterSpecArray []GoogleCloudMlV1__ParameterSpecInput

func (GoogleCloudMlV1__ParameterSpecArray) ElementType 

func (GoogleCloudMlV1__ParameterSpecArray) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecArray) ToGoogleCloudMlV1__ParameterSpecArrayOutput 

func (i GoogleCloudMlV1__ParameterSpecArray) ToGoogleCloudMlV1__ParameterSpecArrayOutput() GoogleCloudMlV1__ParameterSpecArrayOutput

func (GoogleCloudMlV1__ParameterSpecArray) ToGoogleCloudMlV1__ParameterSpecArrayOutputWithContext 

func (i GoogleCloudMlV1__ParameterSpecArray) ToGoogleCloudMlV1__ParameterSpecArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecArrayOutput

type GoogleCloudMlV1__ParameterSpecArrayInput 

type GoogleCloudMlV1__ParameterSpecArrayInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ParameterSpecArrayOutput() GoogleCloudMlV1__ParameterSpecArrayOutput
	ToGoogleCloudMlV1__ParameterSpecArrayOutputWithContext(context.Context) GoogleCloudMlV1__ParameterSpecArrayOutput
}

GoogleCloudMlV1__ParameterSpecArrayInput is an input type that accepts GoogleCloudMlV1__ParameterSpecArray and GoogleCloudMlV1__ParameterSpecArrayOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ParameterSpecArrayInput` via: 

GoogleCloudMlV1__ParameterSpecArray{ GoogleCloudMlV1__ParameterSpecArgs{...} }

type GoogleCloudMlV1__ParameterSpecArrayOutput 

type GoogleCloudMlV1__ParameterSpecArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ParameterSpecArrayOutput) ElementType 

func (GoogleCloudMlV1__ParameterSpecArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecArrayOutput) Index 

func (o GoogleCloudMlV1__ParameterSpecArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__ParameterSpecOutput

func (GoogleCloudMlV1__ParameterSpecArrayOutput) ToGoogleCloudMlV1__ParameterSpecArrayOutput 

func (o GoogleCloudMlV1__ParameterSpecArrayOutput) ToGoogleCloudMlV1__ParameterSpecArrayOutput() GoogleCloudMlV1__ParameterSpecArrayOutput

func (GoogleCloudMlV1__ParameterSpecArrayOutput) ToGoogleCloudMlV1__ParameterSpecArrayOutputWithContext 

func (o GoogleCloudMlV1__ParameterSpecArrayOutput) ToGoogleCloudMlV1__ParameterSpecArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecArrayOutput

type GoogleCloudMlV1__ParameterSpecInput 

type GoogleCloudMlV1__ParameterSpecInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ParameterSpecOutput() GoogleCloudMlV1__ParameterSpecOutput
	ToGoogleCloudMlV1__ParameterSpecOutputWithContext(context.Context) GoogleCloudMlV1__ParameterSpecOutput
}

GoogleCloudMlV1__ParameterSpecInput is an input type that accepts GoogleCloudMlV1__ParameterSpecArgs and GoogleCloudMlV1__ParameterSpecOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ParameterSpecInput` via: 

GoogleCloudMlV1__ParameterSpecArgs{...}

type GoogleCloudMlV1__ParameterSpecOutput 

type GoogleCloudMlV1__ParameterSpecOutput struct{ *pulumi.OutputState }

Represents a single hyperparameter to optimize.

func (GoogleCloudMlV1__ParameterSpecOutput) CategoricalValues 

func (o GoogleCloudMlV1__ParameterSpecOutput) CategoricalValues() pulumi.StringArrayOutput

Required if type is `CATEGORICAL`. The list of possible categories.

func (GoogleCloudMlV1__ParameterSpecOutput) DiscreteValues 

func (o GoogleCloudMlV1__ParameterSpecOutput) DiscreteValues() pulumi.Float64ArrayOutput

Required if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

func (GoogleCloudMlV1__ParameterSpecOutput) ElementType 

func (GoogleCloudMlV1__ParameterSpecOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecOutput) MaxValue 

func (o GoogleCloudMlV1__ParameterSpecOutput) MaxValue() pulumi.Float64PtrOutput

Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is `INTEGER`.

func (GoogleCloudMlV1__ParameterSpecOutput) MinValue 

func (o GoogleCloudMlV1__ParameterSpecOutput) MinValue() pulumi.Float64PtrOutput

Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is INTEGER.

func (GoogleCloudMlV1__ParameterSpecOutput) ParameterName 

func (o GoogleCloudMlV1__ParameterSpecOutput) ParameterName() pulumi.StringOutput

The parameter name must be unique amongst all ParameterConfigs in a HyperparameterSpec message. E.g., "learning_rate".

func (GoogleCloudMlV1__ParameterSpecOutput) ScaleType 

func (o GoogleCloudMlV1__ParameterSpecOutput) ScaleType() GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput

Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., `UNIT_LINEAR_SCALE`).

func (GoogleCloudMlV1__ParameterSpecOutput) ToGoogleCloudMlV1__ParameterSpecOutput 

func (o GoogleCloudMlV1__ParameterSpecOutput) ToGoogleCloudMlV1__ParameterSpecOutput() GoogleCloudMlV1__ParameterSpecOutput

func (GoogleCloudMlV1__ParameterSpecOutput) ToGoogleCloudMlV1__ParameterSpecOutputWithContext 

func (o GoogleCloudMlV1__ParameterSpecOutput) ToGoogleCloudMlV1__ParameterSpecOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecOutput

func (GoogleCloudMlV1__ParameterSpecOutput) Type 

func (o GoogleCloudMlV1__ParameterSpecOutput) Type() GoogleCloudMlV1__ParameterSpecTypeOutput

The type of the parameter.

type GoogleCloudMlV1__ParameterSpecResponse 

type GoogleCloudMlV1__ParameterSpecResponse struct {
	// Required if type is `CATEGORICAL`. The list of possible categories.
	CategoricalValues []string `pulumi:"categoricalValues"`
	// Required if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
	DiscreteValues []float64 `pulumi:"discreteValues"`
	// Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is `INTEGER`.
	MaxValue float64 `pulumi:"maxValue"`
	// Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is INTEGER.
	MinValue float64 `pulumi:"minValue"`
	// The parameter name must be unique amongst all ParameterConfigs in a HyperparameterSpec message. E.g., "learning_rate".
	ParameterName string `pulumi:"parameterName"`
	// Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., `UNIT_LINEAR_SCALE`).
	ScaleType string `pulumi:"scaleType"`
	// The type of the parameter.
	Type string `pulumi:"type"`
}

Represents a single hyperparameter to optimize.

type GoogleCloudMlV1__ParameterSpecResponseArrayOutput 

type GoogleCloudMlV1__ParameterSpecResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ParameterSpecResponseArrayOutput) ElementType 

func (GoogleCloudMlV1__ParameterSpecResponseArrayOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecResponseArrayOutput) Index 

func (o GoogleCloudMlV1__ParameterSpecResponseArrayOutput) Index(i pulumi.IntInput) GoogleCloudMlV1__ParameterSpecResponseOutput

func (GoogleCloudMlV1__ParameterSpecResponseArrayOutput) ToGoogleCloudMlV1__ParameterSpecResponseArrayOutput 

func (o GoogleCloudMlV1__ParameterSpecResponseArrayOutput) ToGoogleCloudMlV1__ParameterSpecResponseArrayOutput() GoogleCloudMlV1__ParameterSpecResponseArrayOutput

func (GoogleCloudMlV1__ParameterSpecResponseArrayOutput) ToGoogleCloudMlV1__ParameterSpecResponseArrayOutputWithContext 

func (o GoogleCloudMlV1__ParameterSpecResponseArrayOutput) ToGoogleCloudMlV1__ParameterSpecResponseArrayOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecResponseArrayOutput

type GoogleCloudMlV1__ParameterSpecResponseOutput 

type GoogleCloudMlV1__ParameterSpecResponseOutput struct{ *pulumi.OutputState }

Represents a single hyperparameter to optimize.

func (GoogleCloudMlV1__ParameterSpecResponseOutput) CategoricalValues 

func (o GoogleCloudMlV1__ParameterSpecResponseOutput) CategoricalValues() pulumi.StringArrayOutput

Required if type is `CATEGORICAL`. The list of possible categories.

func (GoogleCloudMlV1__ParameterSpecResponseOutput) DiscreteValues 

func (o GoogleCloudMlV1__ParameterSpecResponseOutput) DiscreteValues() pulumi.Float64ArrayOutput

Required if type is `DISCRETE`. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

func (GoogleCloudMlV1__ParameterSpecResponseOutput) ElementType 

func (GoogleCloudMlV1__ParameterSpecResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecResponseOutput) MaxValue 

func (o GoogleCloudMlV1__ParameterSpecResponseOutput) MaxValue() pulumi.Float64Output

Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is `INTEGER`.

func (GoogleCloudMlV1__ParameterSpecResponseOutput) MinValue 

func (o GoogleCloudMlV1__ParameterSpecResponseOutput) MinValue() pulumi.Float64Output

Required if type is `DOUBLE` or `INTEGER`. This field should be unset if type is `CATEGORICAL`. This value should be integers if type is INTEGER.

func (GoogleCloudMlV1__ParameterSpecResponseOutput) ParameterName 

func (o GoogleCloudMlV1__ParameterSpecResponseOutput) ParameterName() pulumi.StringOutput

The parameter name must be unique amongst all ParameterConfigs in a HyperparameterSpec message. E.g., "learning_rate".

func (GoogleCloudMlV1__ParameterSpecResponseOutput) ScaleType 

func (o GoogleCloudMlV1__ParameterSpecResponseOutput) ScaleType() pulumi.StringOutput

Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., `UNIT_LINEAR_SCALE`).

func (GoogleCloudMlV1__ParameterSpecResponseOutput) ToGoogleCloudMlV1__ParameterSpecResponseOutput 

func (o GoogleCloudMlV1__ParameterSpecResponseOutput) ToGoogleCloudMlV1__ParameterSpecResponseOutput() GoogleCloudMlV1__ParameterSpecResponseOutput

func (GoogleCloudMlV1__ParameterSpecResponseOutput) ToGoogleCloudMlV1__ParameterSpecResponseOutputWithContext 

func (o GoogleCloudMlV1__ParameterSpecResponseOutput) ToGoogleCloudMlV1__ParameterSpecResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecResponseOutput

func (GoogleCloudMlV1__ParameterSpecResponseOutput) Type 

func (o GoogleCloudMlV1__ParameterSpecResponseOutput) Type() pulumi.StringOutput

The type of the parameter.

type GoogleCloudMlV1__ParameterSpecScaleType added in v0.4.0 

type GoogleCloudMlV1__ParameterSpecScaleType string

Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g., `UNIT_LINEAR_SCALE`).

func (GoogleCloudMlV1__ParameterSpecScaleType) ElementType added in v0.4.0 

func (GoogleCloudMlV1__ParameterSpecScaleType) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecScaleType) ToGoogleCloudMlV1__ParameterSpecScaleTypeOutput added in v0.6.0 

func (e GoogleCloudMlV1__ParameterSpecScaleType) ToGoogleCloudMlV1__ParameterSpecScaleTypeOutput() GoogleCloudMlV1__ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1__ParameterSpecScaleType) ToGoogleCloudMlV1__ParameterSpecScaleTypeOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__ParameterSpecScaleType) ToGoogleCloudMlV1__ParameterSpecScaleTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1__ParameterSpecScaleType) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__ParameterSpecScaleType) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutput() GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecScaleType) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__ParameterSpecScaleType) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecScaleType) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__ParameterSpecScaleType) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__ParameterSpecScaleType) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__ParameterSpecScaleType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__ParameterSpecScaleType) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__ParameterSpecScaleType) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__ParameterSpecScaleType) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__ParameterSpecScaleType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__ParameterSpecScaleTypeInput added in v0.6.0 

type GoogleCloudMlV1__ParameterSpecScaleTypeInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ParameterSpecScaleTypeOutput() GoogleCloudMlV1__ParameterSpecScaleTypeOutput
	ToGoogleCloudMlV1__ParameterSpecScaleTypeOutputWithContext(context.Context) GoogleCloudMlV1__ParameterSpecScaleTypeOutput
}

GoogleCloudMlV1__ParameterSpecScaleTypeInput is an input type that accepts GoogleCloudMlV1__ParameterSpecScaleTypeArgs and GoogleCloudMlV1__ParameterSpecScaleTypeOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ParameterSpecScaleTypeInput` via: 

GoogleCloudMlV1__ParameterSpecScaleTypeArgs{...}

type GoogleCloudMlV1__ParameterSpecScaleTypeOutput added in v0.6.0 

type GoogleCloudMlV1__ParameterSpecScaleTypeOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypeOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypeOutput() GoogleCloudMlV1__ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypeOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutput() GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__ParameterSpecScaleTypePtrInput added in v0.6.0 

type GoogleCloudMlV1__ParameterSpecScaleTypePtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutput() GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput
	ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutputWithContext(context.Context) GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput
}

func GoogleCloudMlV1__ParameterSpecScaleTypePtr added in v0.6.0 

func GoogleCloudMlV1__ParameterSpecScaleTypePtr(v string) GoogleCloudMlV1__ParameterSpecScaleTypePtrInput

type GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput added in v0.6.0 

type GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) Elem() GoogleCloudMlV1__ParameterSpecScaleTypeOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutput() GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ToGoogleCloudMlV1__ParameterSpecScaleTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecScaleTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__ParameterSpecType added in v0.4.0 

type GoogleCloudMlV1__ParameterSpecType string

Required. The type of the parameter.

func (GoogleCloudMlV1__ParameterSpecType) ElementType added in v0.4.0 

func (GoogleCloudMlV1__ParameterSpecType) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecType) ToGoogleCloudMlV1__ParameterSpecTypeOutput added in v0.6.0 

func (e GoogleCloudMlV1__ParameterSpecType) ToGoogleCloudMlV1__ParameterSpecTypeOutput() GoogleCloudMlV1__ParameterSpecTypeOutput

func (GoogleCloudMlV1__ParameterSpecType) ToGoogleCloudMlV1__ParameterSpecTypeOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__ParameterSpecType) ToGoogleCloudMlV1__ParameterSpecTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecTypeOutput

func (GoogleCloudMlV1__ParameterSpecType) ToGoogleCloudMlV1__ParameterSpecTypePtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__ParameterSpecType) ToGoogleCloudMlV1__ParameterSpecTypePtrOutput() GoogleCloudMlV1__ParameterSpecTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecType) ToGoogleCloudMlV1__ParameterSpecTypePtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__ParameterSpecType) ToGoogleCloudMlV1__ParameterSpecTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecType) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__ParameterSpecType) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__ParameterSpecType) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__ParameterSpecType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__ParameterSpecType) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__ParameterSpecType) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__ParameterSpecType) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__ParameterSpecType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__ParameterSpecTypeInput added in v0.6.0 

type GoogleCloudMlV1__ParameterSpecTypeInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ParameterSpecTypeOutput() GoogleCloudMlV1__ParameterSpecTypeOutput
	ToGoogleCloudMlV1__ParameterSpecTypeOutputWithContext(context.Context) GoogleCloudMlV1__ParameterSpecTypeOutput
}

GoogleCloudMlV1__ParameterSpecTypeInput is an input type that accepts GoogleCloudMlV1__ParameterSpecTypeArgs and GoogleCloudMlV1__ParameterSpecTypeOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ParameterSpecTypeInput` via: 

GoogleCloudMlV1__ParameterSpecTypeArgs{...}

type GoogleCloudMlV1__ParameterSpecTypeOutput added in v0.6.0 

type GoogleCloudMlV1__ParameterSpecTypeOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ToGoogleCloudMlV1__ParameterSpecTypeOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypeOutput) ToGoogleCloudMlV1__ParameterSpecTypeOutput() GoogleCloudMlV1__ParameterSpecTypeOutput

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ToGoogleCloudMlV1__ParameterSpecTypeOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypeOutput) ToGoogleCloudMlV1__ParameterSpecTypeOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecTypeOutput

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ToGoogleCloudMlV1__ParameterSpecTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypeOutput) ToGoogleCloudMlV1__ParameterSpecTypePtrOutput() GoogleCloudMlV1__ParameterSpecTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ToGoogleCloudMlV1__ParameterSpecTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypeOutput) ToGoogleCloudMlV1__ParameterSpecTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypeOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__ParameterSpecTypeOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__ParameterSpecTypePtrInput added in v0.6.0 

type GoogleCloudMlV1__ParameterSpecTypePtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ParameterSpecTypePtrOutput() GoogleCloudMlV1__ParameterSpecTypePtrOutput
	ToGoogleCloudMlV1__ParameterSpecTypePtrOutputWithContext(context.Context) GoogleCloudMlV1__ParameterSpecTypePtrOutput
}

func GoogleCloudMlV1__ParameterSpecTypePtr added in v0.6.0 

func GoogleCloudMlV1__ParameterSpecTypePtr(v string) GoogleCloudMlV1__ParameterSpecTypePtrInput

type GoogleCloudMlV1__ParameterSpecTypePtrOutput added in v0.6.0 

type GoogleCloudMlV1__ParameterSpecTypePtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ParameterSpecTypePtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypePtrOutput) Elem() GoogleCloudMlV1__ParameterSpecTypeOutput

func (GoogleCloudMlV1__ParameterSpecTypePtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__ParameterSpecTypePtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ParameterSpecTypePtrOutput) ToGoogleCloudMlV1__ParameterSpecTypePtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypePtrOutput) ToGoogleCloudMlV1__ParameterSpecTypePtrOutput() GoogleCloudMlV1__ParameterSpecTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecTypePtrOutput) ToGoogleCloudMlV1__ParameterSpecTypePtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypePtrOutput) ToGoogleCloudMlV1__ParameterSpecTypePtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ParameterSpecTypePtrOutput

func (GoogleCloudMlV1__ParameterSpecTypePtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__ParameterSpecTypePtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__ParameterSpecTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__PredictionInput 

type GoogleCloudMlV1__PredictionInput struct {
	// Optional. Number of records per batch, defaults to 64. The service will buffer batch_size number of records in memory before invoking one Tensorflow prediction call internally. So take the record size and memory available into consideration when setting this parameter.
	BatchSize *string `pulumi:"batchSize"`
	// The format of the input data files.
	DataFormat GoogleCloudMlV1__PredictionInputDataFormat `pulumi:"dataFormat"`
	// The Cloud Storage location of the input data files. May contain wildcards.
	InputPaths []string `pulumi:"inputPaths"`
	// Optional. The maximum number of workers to be used for parallel processing. Defaults to 10 if not specified.
	MaxWorkerCount *string `pulumi:"maxWorkerCount"`
	// Use this field if you want to use the default version for the specified model. The string must use the following format: `"projects/YOUR_PROJECT/models/YOUR_MODEL"`
	ModelName *string `pulumi:"modelName"`
	// Optional. Format of the output data files, defaults to JSON.
	OutputDataFormat *GoogleCloudMlV1__PredictionInputOutputDataFormat `pulumi:"outputDataFormat"`
	// The output Google Cloud Storage location.
	OutputPath string `pulumi:"outputPath"`
	// The Google Compute Engine region to run the prediction job in. See the available regions for AI Platform services.
	Region string `pulumi:"region"`
	// Optional. The AI Platform runtime version to use for this batch prediction. If not set, AI Platform will pick the runtime version used during the CreateVersion request for this model version, or choose the latest stable version when model version information is not available such as when the model is specified by uri.
	RuntimeVersion *string `pulumi:"runtimeVersion"`
	// Optional. The name of the signature defined in the SavedModel to use for this job. Please refer to [SavedModel](https://tensorflow.github.io/serving/serving_basic.html) for information about how to use signatures. Defaults to [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/tf/saved_model/signature_constants) , which is "serving_default".
	SignatureName *string `pulumi:"signatureName"`
	// Use this field if you want to specify a Google Cloud Storage path for the model to use.
	Uri *string `pulumi:"uri"`
	// Use this field if you want to specify a version of the model to use. The string is formatted the same way as `model_version`, with the addition of the version information: `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"`
	VersionName *string `pulumi:"versionName"`
}

Represents input parameters for a prediction job.

type GoogleCloudMlV1__PredictionInputArgs 

type GoogleCloudMlV1__PredictionInputArgs struct {
	// Optional. Number of records per batch, defaults to 64. The service will buffer batch_size number of records in memory before invoking one Tensorflow prediction call internally. So take the record size and memory available into consideration when setting this parameter.
	BatchSize pulumi.StringPtrInput `pulumi:"batchSize"`
	// The format of the input data files.
	DataFormat GoogleCloudMlV1__PredictionInputDataFormatInput `pulumi:"dataFormat"`
	// The Cloud Storage location of the input data files. May contain wildcards.
	InputPaths pulumi.StringArrayInput `pulumi:"inputPaths"`
	// Optional. The maximum number of workers to be used for parallel processing. Defaults to 10 if not specified.
	MaxWorkerCount pulumi.StringPtrInput `pulumi:"maxWorkerCount"`
	// Use this field if you want to use the default version for the specified model. The string must use the following format: `"projects/YOUR_PROJECT/models/YOUR_MODEL"`
	ModelName pulumi.StringPtrInput `pulumi:"modelName"`
	// Optional. Format of the output data files, defaults to JSON.
	OutputDataFormat GoogleCloudMlV1__PredictionInputOutputDataFormatPtrInput `pulumi:"outputDataFormat"`
	// The output Google Cloud Storage location.
	OutputPath pulumi.StringInput `pulumi:"outputPath"`
	// The Google Compute Engine region to run the prediction job in. See the available regions for AI Platform services.
	Region pulumi.StringInput `pulumi:"region"`
	// Optional. The AI Platform runtime version to use for this batch prediction. If not set, AI Platform will pick the runtime version used during the CreateVersion request for this model version, or choose the latest stable version when model version information is not available such as when the model is specified by uri.
	RuntimeVersion pulumi.StringPtrInput `pulumi:"runtimeVersion"`
	// Optional. The name of the signature defined in the SavedModel to use for this job. Please refer to [SavedModel](https://tensorflow.github.io/serving/serving_basic.html) for information about how to use signatures. Defaults to [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/tf/saved_model/signature_constants) , which is "serving_default".
	SignatureName pulumi.StringPtrInput `pulumi:"signatureName"`
	// Use this field if you want to specify a Google Cloud Storage path for the model to use.
	Uri pulumi.StringPtrInput `pulumi:"uri"`
	// Use this field if you want to specify a version of the model to use. The string is formatted the same way as `model_version`, with the addition of the version information: `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"`
	VersionName pulumi.StringPtrInput `pulumi:"versionName"`
}

Represents input parameters for a prediction job.

func (GoogleCloudMlV1__PredictionInputArgs) ElementType 

func (GoogleCloudMlV1__PredictionInputArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputArgs) ToGoogleCloudMlV1__PredictionInputOutput 

func (i GoogleCloudMlV1__PredictionInputArgs) ToGoogleCloudMlV1__PredictionInputOutput() GoogleCloudMlV1__PredictionInputOutput

func (GoogleCloudMlV1__PredictionInputArgs) ToGoogleCloudMlV1__PredictionInputOutputWithContext 

func (i GoogleCloudMlV1__PredictionInputArgs) ToGoogleCloudMlV1__PredictionInputOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputOutput

func (GoogleCloudMlV1__PredictionInputArgs) ToGoogleCloudMlV1__PredictionInputPtrOutput 

func (i GoogleCloudMlV1__PredictionInputArgs) ToGoogleCloudMlV1__PredictionInputPtrOutput() GoogleCloudMlV1__PredictionInputPtrOutput

func (GoogleCloudMlV1__PredictionInputArgs) ToGoogleCloudMlV1__PredictionInputPtrOutputWithContext 

func (i GoogleCloudMlV1__PredictionInputArgs) ToGoogleCloudMlV1__PredictionInputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputPtrOutput

type GoogleCloudMlV1__PredictionInputDataFormat added in v0.4.0 

type GoogleCloudMlV1__PredictionInputDataFormat string

Required. The format of the input data files.

func (GoogleCloudMlV1__PredictionInputDataFormat) ElementType added in v0.4.0 

func (GoogleCloudMlV1__PredictionInputDataFormat) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputDataFormat) ToGoogleCloudMlV1__PredictionInputDataFormatOutput added in v0.6.0 

func (e GoogleCloudMlV1__PredictionInputDataFormat) ToGoogleCloudMlV1__PredictionInputDataFormatOutput() GoogleCloudMlV1__PredictionInputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputDataFormat) ToGoogleCloudMlV1__PredictionInputDataFormatOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__PredictionInputDataFormat) ToGoogleCloudMlV1__PredictionInputDataFormatOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputDataFormat) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__PredictionInputDataFormat) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutput() GoogleCloudMlV1__PredictionInputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputDataFormat) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__PredictionInputDataFormat) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputDataFormat) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__PredictionInputDataFormat) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__PredictionInputDataFormat) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__PredictionInputDataFormat) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__PredictionInputDataFormat) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__PredictionInputDataFormat) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__PredictionInputDataFormat) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__PredictionInputDataFormat) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__PredictionInputDataFormatInput added in v0.6.0 

type GoogleCloudMlV1__PredictionInputDataFormatInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__PredictionInputDataFormatOutput() GoogleCloudMlV1__PredictionInputDataFormatOutput
	ToGoogleCloudMlV1__PredictionInputDataFormatOutputWithContext(context.Context) GoogleCloudMlV1__PredictionInputDataFormatOutput
}

GoogleCloudMlV1__PredictionInputDataFormatInput is an input type that accepts GoogleCloudMlV1__PredictionInputDataFormatArgs and GoogleCloudMlV1__PredictionInputDataFormatOutput values. You can construct a concrete instance of `GoogleCloudMlV1__PredictionInputDataFormatInput` via: 

GoogleCloudMlV1__PredictionInputDataFormatArgs{...}

type GoogleCloudMlV1__PredictionInputDataFormatOutput added in v0.6.0 

type GoogleCloudMlV1__PredictionInputDataFormatOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputDataFormatOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputDataFormatOutput() GoogleCloudMlV1__PredictionInputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputDataFormatOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputDataFormatOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutput() GoogleCloudMlV1__PredictionInputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__PredictionInputDataFormatOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__PredictionInputDataFormatPtrInput added in v0.6.0 

type GoogleCloudMlV1__PredictionInputDataFormatPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutput() GoogleCloudMlV1__PredictionInputDataFormatPtrOutput
	ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutputWithContext(context.Context) GoogleCloudMlV1__PredictionInputDataFormatPtrOutput
}

func GoogleCloudMlV1__PredictionInputDataFormatPtr added in v0.6.0 

func GoogleCloudMlV1__PredictionInputDataFormatPtr(v string) GoogleCloudMlV1__PredictionInputDataFormatPtrInput

type GoogleCloudMlV1__PredictionInputDataFormatPtrOutput added in v0.6.0 

type GoogleCloudMlV1__PredictionInputDataFormatPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) Elem() GoogleCloudMlV1__PredictionInputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutput() GoogleCloudMlV1__PredictionInputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ToGoogleCloudMlV1__PredictionInputDataFormatPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputDataFormatPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__PredictionInputInput 

type GoogleCloudMlV1__PredictionInputInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__PredictionInputOutput() GoogleCloudMlV1__PredictionInputOutput
	ToGoogleCloudMlV1__PredictionInputOutputWithContext(context.Context) GoogleCloudMlV1__PredictionInputOutput
}

GoogleCloudMlV1__PredictionInputInput is an input type that accepts GoogleCloudMlV1__PredictionInputArgs and GoogleCloudMlV1__PredictionInputOutput values. You can construct a concrete instance of `GoogleCloudMlV1__PredictionInputInput` via: 

GoogleCloudMlV1__PredictionInputArgs{...}

type GoogleCloudMlV1__PredictionInputOutput 

type GoogleCloudMlV1__PredictionInputOutput struct{ *pulumi.OutputState }

Represents input parameters for a prediction job.

func (GoogleCloudMlV1__PredictionInputOutput) BatchSize 

func (o GoogleCloudMlV1__PredictionInputOutput) BatchSize() pulumi.StringPtrOutput

Optional. Number of records per batch, defaults to 64. The service will buffer batch_size number of records in memory before invoking one Tensorflow prediction call internally. So take the record size and memory available into consideration when setting this parameter.

func (GoogleCloudMlV1__PredictionInputOutput) DataFormat 

func (o GoogleCloudMlV1__PredictionInputOutput) DataFormat() GoogleCloudMlV1__PredictionInputDataFormatOutput

The format of the input data files.

func (GoogleCloudMlV1__PredictionInputOutput) ElementType 

func (GoogleCloudMlV1__PredictionInputOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputOutput) InputPaths 

func (o GoogleCloudMlV1__PredictionInputOutput) InputPaths() pulumi.StringArrayOutput

The Cloud Storage location of the input data files. May contain wildcards.

func (GoogleCloudMlV1__PredictionInputOutput) MaxWorkerCount 

func (o GoogleCloudMlV1__PredictionInputOutput) MaxWorkerCount() pulumi.StringPtrOutput

Optional. The maximum number of workers to be used for parallel processing. Defaults to 10 if not specified.

func (GoogleCloudMlV1__PredictionInputOutput) ModelName 

func (o GoogleCloudMlV1__PredictionInputOutput) ModelName() pulumi.StringPtrOutput

Use this field if you want to use the default version for the specified model. The string must use the following format: `"projects/YOUR_PROJECT/models/YOUR_MODEL"`

func (GoogleCloudMlV1__PredictionInputOutput) OutputDataFormat 

func (o GoogleCloudMlV1__PredictionInputOutput) OutputDataFormat() GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput

Optional. Format of the output data files, defaults to JSON.

func (GoogleCloudMlV1__PredictionInputOutput) OutputPath 

func (o GoogleCloudMlV1__PredictionInputOutput) OutputPath() pulumi.StringOutput

The output Google Cloud Storage location.

func (GoogleCloudMlV1__PredictionInputOutput) Region 

func (o GoogleCloudMlV1__PredictionInputOutput) Region() pulumi.StringOutput

The Google Compute Engine region to run the prediction job in. See the available regions for AI Platform services.

func (GoogleCloudMlV1__PredictionInputOutput) RuntimeVersion 

func (o GoogleCloudMlV1__PredictionInputOutput) RuntimeVersion() pulumi.StringPtrOutput

Optional. The AI Platform runtime version to use for this batch prediction. If not set, AI Platform will pick the runtime version used during the CreateVersion request for this model version, or choose the latest stable version when model version information is not available such as when the model is specified by uri.

func (GoogleCloudMlV1__PredictionInputOutput) SignatureName 

func (o GoogleCloudMlV1__PredictionInputOutput) SignatureName() pulumi.StringPtrOutput

Optional. The name of the signature defined in the SavedModel to use for this job. Please refer to [SavedModel](https://tensorflow.github.io/serving/serving_basic.html) for information about how to use signatures. Defaults to [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/tf/saved_model/signature_constants) , which is "serving_default".

func (GoogleCloudMlV1__PredictionInputOutput) ToGoogleCloudMlV1__PredictionInputOutput 

func (o GoogleCloudMlV1__PredictionInputOutput) ToGoogleCloudMlV1__PredictionInputOutput() GoogleCloudMlV1__PredictionInputOutput

func (GoogleCloudMlV1__PredictionInputOutput) ToGoogleCloudMlV1__PredictionInputOutputWithContext 

func (o GoogleCloudMlV1__PredictionInputOutput) ToGoogleCloudMlV1__PredictionInputOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputOutput

func (GoogleCloudMlV1__PredictionInputOutput) ToGoogleCloudMlV1__PredictionInputPtrOutput 

func (o GoogleCloudMlV1__PredictionInputOutput) ToGoogleCloudMlV1__PredictionInputPtrOutput() GoogleCloudMlV1__PredictionInputPtrOutput

func (GoogleCloudMlV1__PredictionInputOutput) ToGoogleCloudMlV1__PredictionInputPtrOutputWithContext 

func (o GoogleCloudMlV1__PredictionInputOutput) ToGoogleCloudMlV1__PredictionInputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputPtrOutput

func (GoogleCloudMlV1__PredictionInputOutput) Uri 

func (o GoogleCloudMlV1__PredictionInputOutput) Uri() pulumi.StringPtrOutput

Use this field if you want to specify a Google Cloud Storage path for the model to use.

func (GoogleCloudMlV1__PredictionInputOutput) VersionName 

func (o GoogleCloudMlV1__PredictionInputOutput) VersionName() pulumi.StringPtrOutput

Use this field if you want to specify a version of the model to use. The string is formatted the same way as `model_version`, with the addition of the version information: `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"`

type GoogleCloudMlV1__PredictionInputOutputDataFormat added in v0.4.0 

type GoogleCloudMlV1__PredictionInputOutputDataFormat string

Optional. Format of the output data files, defaults to JSON.

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ElementType added in v0.4.0 

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutput added in v0.6.0 

func (e GoogleCloudMlV1__PredictionInputOutputDataFormat) ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutput() GoogleCloudMlV1__PredictionInputOutputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__PredictionInputOutputDataFormat) ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputOutputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__PredictionInputOutputDataFormat) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput() GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__PredictionInputOutputDataFormat) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__PredictionInputOutputDataFormat) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__PredictionInputOutputDataFormat) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__PredictionInputOutputDataFormat) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormat) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__PredictionInputOutputDataFormat) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__PredictionInputOutputDataFormatInput added in v0.6.0 

type GoogleCloudMlV1__PredictionInputOutputDataFormatInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutput() GoogleCloudMlV1__PredictionInputOutputDataFormatOutput
	ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutputWithContext(context.Context) GoogleCloudMlV1__PredictionInputOutputDataFormatOutput
}

GoogleCloudMlV1__PredictionInputOutputDataFormatInput is an input type that accepts GoogleCloudMlV1__PredictionInputOutputDataFormatArgs and GoogleCloudMlV1__PredictionInputOutputDataFormatOutput values. You can construct a concrete instance of `GoogleCloudMlV1__PredictionInputOutputDataFormatInput` via: 

GoogleCloudMlV1__PredictionInputOutputDataFormatArgs{...}

type GoogleCloudMlV1__PredictionInputOutputDataFormatOutput added in v0.6.0 

type GoogleCloudMlV1__PredictionInputOutputDataFormatOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutput() GoogleCloudMlV1__PredictionInputOutputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputOutputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput() GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__PredictionInputOutputDataFormatPtrInput added in v0.6.0 

type GoogleCloudMlV1__PredictionInputOutputDataFormatPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput() GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput
	ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutputWithContext(context.Context) GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput
}

func GoogleCloudMlV1__PredictionInputOutputDataFormatPtr added in v0.6.0 

func GoogleCloudMlV1__PredictionInputOutputDataFormatPtr(v string) GoogleCloudMlV1__PredictionInputOutputDataFormatPtrInput

type GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput added in v0.6.0 

type GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) Elem() GoogleCloudMlV1__PredictionInputOutputDataFormatOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput() GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ToGoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__PredictionInputPtrInput 

type GoogleCloudMlV1__PredictionInputPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__PredictionInputPtrOutput() GoogleCloudMlV1__PredictionInputPtrOutput
	ToGoogleCloudMlV1__PredictionInputPtrOutputWithContext(context.Context) GoogleCloudMlV1__PredictionInputPtrOutput
}

GoogleCloudMlV1__PredictionInputPtrInput is an input type that accepts GoogleCloudMlV1__PredictionInputArgs, GoogleCloudMlV1__PredictionInputPtr and GoogleCloudMlV1__PredictionInputPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__PredictionInputPtrInput` via: 

        GoogleCloudMlV1__PredictionInputArgs{...}

or:

        nil

func GoogleCloudMlV1__PredictionInputPtr 

func GoogleCloudMlV1__PredictionInputPtr(v *GoogleCloudMlV1__PredictionInputArgs) GoogleCloudMlV1__PredictionInputPtrInput

type GoogleCloudMlV1__PredictionInputPtrOutput 

type GoogleCloudMlV1__PredictionInputPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__PredictionInputPtrOutput) BatchSize 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) BatchSize() pulumi.StringPtrOutput

Optional. Number of records per batch, defaults to 64. The service will buffer batch_size number of records in memory before invoking one Tensorflow prediction call internally. So take the record size and memory available into consideration when setting this parameter.

func (GoogleCloudMlV1__PredictionInputPtrOutput) DataFormat 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) DataFormat() GoogleCloudMlV1__PredictionInputDataFormatPtrOutput

The format of the input data files.

func (GoogleCloudMlV1__PredictionInputPtrOutput) Elem 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) Elem() GoogleCloudMlV1__PredictionInputOutput

func (GoogleCloudMlV1__PredictionInputPtrOutput) ElementType 

func (GoogleCloudMlV1__PredictionInputPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputPtrOutput) InputPaths 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) InputPaths() pulumi.StringArrayOutput

The Cloud Storage location of the input data files. May contain wildcards.

func (GoogleCloudMlV1__PredictionInputPtrOutput) MaxWorkerCount 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) MaxWorkerCount() pulumi.StringPtrOutput

Optional. The maximum number of workers to be used for parallel processing. Defaults to 10 if not specified.

func (GoogleCloudMlV1__PredictionInputPtrOutput) ModelName 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) ModelName() pulumi.StringPtrOutput

Use this field if you want to use the default version for the specified model. The string must use the following format: `"projects/YOUR_PROJECT/models/YOUR_MODEL"`

func (GoogleCloudMlV1__PredictionInputPtrOutput) OutputDataFormat 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) OutputDataFormat() GoogleCloudMlV1__PredictionInputOutputDataFormatPtrOutput

Optional. Format of the output data files, defaults to JSON.

func (GoogleCloudMlV1__PredictionInputPtrOutput) OutputPath 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) OutputPath() pulumi.StringPtrOutput

The output Google Cloud Storage location.

func (GoogleCloudMlV1__PredictionInputPtrOutput) Region 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) Region() pulumi.StringPtrOutput

The Google Compute Engine region to run the prediction job in. See the available regions for AI Platform services.

func (GoogleCloudMlV1__PredictionInputPtrOutput) RuntimeVersion 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) RuntimeVersion() pulumi.StringPtrOutput

Optional. The AI Platform runtime version to use for this batch prediction. If not set, AI Platform will pick the runtime version used during the CreateVersion request for this model version, or choose the latest stable version when model version information is not available such as when the model is specified by uri.

func (GoogleCloudMlV1__PredictionInputPtrOutput) SignatureName 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) SignatureName() pulumi.StringPtrOutput

Optional. The name of the signature defined in the SavedModel to use for this job. Please refer to [SavedModel](https://tensorflow.github.io/serving/serving_basic.html) for information about how to use signatures. Defaults to [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/tf/saved_model/signature_constants) , which is "serving_default".

func (GoogleCloudMlV1__PredictionInputPtrOutput) ToGoogleCloudMlV1__PredictionInputPtrOutput 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) ToGoogleCloudMlV1__PredictionInputPtrOutput() GoogleCloudMlV1__PredictionInputPtrOutput

func (GoogleCloudMlV1__PredictionInputPtrOutput) ToGoogleCloudMlV1__PredictionInputPtrOutputWithContext 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) ToGoogleCloudMlV1__PredictionInputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputPtrOutput

func (GoogleCloudMlV1__PredictionInputPtrOutput) Uri 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) Uri() pulumi.StringPtrOutput

Use this field if you want to specify a Google Cloud Storage path for the model to use.

func (GoogleCloudMlV1__PredictionInputPtrOutput) VersionName 

func (o GoogleCloudMlV1__PredictionInputPtrOutput) VersionName() pulumi.StringPtrOutput

Use this field if you want to specify a version of the model to use. The string is formatted the same way as `model_version`, with the addition of the version information: `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"`

type GoogleCloudMlV1__PredictionInputResponse 

type GoogleCloudMlV1__PredictionInputResponse struct {
	// Optional. Number of records per batch, defaults to 64. The service will buffer batch_size number of records in memory before invoking one Tensorflow prediction call internally. So take the record size and memory available into consideration when setting this parameter.
	BatchSize string `pulumi:"batchSize"`
	// The format of the input data files.
	DataFormat string `pulumi:"dataFormat"`
	// The Cloud Storage location of the input data files. May contain wildcards.
	InputPaths []string `pulumi:"inputPaths"`
	// Optional. The maximum number of workers to be used for parallel processing. Defaults to 10 if not specified.
	MaxWorkerCount string `pulumi:"maxWorkerCount"`
	// Use this field if you want to use the default version for the specified model. The string must use the following format: `"projects/YOUR_PROJECT/models/YOUR_MODEL"`
	ModelName string `pulumi:"modelName"`
	// Optional. Format of the output data files, defaults to JSON.
	OutputDataFormat string `pulumi:"outputDataFormat"`
	// The output Google Cloud Storage location.
	OutputPath string `pulumi:"outputPath"`
	// The Google Compute Engine region to run the prediction job in. See the available regions for AI Platform services.
	Region string `pulumi:"region"`
	// Optional. The AI Platform runtime version to use for this batch prediction. If not set, AI Platform will pick the runtime version used during the CreateVersion request for this model version, or choose the latest stable version when model version information is not available such as when the model is specified by uri.
	RuntimeVersion string `pulumi:"runtimeVersion"`
	// Optional. The name of the signature defined in the SavedModel to use for this job. Please refer to [SavedModel](https://tensorflow.github.io/serving/serving_basic.html) for information about how to use signatures. Defaults to [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/tf/saved_model/signature_constants) , which is "serving_default".
	SignatureName string `pulumi:"signatureName"`
	// Use this field if you want to specify a Google Cloud Storage path for the model to use.
	Uri string `pulumi:"uri"`
	// Use this field if you want to specify a version of the model to use. The string is formatted the same way as `model_version`, with the addition of the version information: `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"`
	VersionName string `pulumi:"versionName"`
}

Represents input parameters for a prediction job.

type GoogleCloudMlV1__PredictionInputResponseOutput 

type GoogleCloudMlV1__PredictionInputResponseOutput struct{ *pulumi.OutputState }

Represents input parameters for a prediction job.

func (GoogleCloudMlV1__PredictionInputResponseOutput) BatchSize 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) BatchSize() pulumi.StringOutput

Optional. Number of records per batch, defaults to 64. The service will buffer batch_size number of records in memory before invoking one Tensorflow prediction call internally. So take the record size and memory available into consideration when setting this parameter.

func (GoogleCloudMlV1__PredictionInputResponseOutput) DataFormat 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) DataFormat() pulumi.StringOutput

The format of the input data files.

func (GoogleCloudMlV1__PredictionInputResponseOutput) ElementType 

func (GoogleCloudMlV1__PredictionInputResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionInputResponseOutput) InputPaths 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) InputPaths() pulumi.StringArrayOutput

The Cloud Storage location of the input data files. May contain wildcards.

func (GoogleCloudMlV1__PredictionInputResponseOutput) MaxWorkerCount 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) MaxWorkerCount() pulumi.StringOutput

Optional. The maximum number of workers to be used for parallel processing. Defaults to 10 if not specified.

func (GoogleCloudMlV1__PredictionInputResponseOutput) ModelName 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) ModelName() pulumi.StringOutput

Use this field if you want to use the default version for the specified model. The string must use the following format: `"projects/YOUR_PROJECT/models/YOUR_MODEL"`

func (GoogleCloudMlV1__PredictionInputResponseOutput) OutputDataFormat 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) OutputDataFormat() pulumi.StringOutput

Optional. Format of the output data files, defaults to JSON.

func (GoogleCloudMlV1__PredictionInputResponseOutput) OutputPath 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) OutputPath() pulumi.StringOutput

The output Google Cloud Storage location.

func (GoogleCloudMlV1__PredictionInputResponseOutput) Region 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) Region() pulumi.StringOutput

The Google Compute Engine region to run the prediction job in. See the available regions for AI Platform services.

func (GoogleCloudMlV1__PredictionInputResponseOutput) RuntimeVersion 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) RuntimeVersion() pulumi.StringOutput

Optional. The AI Platform runtime version to use for this batch prediction. If not set, AI Platform will pick the runtime version used during the CreateVersion request for this model version, or choose the latest stable version when model version information is not available such as when the model is specified by uri.

func (GoogleCloudMlV1__PredictionInputResponseOutput) SignatureName 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) SignatureName() pulumi.StringOutput

Optional. The name of the signature defined in the SavedModel to use for this job. Please refer to [SavedModel](https://tensorflow.github.io/serving/serving_basic.html) for information about how to use signatures. Defaults to [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/tf/saved_model/signature_constants) , which is "serving_default".

func (GoogleCloudMlV1__PredictionInputResponseOutput) ToGoogleCloudMlV1__PredictionInputResponseOutput 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) ToGoogleCloudMlV1__PredictionInputResponseOutput() GoogleCloudMlV1__PredictionInputResponseOutput

func (GoogleCloudMlV1__PredictionInputResponseOutput) ToGoogleCloudMlV1__PredictionInputResponseOutputWithContext 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) ToGoogleCloudMlV1__PredictionInputResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionInputResponseOutput

func (GoogleCloudMlV1__PredictionInputResponseOutput) Uri 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) Uri() pulumi.StringOutput

Use this field if you want to specify a Google Cloud Storage path for the model to use.

func (GoogleCloudMlV1__PredictionInputResponseOutput) VersionName 

func (o GoogleCloudMlV1__PredictionInputResponseOutput) VersionName() pulumi.StringOutput

Use this field if you want to specify a version of the model to use. The string is formatted the same way as `model_version`, with the addition of the version information: `"projects/YOUR_PROJECT/models/YOUR_MODEL/versions/YOUR_VERSION"`

type GoogleCloudMlV1__PredictionOutput 

type GoogleCloudMlV1__PredictionOutput struct {
	// The number of data instances which resulted in errors.
	ErrorCount *string `pulumi:"errorCount"`
	// Node hours used by the batch prediction job.
	NodeHours *float64 `pulumi:"nodeHours"`
	// The output Google Cloud Storage location provided at the job creation time.
	OutputPath *string `pulumi:"outputPath"`
	// The number of generated predictions.
	PredictionCount *string `pulumi:"predictionCount"`
}

Represents results of a prediction job.

type GoogleCloudMlV1__PredictionOutputArgs 

type GoogleCloudMlV1__PredictionOutputArgs struct {
	// The number of data instances which resulted in errors.
	ErrorCount pulumi.StringPtrInput `pulumi:"errorCount"`
	// Node hours used by the batch prediction job.
	NodeHours pulumi.Float64PtrInput `pulumi:"nodeHours"`
	// The output Google Cloud Storage location provided at the job creation time.
	OutputPath pulumi.StringPtrInput `pulumi:"outputPath"`
	// The number of generated predictions.
	PredictionCount pulumi.StringPtrInput `pulumi:"predictionCount"`
}

Represents results of a prediction job.

func (GoogleCloudMlV1__PredictionOutputArgs) ElementType 

func (GoogleCloudMlV1__PredictionOutputArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionOutputArgs) ToGoogleCloudMlV1__PredictionOutputOutput 

func (i GoogleCloudMlV1__PredictionOutputArgs) ToGoogleCloudMlV1__PredictionOutputOutput() GoogleCloudMlV1__PredictionOutputOutput

func (GoogleCloudMlV1__PredictionOutputArgs) ToGoogleCloudMlV1__PredictionOutputOutputWithContext 

func (i GoogleCloudMlV1__PredictionOutputArgs) ToGoogleCloudMlV1__PredictionOutputOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionOutputOutput

func (GoogleCloudMlV1__PredictionOutputArgs) ToGoogleCloudMlV1__PredictionOutputPtrOutput 

func (i GoogleCloudMlV1__PredictionOutputArgs) ToGoogleCloudMlV1__PredictionOutputPtrOutput() GoogleCloudMlV1__PredictionOutputPtrOutput

func (GoogleCloudMlV1__PredictionOutputArgs) ToGoogleCloudMlV1__PredictionOutputPtrOutputWithContext 

func (i GoogleCloudMlV1__PredictionOutputArgs) ToGoogleCloudMlV1__PredictionOutputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionOutputPtrOutput

type GoogleCloudMlV1__PredictionOutputInput 

type GoogleCloudMlV1__PredictionOutputInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__PredictionOutputOutput() GoogleCloudMlV1__PredictionOutputOutput
	ToGoogleCloudMlV1__PredictionOutputOutputWithContext(context.Context) GoogleCloudMlV1__PredictionOutputOutput
}

GoogleCloudMlV1__PredictionOutputInput is an input type that accepts GoogleCloudMlV1__PredictionOutputArgs and GoogleCloudMlV1__PredictionOutputOutput values. You can construct a concrete instance of `GoogleCloudMlV1__PredictionOutputInput` via: 

GoogleCloudMlV1__PredictionOutputArgs{...}

type GoogleCloudMlV1__PredictionOutputOutput 

type GoogleCloudMlV1__PredictionOutputOutput struct{ *pulumi.OutputState }

Represents results of a prediction job.

func (GoogleCloudMlV1__PredictionOutputOutput) ElementType 

func (GoogleCloudMlV1__PredictionOutputOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionOutputOutput) ErrorCount 

func (o GoogleCloudMlV1__PredictionOutputOutput) ErrorCount() pulumi.StringPtrOutput

The number of data instances which resulted in errors.

func (GoogleCloudMlV1__PredictionOutputOutput) NodeHours 

func (o GoogleCloudMlV1__PredictionOutputOutput) NodeHours() pulumi.Float64PtrOutput

Node hours used by the batch prediction job.

func (GoogleCloudMlV1__PredictionOutputOutput) OutputPath 

func (o GoogleCloudMlV1__PredictionOutputOutput) OutputPath() pulumi.StringPtrOutput

The output Google Cloud Storage location provided at the job creation time.

func (GoogleCloudMlV1__PredictionOutputOutput) PredictionCount 

func (o GoogleCloudMlV1__PredictionOutputOutput) PredictionCount() pulumi.StringPtrOutput

The number of generated predictions.

func (GoogleCloudMlV1__PredictionOutputOutput) ToGoogleCloudMlV1__PredictionOutputOutput 

func (o GoogleCloudMlV1__PredictionOutputOutput) ToGoogleCloudMlV1__PredictionOutputOutput() GoogleCloudMlV1__PredictionOutputOutput

func (GoogleCloudMlV1__PredictionOutputOutput) ToGoogleCloudMlV1__PredictionOutputOutputWithContext 

func (o GoogleCloudMlV1__PredictionOutputOutput) ToGoogleCloudMlV1__PredictionOutputOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionOutputOutput

func (GoogleCloudMlV1__PredictionOutputOutput) ToGoogleCloudMlV1__PredictionOutputPtrOutput 

func (o GoogleCloudMlV1__PredictionOutputOutput) ToGoogleCloudMlV1__PredictionOutputPtrOutput() GoogleCloudMlV1__PredictionOutputPtrOutput

func (GoogleCloudMlV1__PredictionOutputOutput) ToGoogleCloudMlV1__PredictionOutputPtrOutputWithContext 

func (o GoogleCloudMlV1__PredictionOutputOutput) ToGoogleCloudMlV1__PredictionOutputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionOutputPtrOutput

type GoogleCloudMlV1__PredictionOutputPtrInput 

type GoogleCloudMlV1__PredictionOutputPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__PredictionOutputPtrOutput() GoogleCloudMlV1__PredictionOutputPtrOutput
	ToGoogleCloudMlV1__PredictionOutputPtrOutputWithContext(context.Context) GoogleCloudMlV1__PredictionOutputPtrOutput
}

GoogleCloudMlV1__PredictionOutputPtrInput is an input type that accepts GoogleCloudMlV1__PredictionOutputArgs, GoogleCloudMlV1__PredictionOutputPtr and GoogleCloudMlV1__PredictionOutputPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__PredictionOutputPtrInput` via: 

        GoogleCloudMlV1__PredictionOutputArgs{...}

or:

        nil

func GoogleCloudMlV1__PredictionOutputPtr 

func GoogleCloudMlV1__PredictionOutputPtr(v *GoogleCloudMlV1__PredictionOutputArgs) GoogleCloudMlV1__PredictionOutputPtrInput

type GoogleCloudMlV1__PredictionOutputPtrOutput 

type GoogleCloudMlV1__PredictionOutputPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__PredictionOutputPtrOutput) Elem 

func (o GoogleCloudMlV1__PredictionOutputPtrOutput) Elem() GoogleCloudMlV1__PredictionOutputOutput

func (GoogleCloudMlV1__PredictionOutputPtrOutput) ElementType 

func (GoogleCloudMlV1__PredictionOutputPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionOutputPtrOutput) ErrorCount 

func (o GoogleCloudMlV1__PredictionOutputPtrOutput) ErrorCount() pulumi.StringPtrOutput

The number of data instances which resulted in errors.

func (GoogleCloudMlV1__PredictionOutputPtrOutput) NodeHours 

func (o GoogleCloudMlV1__PredictionOutputPtrOutput) NodeHours() pulumi.Float64PtrOutput

Node hours used by the batch prediction job.

func (GoogleCloudMlV1__PredictionOutputPtrOutput) OutputPath 

func (o GoogleCloudMlV1__PredictionOutputPtrOutput) OutputPath() pulumi.StringPtrOutput

The output Google Cloud Storage location provided at the job creation time.

func (GoogleCloudMlV1__PredictionOutputPtrOutput) PredictionCount 

func (o GoogleCloudMlV1__PredictionOutputPtrOutput) PredictionCount() pulumi.StringPtrOutput

The number of generated predictions.

func (GoogleCloudMlV1__PredictionOutputPtrOutput) ToGoogleCloudMlV1__PredictionOutputPtrOutput 

func (o GoogleCloudMlV1__PredictionOutputPtrOutput) ToGoogleCloudMlV1__PredictionOutputPtrOutput() GoogleCloudMlV1__PredictionOutputPtrOutput

func (GoogleCloudMlV1__PredictionOutputPtrOutput) ToGoogleCloudMlV1__PredictionOutputPtrOutputWithContext 

func (o GoogleCloudMlV1__PredictionOutputPtrOutput) ToGoogleCloudMlV1__PredictionOutputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionOutputPtrOutput

type GoogleCloudMlV1__PredictionOutputResponse 

type GoogleCloudMlV1__PredictionOutputResponse struct {
	// The number of data instances which resulted in errors.
	ErrorCount string `pulumi:"errorCount"`
	// Node hours used by the batch prediction job.
	NodeHours float64 `pulumi:"nodeHours"`
	// The output Google Cloud Storage location provided at the job creation time.
	OutputPath string `pulumi:"outputPath"`
	// The number of generated predictions.
	PredictionCount string `pulumi:"predictionCount"`
}

Represents results of a prediction job.

type GoogleCloudMlV1__PredictionOutputResponseOutput 

type GoogleCloudMlV1__PredictionOutputResponseOutput struct{ *pulumi.OutputState }

Represents results of a prediction job.

func (GoogleCloudMlV1__PredictionOutputResponseOutput) ElementType 

func (GoogleCloudMlV1__PredictionOutputResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__PredictionOutputResponseOutput) ErrorCount 

func (o GoogleCloudMlV1__PredictionOutputResponseOutput) ErrorCount() pulumi.StringOutput

The number of data instances which resulted in errors.

func (GoogleCloudMlV1__PredictionOutputResponseOutput) NodeHours 

func (o GoogleCloudMlV1__PredictionOutputResponseOutput) NodeHours() pulumi.Float64Output

Node hours used by the batch prediction job.

func (GoogleCloudMlV1__PredictionOutputResponseOutput) OutputPath 

func (o GoogleCloudMlV1__PredictionOutputResponseOutput) OutputPath() pulumi.StringOutput

The output Google Cloud Storage location provided at the job creation time.

func (GoogleCloudMlV1__PredictionOutputResponseOutput) PredictionCount 

func (o GoogleCloudMlV1__PredictionOutputResponseOutput) PredictionCount() pulumi.StringOutput

The number of generated predictions.

func (GoogleCloudMlV1__PredictionOutputResponseOutput) ToGoogleCloudMlV1__PredictionOutputResponseOutput 

func (o GoogleCloudMlV1__PredictionOutputResponseOutput) ToGoogleCloudMlV1__PredictionOutputResponseOutput() GoogleCloudMlV1__PredictionOutputResponseOutput

func (GoogleCloudMlV1__PredictionOutputResponseOutput) ToGoogleCloudMlV1__PredictionOutputResponseOutputWithContext 

func (o GoogleCloudMlV1__PredictionOutputResponseOutput) ToGoogleCloudMlV1__PredictionOutputResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__PredictionOutputResponseOutput

type GoogleCloudMlV1__ReplicaConfig 

type GoogleCloudMlV1__ReplicaConfig struct {
	// Represents the type and number of accelerators used by the replica. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu)
	AcceleratorConfig *GoogleCloudMlV1__AcceleratorConfig `pulumi:"acceleratorConfig"`
	// Arguments to the entrypoint command. The following rules apply for container_command and container_args: - If you do not supply command or args: The defaults defined in the Docker image are used. - If you supply a command but no args: The default EntryPoint and the default Cmd defined in the Docker image are ignored. Your command is run without any arguments. - If you supply only args: The default Entrypoint defined in the Docker image is run with the args that you supplied. - If you supply a command and args: The default Entrypoint and the default Cmd defined in the Docker image are ignored. Your command is run with your args. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.
	ContainerArgs []string `pulumi:"containerArgs"`
	// The command with which the replica's custom container is run. If provided, it will override default ENTRYPOINT of the docker image. If not provided, the docker image's ENTRYPOINT is used. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.
	ContainerCommand []string `pulumi:"containerCommand"`
	// Represents the configuration of disk options.
	DiskConfig *GoogleCloudMlV1__DiskConfig `pulumi:"diskConfig"`
	// The Docker image to run on the replica. This image must be in Container Registry. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	ImageUri *string `pulumi:"imageUri"`
	// The AI Platform runtime version that includes a TensorFlow version matching the one used in the custom container. This field is required if the replica is a TPU worker that uses a custom container. Otherwise, do not specify this field. This must be a [runtime version that currently supports training with TPUs](/ml-engine/docs/tensorflow/runtime-version-list#tpu-support). Note that the version of TensorFlow included in a runtime version may differ from the numbering of the runtime version itself, because it may have a different [patch version](https://www.tensorflow.org/guide/version_compat#semantic_versioning_20). In this field, you must specify the runtime version (TensorFlow minor version). For example, if your custom container runs TensorFlow `1.x.y`, specify `1.x`.
	TpuTfVersion *string `pulumi:"tpuTfVersion"`
}

Represents the configuration for a replica in a cluster.

type GoogleCloudMlV1__ReplicaConfigArgs 

type GoogleCloudMlV1__ReplicaConfigArgs struct {
	// Represents the type and number of accelerators used by the replica. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu)
	AcceleratorConfig GoogleCloudMlV1__AcceleratorConfigPtrInput `pulumi:"acceleratorConfig"`
	// Arguments to the entrypoint command. The following rules apply for container_command and container_args: - If you do not supply command or args: The defaults defined in the Docker image are used. - If you supply a command but no args: The default EntryPoint and the default Cmd defined in the Docker image are ignored. Your command is run without any arguments. - If you supply only args: The default Entrypoint defined in the Docker image is run with the args that you supplied. - If you supply a command and args: The default Entrypoint and the default Cmd defined in the Docker image are ignored. Your command is run with your args. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.
	ContainerArgs pulumi.StringArrayInput `pulumi:"containerArgs"`
	// The command with which the replica's custom container is run. If provided, it will override default ENTRYPOINT of the docker image. If not provided, the docker image's ENTRYPOINT is used. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.
	ContainerCommand pulumi.StringArrayInput `pulumi:"containerCommand"`
	// Represents the configuration of disk options.
	DiskConfig GoogleCloudMlV1__DiskConfigPtrInput `pulumi:"diskConfig"`
	// The Docker image to run on the replica. This image must be in Container Registry. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	ImageUri pulumi.StringPtrInput `pulumi:"imageUri"`
	// The AI Platform runtime version that includes a TensorFlow version matching the one used in the custom container. This field is required if the replica is a TPU worker that uses a custom container. Otherwise, do not specify this field. This must be a [runtime version that currently supports training with TPUs](/ml-engine/docs/tensorflow/runtime-version-list#tpu-support). Note that the version of TensorFlow included in a runtime version may differ from the numbering of the runtime version itself, because it may have a different [patch version](https://www.tensorflow.org/guide/version_compat#semantic_versioning_20). In this field, you must specify the runtime version (TensorFlow minor version). For example, if your custom container runs TensorFlow `1.x.y`, specify `1.x`.
	TpuTfVersion pulumi.StringPtrInput `pulumi:"tpuTfVersion"`
}

Represents the configuration for a replica in a cluster.

func (GoogleCloudMlV1__ReplicaConfigArgs) ElementType 

func (GoogleCloudMlV1__ReplicaConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__ReplicaConfigArgs) ToGoogleCloudMlV1__ReplicaConfigOutput 

func (i GoogleCloudMlV1__ReplicaConfigArgs) ToGoogleCloudMlV1__ReplicaConfigOutput() GoogleCloudMlV1__ReplicaConfigOutput

func (GoogleCloudMlV1__ReplicaConfigArgs) ToGoogleCloudMlV1__ReplicaConfigOutputWithContext 

func (i GoogleCloudMlV1__ReplicaConfigArgs) ToGoogleCloudMlV1__ReplicaConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__ReplicaConfigOutput

func (GoogleCloudMlV1__ReplicaConfigArgs) ToGoogleCloudMlV1__ReplicaConfigPtrOutput 

func (i GoogleCloudMlV1__ReplicaConfigArgs) ToGoogleCloudMlV1__ReplicaConfigPtrOutput() GoogleCloudMlV1__ReplicaConfigPtrOutput

func (GoogleCloudMlV1__ReplicaConfigArgs) ToGoogleCloudMlV1__ReplicaConfigPtrOutputWithContext 

func (i GoogleCloudMlV1__ReplicaConfigArgs) ToGoogleCloudMlV1__ReplicaConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ReplicaConfigPtrOutput

type GoogleCloudMlV1__ReplicaConfigInput 

type GoogleCloudMlV1__ReplicaConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ReplicaConfigOutput() GoogleCloudMlV1__ReplicaConfigOutput
	ToGoogleCloudMlV1__ReplicaConfigOutputWithContext(context.Context) GoogleCloudMlV1__ReplicaConfigOutput
}

GoogleCloudMlV1__ReplicaConfigInput is an input type that accepts GoogleCloudMlV1__ReplicaConfigArgs and GoogleCloudMlV1__ReplicaConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ReplicaConfigInput` via: 

GoogleCloudMlV1__ReplicaConfigArgs{...}

type GoogleCloudMlV1__ReplicaConfigOutput 

type GoogleCloudMlV1__ReplicaConfigOutput struct{ *pulumi.OutputState }

Represents the configuration for a replica in a cluster.

func (GoogleCloudMlV1__ReplicaConfigOutput) AcceleratorConfig 

func (o GoogleCloudMlV1__ReplicaConfigOutput) AcceleratorConfig() GoogleCloudMlV1__AcceleratorConfigPtrOutput

Represents the type and number of accelerators used by the replica. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu)

func (GoogleCloudMlV1__ReplicaConfigOutput) ContainerArgs 

func (o GoogleCloudMlV1__ReplicaConfigOutput) ContainerArgs() pulumi.StringArrayOutput

Arguments to the entrypoint command. The following rules apply for container_command and container_args: - If you do not supply command or args: The defaults defined in the Docker image are used. - If you supply a command but no args: The default EntryPoint and the default Cmd defined in the Docker image are ignored. Your command is run without any arguments. - If you supply only args: The default Entrypoint defined in the Docker image is run with the args that you supplied. - If you supply a command and args: The default Entrypoint and the default Cmd defined in the Docker image are ignored. Your command is run with your args. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.

func (GoogleCloudMlV1__ReplicaConfigOutput) ContainerCommand 

func (o GoogleCloudMlV1__ReplicaConfigOutput) ContainerCommand() pulumi.StringArrayOutput

The command with which the replica's custom container is run. If provided, it will override default ENTRYPOINT of the docker image. If not provided, the docker image's ENTRYPOINT is used. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.

func (GoogleCloudMlV1__ReplicaConfigOutput) DiskConfig 

func (o GoogleCloudMlV1__ReplicaConfigOutput) DiskConfig() GoogleCloudMlV1__DiskConfigPtrOutput

Represents the configuration of disk options.

func (GoogleCloudMlV1__ReplicaConfigOutput) ElementType 

func (GoogleCloudMlV1__ReplicaConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ReplicaConfigOutput) ImageUri 

func (o GoogleCloudMlV1__ReplicaConfigOutput) ImageUri() pulumi.StringPtrOutput

The Docker image to run on the replica. This image must be in Container Registry. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__ReplicaConfigOutput) ToGoogleCloudMlV1__ReplicaConfigOutput 

func (o GoogleCloudMlV1__ReplicaConfigOutput) ToGoogleCloudMlV1__ReplicaConfigOutput() GoogleCloudMlV1__ReplicaConfigOutput

func (GoogleCloudMlV1__ReplicaConfigOutput) ToGoogleCloudMlV1__ReplicaConfigOutputWithContext 

func (o GoogleCloudMlV1__ReplicaConfigOutput) ToGoogleCloudMlV1__ReplicaConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__ReplicaConfigOutput

func (GoogleCloudMlV1__ReplicaConfigOutput) ToGoogleCloudMlV1__ReplicaConfigPtrOutput 

func (o GoogleCloudMlV1__ReplicaConfigOutput) ToGoogleCloudMlV1__ReplicaConfigPtrOutput() GoogleCloudMlV1__ReplicaConfigPtrOutput

func (GoogleCloudMlV1__ReplicaConfigOutput) ToGoogleCloudMlV1__ReplicaConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__ReplicaConfigOutput) ToGoogleCloudMlV1__ReplicaConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ReplicaConfigPtrOutput

func (GoogleCloudMlV1__ReplicaConfigOutput) TpuTfVersion 

func (o GoogleCloudMlV1__ReplicaConfigOutput) TpuTfVersion() pulumi.StringPtrOutput

The AI Platform runtime version that includes a TensorFlow version matching the one used in the custom container. This field is required if the replica is a TPU worker that uses a custom container. Otherwise, do not specify this field. This must be a [runtime version that currently supports training with TPUs](/ml-engine/docs/tensorflow/runtime-version-list#tpu-support). Note that the version of TensorFlow included in a runtime version may differ from the numbering of the runtime version itself, because it may have a different [patch version](https://www.tensorflow.org/guide/version_compat#semantic_versioning_20). In this field, you must specify the runtime version (TensorFlow minor version). For example, if your custom container runs TensorFlow `1.x.y`, specify `1.x`.

type GoogleCloudMlV1__ReplicaConfigPtrInput 

type GoogleCloudMlV1__ReplicaConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__ReplicaConfigPtrOutput() GoogleCloudMlV1__ReplicaConfigPtrOutput
	ToGoogleCloudMlV1__ReplicaConfigPtrOutputWithContext(context.Context) GoogleCloudMlV1__ReplicaConfigPtrOutput
}

GoogleCloudMlV1__ReplicaConfigPtrInput is an input type that accepts GoogleCloudMlV1__ReplicaConfigArgs, GoogleCloudMlV1__ReplicaConfigPtr and GoogleCloudMlV1__ReplicaConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__ReplicaConfigPtrInput` via: 

        GoogleCloudMlV1__ReplicaConfigArgs{...}

or:

        nil

func GoogleCloudMlV1__ReplicaConfigPtr 

func GoogleCloudMlV1__ReplicaConfigPtr(v *GoogleCloudMlV1__ReplicaConfigArgs) GoogleCloudMlV1__ReplicaConfigPtrInput

type GoogleCloudMlV1__ReplicaConfigPtrOutput 

type GoogleCloudMlV1__ReplicaConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) AcceleratorConfig 

func (o GoogleCloudMlV1__ReplicaConfigPtrOutput) AcceleratorConfig() GoogleCloudMlV1__AcceleratorConfigPtrOutput

Represents the type and number of accelerators used by the replica. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu)

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) ContainerArgs 

func (o GoogleCloudMlV1__ReplicaConfigPtrOutput) ContainerArgs() pulumi.StringArrayOutput

Arguments to the entrypoint command. The following rules apply for container_command and container_args: - If you do not supply command or args: The defaults defined in the Docker image are used. - If you supply a command but no args: The default EntryPoint and the default Cmd defined in the Docker image are ignored. Your command is run without any arguments. - If you supply only args: The default Entrypoint defined in the Docker image is run with the args that you supplied. - If you supply a command and args: The default Entrypoint and the default Cmd defined in the Docker image are ignored. Your command is run with your args. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) ContainerCommand 

func (o GoogleCloudMlV1__ReplicaConfigPtrOutput) ContainerCommand() pulumi.StringArrayOutput

The command with which the replica's custom container is run. If provided, it will override default ENTRYPOINT of the docker image. If not provided, the docker image's ENTRYPOINT is used. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) DiskConfig 

func (o GoogleCloudMlV1__ReplicaConfigPtrOutput) DiskConfig() GoogleCloudMlV1__DiskConfigPtrOutput

Represents the configuration of disk options.

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) Elem 

func (o GoogleCloudMlV1__ReplicaConfigPtrOutput) Elem() GoogleCloudMlV1__ReplicaConfigOutput

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) ElementType 

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) ImageUri 

func (o GoogleCloudMlV1__ReplicaConfigPtrOutput) ImageUri() pulumi.StringPtrOutput

The Docker image to run on the replica. This image must be in Container Registry. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) ToGoogleCloudMlV1__ReplicaConfigPtrOutput 

func (o GoogleCloudMlV1__ReplicaConfigPtrOutput) ToGoogleCloudMlV1__ReplicaConfigPtrOutput() GoogleCloudMlV1__ReplicaConfigPtrOutput

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) ToGoogleCloudMlV1__ReplicaConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__ReplicaConfigPtrOutput) ToGoogleCloudMlV1__ReplicaConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__ReplicaConfigPtrOutput

func (GoogleCloudMlV1__ReplicaConfigPtrOutput) TpuTfVersion 

func (o GoogleCloudMlV1__ReplicaConfigPtrOutput) TpuTfVersion() pulumi.StringPtrOutput

The AI Platform runtime version that includes a TensorFlow version matching the one used in the custom container. This field is required if the replica is a TPU worker that uses a custom container. Otherwise, do not specify this field. This must be a [runtime version that currently supports training with TPUs](/ml-engine/docs/tensorflow/runtime-version-list#tpu-support). Note that the version of TensorFlow included in a runtime version may differ from the numbering of the runtime version itself, because it may have a different [patch version](https://www.tensorflow.org/guide/version_compat#semantic_versioning_20). In this field, you must specify the runtime version (TensorFlow minor version). For example, if your custom container runs TensorFlow `1.x.y`, specify `1.x`.

type GoogleCloudMlV1__ReplicaConfigResponse 

type GoogleCloudMlV1__ReplicaConfigResponse struct {
	// Represents the type and number of accelerators used by the replica. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu)
	AcceleratorConfig GoogleCloudMlV1__AcceleratorConfigResponse `pulumi:"acceleratorConfig"`
	// Arguments to the entrypoint command. The following rules apply for container_command and container_args: - If you do not supply command or args: The defaults defined in the Docker image are used. - If you supply a command but no args: The default EntryPoint and the default Cmd defined in the Docker image are ignored. Your command is run without any arguments. - If you supply only args: The default Entrypoint defined in the Docker image is run with the args that you supplied. - If you supply a command and args: The default Entrypoint and the default Cmd defined in the Docker image are ignored. Your command is run with your args. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.
	ContainerArgs []string `pulumi:"containerArgs"`
	// The command with which the replica's custom container is run. If provided, it will override default ENTRYPOINT of the docker image. If not provided, the docker image's ENTRYPOINT is used. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.
	ContainerCommand []string `pulumi:"containerCommand"`
	// Represents the configuration of disk options.
	DiskConfig GoogleCloudMlV1__DiskConfigResponse `pulumi:"diskConfig"`
	// The Docker image to run on the replica. This image must be in Container Registry. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	ImageUri string `pulumi:"imageUri"`
	// The AI Platform runtime version that includes a TensorFlow version matching the one used in the custom container. This field is required if the replica is a TPU worker that uses a custom container. Otherwise, do not specify this field. This must be a [runtime version that currently supports training with TPUs](/ml-engine/docs/tensorflow/runtime-version-list#tpu-support). Note that the version of TensorFlow included in a runtime version may differ from the numbering of the runtime version itself, because it may have a different [patch version](https://www.tensorflow.org/guide/version_compat#semantic_versioning_20). In this field, you must specify the runtime version (TensorFlow minor version). For example, if your custom container runs TensorFlow `1.x.y`, specify `1.x`.
	TpuTfVersion string `pulumi:"tpuTfVersion"`
}

Represents the configuration for a replica in a cluster.

type GoogleCloudMlV1__ReplicaConfigResponseOutput 

type GoogleCloudMlV1__ReplicaConfigResponseOutput struct{ *pulumi.OutputState }

Represents the configuration for a replica in a cluster.

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) AcceleratorConfig 

func (o GoogleCloudMlV1__ReplicaConfigResponseOutput) AcceleratorConfig() GoogleCloudMlV1__AcceleratorConfigResponseOutput

Represents the type and number of accelerators used by the replica. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu)

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) ContainerArgs 

func (o GoogleCloudMlV1__ReplicaConfigResponseOutput) ContainerArgs() pulumi.StringArrayOutput

Arguments to the entrypoint command. The following rules apply for container_command and container_args: - If you do not supply command or args: The defaults defined in the Docker image are used. - If you supply a command but no args: The default EntryPoint and the default Cmd defined in the Docker image are ignored. Your command is run without any arguments. - If you supply only args: The default Entrypoint defined in the Docker image is run with the args that you supplied. - If you supply a command and args: The default Entrypoint and the default Cmd defined in the Docker image are ignored. Your command is run with your args. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) ContainerCommand 

func (o GoogleCloudMlV1__ReplicaConfigResponseOutput) ContainerCommand() pulumi.StringArrayOutput

The command with which the replica's custom container is run. If provided, it will override default ENTRYPOINT of the docker image. If not provided, the docker image's ENTRYPOINT is used. It cannot be set if custom container image is not provided. Note that this field and [TrainingInput.args] are mutually exclusive, i.e., both cannot be set at the same time.

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) DiskConfig 

func (o GoogleCloudMlV1__ReplicaConfigResponseOutput) DiskConfig() GoogleCloudMlV1__DiskConfigResponseOutput

Represents the configuration of disk options.

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) ElementType 

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) ImageUri 

func (o GoogleCloudMlV1__ReplicaConfigResponseOutput) ImageUri() pulumi.StringOutput

The Docker image to run on the replica. This image must be in Container Registry. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) ToGoogleCloudMlV1__ReplicaConfigResponseOutput 

func (o GoogleCloudMlV1__ReplicaConfigResponseOutput) ToGoogleCloudMlV1__ReplicaConfigResponseOutput() GoogleCloudMlV1__ReplicaConfigResponseOutput

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) ToGoogleCloudMlV1__ReplicaConfigResponseOutputWithContext 

func (o GoogleCloudMlV1__ReplicaConfigResponseOutput) ToGoogleCloudMlV1__ReplicaConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__ReplicaConfigResponseOutput

func (GoogleCloudMlV1__ReplicaConfigResponseOutput) TpuTfVersion 

func (o GoogleCloudMlV1__ReplicaConfigResponseOutput) TpuTfVersion() pulumi.StringOutput

The AI Platform runtime version that includes a TensorFlow version matching the one used in the custom container. This field is required if the replica is a TPU worker that uses a custom container. Otherwise, do not specify this field. This must be a [runtime version that currently supports training with TPUs](/ml-engine/docs/tensorflow/runtime-version-list#tpu-support). Note that the version of TensorFlow included in a runtime version may differ from the numbering of the runtime version itself, because it may have a different [patch version](https://www.tensorflow.org/guide/version_compat#semantic_versioning_20). In this field, you must specify the runtime version (TensorFlow minor version). For example, if your custom container runs TensorFlow `1.x.y`, specify `1.x`.

type GoogleCloudMlV1__RequestLoggingConfig 

type GoogleCloudMlV1__RequestLoggingConfig struct {
	// Fully qualified BigQuery table name in the following format: " project_id.dataset_name.table_name" The specified table must already exist, and the "Cloud ML Service Agent" for your project must have permission to write to it. The table must have the following [schema](/bigquery/docs/schemas): Field nameType Mode model STRING REQUIRED model_version STRING REQUIRED time TIMESTAMP REQUIRED raw_data STRING REQUIRED raw_prediction STRING NULLABLE groundtruth STRING NULLABLE
	BigqueryTableName string `pulumi:"bigqueryTableName"`
	// Percentage of requests to be logged, expressed as a fraction from 0 to 1. For example, if you want to log 10% of requests, enter `0.1`. The sampling window is the lifetime of the model version. Defaults to 0.
	SamplingPercentage *float64 `pulumi:"samplingPercentage"`
}

Configuration for logging request-response pairs to a BigQuery table. Online prediction requests to a model version and the responses to these requests are converted to raw strings and saved to the specified BigQuery table. Logging is constrained by [BigQuery quotas and limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits, AI Platform Prediction does not log request-response pairs, but it continues to serve predictions. If you are using [continuous evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to specify this configuration manually. Setting up continuous evaluation automatically enables logging of request-response pairs.

type GoogleCloudMlV1__RequestLoggingConfigArgs 

type GoogleCloudMlV1__RequestLoggingConfigArgs struct {
	// Fully qualified BigQuery table name in the following format: " project_id.dataset_name.table_name" The specified table must already exist, and the "Cloud ML Service Agent" for your project must have permission to write to it. The table must have the following [schema](/bigquery/docs/schemas): Field nameType Mode model STRING REQUIRED model_version STRING REQUIRED time TIMESTAMP REQUIRED raw_data STRING REQUIRED raw_prediction STRING NULLABLE groundtruth STRING NULLABLE
	BigqueryTableName pulumi.StringInput `pulumi:"bigqueryTableName"`
	// Percentage of requests to be logged, expressed as a fraction from 0 to 1. For example, if you want to log 10% of requests, enter `0.1`. The sampling window is the lifetime of the model version. Defaults to 0.
	SamplingPercentage pulumi.Float64PtrInput `pulumi:"samplingPercentage"`
}

Configuration for logging request-response pairs to a BigQuery table. Online prediction requests to a model version and the responses to these requests are converted to raw strings and saved to the specified BigQuery table. Logging is constrained by [BigQuery quotas and limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits, AI Platform Prediction does not log request-response pairs, but it continues to serve predictions. If you are using [continuous evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to specify this configuration manually. Setting up continuous evaluation automatically enables logging of request-response pairs.

func (GoogleCloudMlV1__RequestLoggingConfigArgs) ElementType 

func (GoogleCloudMlV1__RequestLoggingConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__RequestLoggingConfigArgs) ToGoogleCloudMlV1__RequestLoggingConfigOutput 

func (i GoogleCloudMlV1__RequestLoggingConfigArgs) ToGoogleCloudMlV1__RequestLoggingConfigOutput() GoogleCloudMlV1__RequestLoggingConfigOutput

func (GoogleCloudMlV1__RequestLoggingConfigArgs) ToGoogleCloudMlV1__RequestLoggingConfigOutputWithContext 

func (i GoogleCloudMlV1__RequestLoggingConfigArgs) ToGoogleCloudMlV1__RequestLoggingConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__RequestLoggingConfigOutput

func (GoogleCloudMlV1__RequestLoggingConfigArgs) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutput 

func (i GoogleCloudMlV1__RequestLoggingConfigArgs) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutput() GoogleCloudMlV1__RequestLoggingConfigPtrOutput

func (GoogleCloudMlV1__RequestLoggingConfigArgs) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutputWithContext 

func (i GoogleCloudMlV1__RequestLoggingConfigArgs) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__RequestLoggingConfigPtrOutput

type GoogleCloudMlV1__RequestLoggingConfigInput 

type GoogleCloudMlV1__RequestLoggingConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__RequestLoggingConfigOutput() GoogleCloudMlV1__RequestLoggingConfigOutput
	ToGoogleCloudMlV1__RequestLoggingConfigOutputWithContext(context.Context) GoogleCloudMlV1__RequestLoggingConfigOutput
}

GoogleCloudMlV1__RequestLoggingConfigInput is an input type that accepts GoogleCloudMlV1__RequestLoggingConfigArgs and GoogleCloudMlV1__RequestLoggingConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1__RequestLoggingConfigInput` via: 

GoogleCloudMlV1__RequestLoggingConfigArgs{...}

type GoogleCloudMlV1__RequestLoggingConfigOutput 

type GoogleCloudMlV1__RequestLoggingConfigOutput struct{ *pulumi.OutputState }

Configuration for logging request-response pairs to a BigQuery table. Online prediction requests to a model version and the responses to these requests are converted to raw strings and saved to the specified BigQuery table. Logging is constrained by [BigQuery quotas and limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits, AI Platform Prediction does not log request-response pairs, but it continues to serve predictions. If you are using [continuous evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to specify this configuration manually. Setting up continuous evaluation automatically enables logging of request-response pairs.

func (GoogleCloudMlV1__RequestLoggingConfigOutput) BigqueryTableName 

func (o GoogleCloudMlV1__RequestLoggingConfigOutput) BigqueryTableName() pulumi.StringOutput

Fully qualified BigQuery table name in the following format: " project_id.dataset_name.table_name" The specified table must already exist, and the "Cloud ML Service Agent" for your project must have permission to write to it. The table must have the following [schema](/bigquery/docs/schemas): Field nameType Mode model STRING REQUIRED model_version STRING REQUIRED time TIMESTAMP REQUIRED raw_data STRING REQUIRED raw_prediction STRING NULLABLE groundtruth STRING NULLABLE

func (GoogleCloudMlV1__RequestLoggingConfigOutput) ElementType 

func (GoogleCloudMlV1__RequestLoggingConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__RequestLoggingConfigOutput) SamplingPercentage 

func (o GoogleCloudMlV1__RequestLoggingConfigOutput) SamplingPercentage() pulumi.Float64PtrOutput

Percentage of requests to be logged, expressed as a fraction from 0 to 1. For example, if you want to log 10% of requests, enter `0.1`. The sampling window is the lifetime of the model version. Defaults to 0.

func (GoogleCloudMlV1__RequestLoggingConfigOutput) ToGoogleCloudMlV1__RequestLoggingConfigOutput 

func (o GoogleCloudMlV1__RequestLoggingConfigOutput) ToGoogleCloudMlV1__RequestLoggingConfigOutput() GoogleCloudMlV1__RequestLoggingConfigOutput

func (GoogleCloudMlV1__RequestLoggingConfigOutput) ToGoogleCloudMlV1__RequestLoggingConfigOutputWithContext 

func (o GoogleCloudMlV1__RequestLoggingConfigOutput) ToGoogleCloudMlV1__RequestLoggingConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__RequestLoggingConfigOutput

func (GoogleCloudMlV1__RequestLoggingConfigOutput) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutput 

func (o GoogleCloudMlV1__RequestLoggingConfigOutput) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutput() GoogleCloudMlV1__RequestLoggingConfigPtrOutput

func (GoogleCloudMlV1__RequestLoggingConfigOutput) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__RequestLoggingConfigOutput) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__RequestLoggingConfigPtrOutput

type GoogleCloudMlV1__RequestLoggingConfigPtrInput 

type GoogleCloudMlV1__RequestLoggingConfigPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__RequestLoggingConfigPtrOutput() GoogleCloudMlV1__RequestLoggingConfigPtrOutput
	ToGoogleCloudMlV1__RequestLoggingConfigPtrOutputWithContext(context.Context) GoogleCloudMlV1__RequestLoggingConfigPtrOutput
}

GoogleCloudMlV1__RequestLoggingConfigPtrInput is an input type that accepts GoogleCloudMlV1__RequestLoggingConfigArgs, GoogleCloudMlV1__RequestLoggingConfigPtr and GoogleCloudMlV1__RequestLoggingConfigPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__RequestLoggingConfigPtrInput` via: 

        GoogleCloudMlV1__RequestLoggingConfigArgs{...}

or:

        nil

func GoogleCloudMlV1__RequestLoggingConfigPtr 

func GoogleCloudMlV1__RequestLoggingConfigPtr(v *GoogleCloudMlV1__RequestLoggingConfigArgs) GoogleCloudMlV1__RequestLoggingConfigPtrInput

type GoogleCloudMlV1__RequestLoggingConfigPtrOutput 

type GoogleCloudMlV1__RequestLoggingConfigPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__RequestLoggingConfigPtrOutput) BigqueryTableName 

func (o GoogleCloudMlV1__RequestLoggingConfigPtrOutput) BigqueryTableName() pulumi.StringPtrOutput

Fully qualified BigQuery table name in the following format: " project_id.dataset_name.table_name" The specified table must already exist, and the "Cloud ML Service Agent" for your project must have permission to write to it. The table must have the following [schema](/bigquery/docs/schemas): Field nameType Mode model STRING REQUIRED model_version STRING REQUIRED time TIMESTAMP REQUIRED raw_data STRING REQUIRED raw_prediction STRING NULLABLE groundtruth STRING NULLABLE

func (GoogleCloudMlV1__RequestLoggingConfigPtrOutput) Elem 

func (o GoogleCloudMlV1__RequestLoggingConfigPtrOutput) Elem() GoogleCloudMlV1__RequestLoggingConfigOutput

func (GoogleCloudMlV1__RequestLoggingConfigPtrOutput) ElementType 

func (GoogleCloudMlV1__RequestLoggingConfigPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__RequestLoggingConfigPtrOutput) SamplingPercentage 

func (o GoogleCloudMlV1__RequestLoggingConfigPtrOutput) SamplingPercentage() pulumi.Float64PtrOutput

Percentage of requests to be logged, expressed as a fraction from 0 to 1. For example, if you want to log 10% of requests, enter `0.1`. The sampling window is the lifetime of the model version. Defaults to 0.

func (GoogleCloudMlV1__RequestLoggingConfigPtrOutput) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutput 

func (o GoogleCloudMlV1__RequestLoggingConfigPtrOutput) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutput() GoogleCloudMlV1__RequestLoggingConfigPtrOutput

func (GoogleCloudMlV1__RequestLoggingConfigPtrOutput) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutputWithContext 

func (o GoogleCloudMlV1__RequestLoggingConfigPtrOutput) ToGoogleCloudMlV1__RequestLoggingConfigPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__RequestLoggingConfigPtrOutput

type GoogleCloudMlV1__RequestLoggingConfigResponse 

type GoogleCloudMlV1__RequestLoggingConfigResponse struct {
	// Fully qualified BigQuery table name in the following format: " project_id.dataset_name.table_name" The specified table must already exist, and the "Cloud ML Service Agent" for your project must have permission to write to it. The table must have the following [schema](/bigquery/docs/schemas): Field nameType Mode model STRING REQUIRED model_version STRING REQUIRED time TIMESTAMP REQUIRED raw_data STRING REQUIRED raw_prediction STRING NULLABLE groundtruth STRING NULLABLE
	BigqueryTableName string `pulumi:"bigqueryTableName"`
	// Percentage of requests to be logged, expressed as a fraction from 0 to 1. For example, if you want to log 10% of requests, enter `0.1`. The sampling window is the lifetime of the model version. Defaults to 0.
	SamplingPercentage float64 `pulumi:"samplingPercentage"`
}

Configuration for logging request-response pairs to a BigQuery table. Online prediction requests to a model version and the responses to these requests are converted to raw strings and saved to the specified BigQuery table. Logging is constrained by [BigQuery quotas and limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits, AI Platform Prediction does not log request-response pairs, but it continues to serve predictions. If you are using [continuous evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to specify this configuration manually. Setting up continuous evaluation automatically enables logging of request-response pairs.

type GoogleCloudMlV1__RequestLoggingConfigResponseOutput 

type GoogleCloudMlV1__RequestLoggingConfigResponseOutput struct{ *pulumi.OutputState }

Configuration for logging request-response pairs to a BigQuery table. Online prediction requests to a model version and the responses to these requests are converted to raw strings and saved to the specified BigQuery table. Logging is constrained by [BigQuery quotas and limits](/bigquery/quotas). If your project exceeds BigQuery quotas or limits, AI Platform Prediction does not log request-response pairs, but it continues to serve predictions. If you are using [continuous evaluation](/ml-engine/docs/continuous-evaluation/), you do not need to specify this configuration manually. Setting up continuous evaluation automatically enables logging of request-response pairs.

func (GoogleCloudMlV1__RequestLoggingConfigResponseOutput) BigqueryTableName 

func (o GoogleCloudMlV1__RequestLoggingConfigResponseOutput) BigqueryTableName() pulumi.StringOutput

Fully qualified BigQuery table name in the following format: " project_id.dataset_name.table_name" The specified table must already exist, and the "Cloud ML Service Agent" for your project must have permission to write to it. The table must have the following [schema](/bigquery/docs/schemas): Field nameType Mode model STRING REQUIRED model_version STRING REQUIRED time TIMESTAMP REQUIRED raw_data STRING REQUIRED raw_prediction STRING NULLABLE groundtruth STRING NULLABLE

func (GoogleCloudMlV1__RequestLoggingConfigResponseOutput) ElementType 

func (GoogleCloudMlV1__RequestLoggingConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__RequestLoggingConfigResponseOutput) SamplingPercentage 

func (o GoogleCloudMlV1__RequestLoggingConfigResponseOutput) SamplingPercentage() pulumi.Float64Output

Percentage of requests to be logged, expressed as a fraction from 0 to 1. For example, if you want to log 10% of requests, enter `0.1`. The sampling window is the lifetime of the model version. Defaults to 0.

func (GoogleCloudMlV1__RequestLoggingConfigResponseOutput) ToGoogleCloudMlV1__RequestLoggingConfigResponseOutput 

func (o GoogleCloudMlV1__RequestLoggingConfigResponseOutput) ToGoogleCloudMlV1__RequestLoggingConfigResponseOutput() GoogleCloudMlV1__RequestLoggingConfigResponseOutput

func (GoogleCloudMlV1__RequestLoggingConfigResponseOutput) ToGoogleCloudMlV1__RequestLoggingConfigResponseOutputWithContext 

func (o GoogleCloudMlV1__RequestLoggingConfigResponseOutput) ToGoogleCloudMlV1__RequestLoggingConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__RequestLoggingConfigResponseOutput

type GoogleCloudMlV1__RouteMap 

type GoogleCloudMlV1__RouteMap struct {
	// HTTP path on the container to send health checkss to. AI Platform Prediction intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](/ai-platform/prediction/docs/custom-container-requirements#checks). For example, if you set this field to `/bar`, then AI Platform Prediction intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/ MODEL/versions/VERSION The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID /models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.
	Health *string `pulumi:"health"`
	// HTTP path on the container to send prediction requests to. AI Platform Prediction forwards requests sent using projects.predict to this path on the container's IP address and port. AI Platform Prediction then returns the container's response in the API response. For example, if you set this field to `/foo`, then when AI Platform Prediction receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/MODEL/versions/VERSION:predict The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID/models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.
	Predict *string `pulumi:"predict"`
}

Specifies HTTP paths served by a custom container. AI Platform Prediction sends requests to these paths on the container; the custom container must run an HTTP server that responds to these requests with appropriate responses. Read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements) for details on how to create your container image to meet these requirements.

type GoogleCloudMlV1__RouteMapArgs 

type GoogleCloudMlV1__RouteMapArgs struct {
	// HTTP path on the container to send health checkss to. AI Platform Prediction intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](/ai-platform/prediction/docs/custom-container-requirements#checks). For example, if you set this field to `/bar`, then AI Platform Prediction intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/ MODEL/versions/VERSION The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID /models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.
	Health pulumi.StringPtrInput `pulumi:"health"`
	// HTTP path on the container to send prediction requests to. AI Platform Prediction forwards requests sent using projects.predict to this path on the container's IP address and port. AI Platform Prediction then returns the container's response in the API response. For example, if you set this field to `/foo`, then when AI Platform Prediction receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/MODEL/versions/VERSION:predict The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID/models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.
	Predict pulumi.StringPtrInput `pulumi:"predict"`
}

Specifies HTTP paths served by a custom container. AI Platform Prediction sends requests to these paths on the container; the custom container must run an HTTP server that responds to these requests with appropriate responses. Read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements) for details on how to create your container image to meet these requirements.

func (GoogleCloudMlV1__RouteMapArgs) ElementType 

func (GoogleCloudMlV1__RouteMapArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__RouteMapArgs) ToGoogleCloudMlV1__RouteMapOutput 

func (i GoogleCloudMlV1__RouteMapArgs) ToGoogleCloudMlV1__RouteMapOutput() GoogleCloudMlV1__RouteMapOutput

func (GoogleCloudMlV1__RouteMapArgs) ToGoogleCloudMlV1__RouteMapOutputWithContext 

func (i GoogleCloudMlV1__RouteMapArgs) ToGoogleCloudMlV1__RouteMapOutputWithContext(ctx context.Context) GoogleCloudMlV1__RouteMapOutput

func (GoogleCloudMlV1__RouteMapArgs) ToGoogleCloudMlV1__RouteMapPtrOutput 

func (i GoogleCloudMlV1__RouteMapArgs) ToGoogleCloudMlV1__RouteMapPtrOutput() GoogleCloudMlV1__RouteMapPtrOutput

func (GoogleCloudMlV1__RouteMapArgs) ToGoogleCloudMlV1__RouteMapPtrOutputWithContext 

func (i GoogleCloudMlV1__RouteMapArgs) ToGoogleCloudMlV1__RouteMapPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__RouteMapPtrOutput

type GoogleCloudMlV1__RouteMapInput 

type GoogleCloudMlV1__RouteMapInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__RouteMapOutput() GoogleCloudMlV1__RouteMapOutput
	ToGoogleCloudMlV1__RouteMapOutputWithContext(context.Context) GoogleCloudMlV1__RouteMapOutput
}

GoogleCloudMlV1__RouteMapInput is an input type that accepts GoogleCloudMlV1__RouteMap and GoogleCloudMlV1__RouteMapOutput values. You can construct a concrete instance of `GoogleCloudMlV1__RouteMapInput` via: 

GoogleCloudMlV1__RouteMap{ "key": GoogleCloudMlV1__RouteArgs{...} }

type GoogleCloudMlV1__RouteMapOutput 

type GoogleCloudMlV1__RouteMapOutput struct{ *pulumi.OutputState }

Specifies HTTP paths served by a custom container. AI Platform Prediction sends requests to these paths on the container; the custom container must run an HTTP server that responds to these requests with appropriate responses. Read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements) for details on how to create your container image to meet these requirements.

func (GoogleCloudMlV1__RouteMapOutput) ElementType 

func (GoogleCloudMlV1__RouteMapOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__RouteMapOutput) Health 

func (o GoogleCloudMlV1__RouteMapOutput) Health() pulumi.StringPtrOutput

HTTP path on the container to send health checkss to. AI Platform Prediction intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](/ai-platform/prediction/docs/custom-container-requirements#checks). For example, if you set this field to `/bar`, then AI Platform Prediction intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/ MODEL/versions/VERSION The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID /models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.

func (GoogleCloudMlV1__RouteMapOutput) Predict 

func (o GoogleCloudMlV1__RouteMapOutput) Predict() pulumi.StringPtrOutput

HTTP path on the container to send prediction requests to. AI Platform Prediction forwards requests sent using projects.predict to this path on the container's IP address and port. AI Platform Prediction then returns the container's response in the API response. For example, if you set this field to `/foo`, then when AI Platform Prediction receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/MODEL/versions/VERSION:predict The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID/models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.

func (GoogleCloudMlV1__RouteMapOutput) ToGoogleCloudMlV1__RouteMapOutput 

func (o GoogleCloudMlV1__RouteMapOutput) ToGoogleCloudMlV1__RouteMapOutput() GoogleCloudMlV1__RouteMapOutput

func (GoogleCloudMlV1__RouteMapOutput) ToGoogleCloudMlV1__RouteMapOutputWithContext 

func (o GoogleCloudMlV1__RouteMapOutput) ToGoogleCloudMlV1__RouteMapOutputWithContext(ctx context.Context) GoogleCloudMlV1__RouteMapOutput

func (GoogleCloudMlV1__RouteMapOutput) ToGoogleCloudMlV1__RouteMapPtrOutput 

func (o GoogleCloudMlV1__RouteMapOutput) ToGoogleCloudMlV1__RouteMapPtrOutput() GoogleCloudMlV1__RouteMapPtrOutput

func (GoogleCloudMlV1__RouteMapOutput) ToGoogleCloudMlV1__RouteMapPtrOutputWithContext 

func (o GoogleCloudMlV1__RouteMapOutput) ToGoogleCloudMlV1__RouteMapPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__RouteMapPtrOutput

type GoogleCloudMlV1__RouteMapPtrInput 

type GoogleCloudMlV1__RouteMapPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__RouteMapPtrOutput() GoogleCloudMlV1__RouteMapPtrOutput
	ToGoogleCloudMlV1__RouteMapPtrOutputWithContext(context.Context) GoogleCloudMlV1__RouteMapPtrOutput
}

GoogleCloudMlV1__RouteMapPtrInput is an input type that accepts GoogleCloudMlV1__RouteMapArgs, GoogleCloudMlV1__RouteMapPtr and GoogleCloudMlV1__RouteMapPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__RouteMapPtrInput` via: 

        GoogleCloudMlV1__RouteMapArgs{...}

or:

        nil

func GoogleCloudMlV1__RouteMapPtr 

func GoogleCloudMlV1__RouteMapPtr(v *GoogleCloudMlV1__RouteMapArgs) GoogleCloudMlV1__RouteMapPtrInput

type GoogleCloudMlV1__RouteMapPtrOutput 

type GoogleCloudMlV1__RouteMapPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__RouteMapPtrOutput) Elem 

func (o GoogleCloudMlV1__RouteMapPtrOutput) Elem() GoogleCloudMlV1__RouteMapOutput

func (GoogleCloudMlV1__RouteMapPtrOutput) ElementType 

func (GoogleCloudMlV1__RouteMapPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__RouteMapPtrOutput) Health 

func (o GoogleCloudMlV1__RouteMapPtrOutput) Health() pulumi.StringPtrOutput

HTTP path on the container to send health checkss to. AI Platform Prediction intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](/ai-platform/prediction/docs/custom-container-requirements#checks). For example, if you set this field to `/bar`, then AI Platform Prediction intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/ MODEL/versions/VERSION The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID /models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.

func (GoogleCloudMlV1__RouteMapPtrOutput) Predict 

func (o GoogleCloudMlV1__RouteMapPtrOutput) Predict() pulumi.StringPtrOutput

HTTP path on the container to send prediction requests to. AI Platform Prediction forwards requests sent using projects.predict to this path on the container's IP address and port. AI Platform Prediction then returns the container's response in the API response. For example, if you set this field to `/foo`, then when AI Platform Prediction receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/MODEL/versions/VERSION:predict The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID/models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.

func (GoogleCloudMlV1__RouteMapPtrOutput) ToGoogleCloudMlV1__RouteMapPtrOutput 

func (o GoogleCloudMlV1__RouteMapPtrOutput) ToGoogleCloudMlV1__RouteMapPtrOutput() GoogleCloudMlV1__RouteMapPtrOutput

func (GoogleCloudMlV1__RouteMapPtrOutput) ToGoogleCloudMlV1__RouteMapPtrOutputWithContext 

func (o GoogleCloudMlV1__RouteMapPtrOutput) ToGoogleCloudMlV1__RouteMapPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__RouteMapPtrOutput

type GoogleCloudMlV1__RouteMapResponse 

type GoogleCloudMlV1__RouteMapResponse struct {
	// HTTP path on the container to send health checkss to. AI Platform Prediction intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](/ai-platform/prediction/docs/custom-container-requirements#checks). For example, if you set this field to `/bar`, then AI Platform Prediction intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/ MODEL/versions/VERSION The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID /models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.
	Health string `pulumi:"health"`
	// HTTP path on the container to send prediction requests to. AI Platform Prediction forwards requests sent using projects.predict to this path on the container's IP address and port. AI Platform Prediction then returns the container's response in the API response. For example, if you set this field to `/foo`, then when AI Platform Prediction receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/MODEL/versions/VERSION:predict The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID/models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.
	Predict string `pulumi:"predict"`
}

Specifies HTTP paths served by a custom container. AI Platform Prediction sends requests to these paths on the container; the custom container must run an HTTP server that responds to these requests with appropriate responses. Read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements) for details on how to create your container image to meet these requirements.

type GoogleCloudMlV1__RouteMapResponseOutput 

type GoogleCloudMlV1__RouteMapResponseOutput struct{ *pulumi.OutputState }

Specifies HTTP paths served by a custom container. AI Platform Prediction sends requests to these paths on the container; the custom container must run an HTTP server that responds to these requests with appropriate responses. Read [Custom container requirements](/ai-platform/prediction/docs/custom-container-requirements) for details on how to create your container image to meet these requirements.

func (GoogleCloudMlV1__RouteMapResponseOutput) ElementType 

func (GoogleCloudMlV1__RouteMapResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__RouteMapResponseOutput) Health 

func (o GoogleCloudMlV1__RouteMapResponseOutput) Health() pulumi.StringOutput

HTTP path on the container to send health checkss to. AI Platform Prediction intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](/ai-platform/prediction/docs/custom-container-requirements#checks). For example, if you set this field to `/bar`, then AI Platform Prediction intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/ MODEL/versions/VERSION The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID /models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.

func (GoogleCloudMlV1__RouteMapResponseOutput) Predict 

func (o GoogleCloudMlV1__RouteMapResponseOutput) Predict() pulumi.StringOutput

HTTP path on the container to send prediction requests to. AI Platform Prediction forwards requests sent using projects.predict to this path on the container's IP address and port. AI Platform Prediction then returns the container's response in the API response. For example, if you set this field to `/foo`, then when AI Platform Prediction receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of Version.container.ports. If you don't specify this field, it defaults to the following value: /v1/models/MODEL/versions/VERSION:predict The placeholders in this value are replaced as follows: * MODEL: The name of the parent Model. This does not include the "projects/PROJECT_ID/models/" prefix that the API returns in output; it is the bare model name, as provided to projects.models.create. * VERSION: The name of the model version. This does not include the "projects/PROJECT_ID/models/MODEL/versions/" prefix that the API returns in output; it is the bare version name, as provided to projects.models.versions.create.

func (GoogleCloudMlV1__RouteMapResponseOutput) ToGoogleCloudMlV1__RouteMapResponseOutput 

func (o GoogleCloudMlV1__RouteMapResponseOutput) ToGoogleCloudMlV1__RouteMapResponseOutput() GoogleCloudMlV1__RouteMapResponseOutput

func (GoogleCloudMlV1__RouteMapResponseOutput) ToGoogleCloudMlV1__RouteMapResponseOutputWithContext 

func (o GoogleCloudMlV1__RouteMapResponseOutput) ToGoogleCloudMlV1__RouteMapResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__RouteMapResponseOutput

type GoogleCloudMlV1__SampledShapleyAttribution 

type GoogleCloudMlV1__SampledShapleyAttribution struct {
	// The number of feature permutations to consider when approximating the Shapley values.
	NumPaths *int `pulumi:"numPaths"`
}

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

type GoogleCloudMlV1__SampledShapleyAttributionArgs 

type GoogleCloudMlV1__SampledShapleyAttributionArgs struct {
	// The number of feature permutations to consider when approximating the Shapley values.
	NumPaths pulumi.IntPtrInput `pulumi:"numPaths"`
}

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

func (GoogleCloudMlV1__SampledShapleyAttributionArgs) ElementType 

func (GoogleCloudMlV1__SampledShapleyAttributionArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__SampledShapleyAttributionArgs) ToGoogleCloudMlV1__SampledShapleyAttributionOutput 

func (i GoogleCloudMlV1__SampledShapleyAttributionArgs) ToGoogleCloudMlV1__SampledShapleyAttributionOutput() GoogleCloudMlV1__SampledShapleyAttributionOutput

func (GoogleCloudMlV1__SampledShapleyAttributionArgs) ToGoogleCloudMlV1__SampledShapleyAttributionOutputWithContext 

func (i GoogleCloudMlV1__SampledShapleyAttributionArgs) ToGoogleCloudMlV1__SampledShapleyAttributionOutputWithContext(ctx context.Context) GoogleCloudMlV1__SampledShapleyAttributionOutput

func (GoogleCloudMlV1__SampledShapleyAttributionArgs) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutput 

func (i GoogleCloudMlV1__SampledShapleyAttributionArgs) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutput() GoogleCloudMlV1__SampledShapleyAttributionPtrOutput

func (GoogleCloudMlV1__SampledShapleyAttributionArgs) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutputWithContext 

func (i GoogleCloudMlV1__SampledShapleyAttributionArgs) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__SampledShapleyAttributionPtrOutput

type GoogleCloudMlV1__SampledShapleyAttributionInput 

type GoogleCloudMlV1__SampledShapleyAttributionInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__SampledShapleyAttributionOutput() GoogleCloudMlV1__SampledShapleyAttributionOutput
	ToGoogleCloudMlV1__SampledShapleyAttributionOutputWithContext(context.Context) GoogleCloudMlV1__SampledShapleyAttributionOutput
}

GoogleCloudMlV1__SampledShapleyAttributionInput is an input type that accepts GoogleCloudMlV1__SampledShapleyAttributionArgs and GoogleCloudMlV1__SampledShapleyAttributionOutput values. You can construct a concrete instance of `GoogleCloudMlV1__SampledShapleyAttributionInput` via: 

GoogleCloudMlV1__SampledShapleyAttributionArgs{...}

type GoogleCloudMlV1__SampledShapleyAttributionOutput 

type GoogleCloudMlV1__SampledShapleyAttributionOutput struct{ *pulumi.OutputState }

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

func (GoogleCloudMlV1__SampledShapleyAttributionOutput) ElementType 

func (GoogleCloudMlV1__SampledShapleyAttributionOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__SampledShapleyAttributionOutput) NumPaths 

func (o GoogleCloudMlV1__SampledShapleyAttributionOutput) NumPaths() pulumi.IntPtrOutput

The number of feature permutations to consider when approximating the Shapley values.

func (GoogleCloudMlV1__SampledShapleyAttributionOutput) ToGoogleCloudMlV1__SampledShapleyAttributionOutput 

func (o GoogleCloudMlV1__SampledShapleyAttributionOutput) ToGoogleCloudMlV1__SampledShapleyAttributionOutput() GoogleCloudMlV1__SampledShapleyAttributionOutput

func (GoogleCloudMlV1__SampledShapleyAttributionOutput) ToGoogleCloudMlV1__SampledShapleyAttributionOutputWithContext 

func (o GoogleCloudMlV1__SampledShapleyAttributionOutput) ToGoogleCloudMlV1__SampledShapleyAttributionOutputWithContext(ctx context.Context) GoogleCloudMlV1__SampledShapleyAttributionOutput

func (GoogleCloudMlV1__SampledShapleyAttributionOutput) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutput 

func (o GoogleCloudMlV1__SampledShapleyAttributionOutput) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutput() GoogleCloudMlV1__SampledShapleyAttributionPtrOutput

func (GoogleCloudMlV1__SampledShapleyAttributionOutput) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutputWithContext 

func (o GoogleCloudMlV1__SampledShapleyAttributionOutput) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__SampledShapleyAttributionPtrOutput

type GoogleCloudMlV1__SampledShapleyAttributionPtrInput 

type GoogleCloudMlV1__SampledShapleyAttributionPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutput() GoogleCloudMlV1__SampledShapleyAttributionPtrOutput
	ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutputWithContext(context.Context) GoogleCloudMlV1__SampledShapleyAttributionPtrOutput
}

GoogleCloudMlV1__SampledShapleyAttributionPtrInput is an input type that accepts GoogleCloudMlV1__SampledShapleyAttributionArgs, GoogleCloudMlV1__SampledShapleyAttributionPtr and GoogleCloudMlV1__SampledShapleyAttributionPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__SampledShapleyAttributionPtrInput` via: 

        GoogleCloudMlV1__SampledShapleyAttributionArgs{...}

or:

        nil

func GoogleCloudMlV1__SampledShapleyAttributionPtr 

func GoogleCloudMlV1__SampledShapleyAttributionPtr(v *GoogleCloudMlV1__SampledShapleyAttributionArgs) GoogleCloudMlV1__SampledShapleyAttributionPtrInput

type GoogleCloudMlV1__SampledShapleyAttributionPtrOutput 

type GoogleCloudMlV1__SampledShapleyAttributionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) Elem 

func (o GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) Elem() GoogleCloudMlV1__SampledShapleyAttributionOutput

func (GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) ElementType 

func (GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) NumPaths 

func (o GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) NumPaths() pulumi.IntPtrOutput

The number of feature permutations to consider when approximating the Shapley values.

func (GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutput 

func (o GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutput() GoogleCloudMlV1__SampledShapleyAttributionPtrOutput

func (GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutputWithContext 

func (o GoogleCloudMlV1__SampledShapleyAttributionPtrOutput) ToGoogleCloudMlV1__SampledShapleyAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__SampledShapleyAttributionPtrOutput

type GoogleCloudMlV1__SampledShapleyAttributionResponse 

type GoogleCloudMlV1__SampledShapleyAttributionResponse struct {
	// The number of feature permutations to consider when approximating the Shapley values.
	NumPaths int `pulumi:"numPaths"`
}

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

type GoogleCloudMlV1__SampledShapleyAttributionResponseOutput 

type GoogleCloudMlV1__SampledShapleyAttributionResponseOutput struct{ *pulumi.OutputState }

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

func (GoogleCloudMlV1__SampledShapleyAttributionResponseOutput) ElementType 

func (GoogleCloudMlV1__SampledShapleyAttributionResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__SampledShapleyAttributionResponseOutput) NumPaths 

func (o GoogleCloudMlV1__SampledShapleyAttributionResponseOutput) NumPaths() pulumi.IntOutput

The number of feature permutations to consider when approximating the Shapley values.

func (GoogleCloudMlV1__SampledShapleyAttributionResponseOutput) ToGoogleCloudMlV1__SampledShapleyAttributionResponseOutput 

func (o GoogleCloudMlV1__SampledShapleyAttributionResponseOutput) ToGoogleCloudMlV1__SampledShapleyAttributionResponseOutput() GoogleCloudMlV1__SampledShapleyAttributionResponseOutput

func (GoogleCloudMlV1__SampledShapleyAttributionResponseOutput) ToGoogleCloudMlV1__SampledShapleyAttributionResponseOutputWithContext 

func (o GoogleCloudMlV1__SampledShapleyAttributionResponseOutput) ToGoogleCloudMlV1__SampledShapleyAttributionResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__SampledShapleyAttributionResponseOutput

type GoogleCloudMlV1__Scheduling 

type GoogleCloudMlV1__Scheduling struct {
	// Optional. The maximum job running time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, this field defaults to `604800s` (seven days). If the training job is still running after this duration, AI Platform Training cancels it. The duration is measured from when the job enters the `RUNNING` state; therefore it does not overlap with the duration limited by Scheduling.max_wait_time. For example, if you want to ensure your job runs for no more than 2 hours, set this field to `7200s` (2 hours * 60 minutes / hour * 60 seconds / minute). If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: “` yaml trainingInput: scheduling: maxRunningTime: 7200s  “`
	MaxRunningTime *string `pulumi:"maxRunningTime"`
	// Optional. The maximum job wait time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, there is no limit to the wait time. The minimum for this field is `1800s` (30 minutes). If the training job has not entered the `RUNNING` state after this duration, AI Platform Training cancels it. After the job begins running, it can no longer be cancelled due to the maximum wait time. Therefore the duration limited by this field does not overlap with the duration limited by Scheduling.max_running_time. For example, if the job temporarily stops running and retries due to a [VM restart](/ai-platform/training/docs/overview#restarts), this cannot lead to a maximum wait time cancellation. However, independently of this constraint, AI Platform Training might stop a job if there are too many retries due to exhausted resources in a region. The following example describes how you might use this field: To cancel your job if it doesn't start running within 1 hour, set this field to `3600s` (1 hour * 60 minutes / hour * 60 seconds / minute). If the job is still in the `QUEUED` or `PREPARING` state after an hour of waiting, AI Platform Training cancels the job. If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: “` yaml trainingInput: scheduling: maxWaitTime: 3600s  “`
	MaxWaitTime *string `pulumi:"maxWaitTime"`
	// Optional. Job scheduling will be based on this priority, which in the range [0, 1000]. The bigger the number, the higher the priority. Default to 0 if not set. If there are multiple jobs requesting same type of accelerators, the high priority job will be scheduled prior to ones with low priority.
	Priority *int `pulumi:"priority"`
}

All parameters related to scheduling of training jobs.

type GoogleCloudMlV1__SchedulingArgs 

type GoogleCloudMlV1__SchedulingArgs struct {
	// Optional. The maximum job running time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, this field defaults to `604800s` (seven days). If the training job is still running after this duration, AI Platform Training cancels it. The duration is measured from when the job enters the `RUNNING` state; therefore it does not overlap with the duration limited by Scheduling.max_wait_time. For example, if you want to ensure your job runs for no more than 2 hours, set this field to `7200s` (2 hours * 60 minutes / hour * 60 seconds / minute). If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: “` yaml trainingInput: scheduling: maxRunningTime: 7200s  “`
	MaxRunningTime pulumi.StringPtrInput `pulumi:"maxRunningTime"`
	// Optional. The maximum job wait time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, there is no limit to the wait time. The minimum for this field is `1800s` (30 minutes). If the training job has not entered the `RUNNING` state after this duration, AI Platform Training cancels it. After the job begins running, it can no longer be cancelled due to the maximum wait time. Therefore the duration limited by this field does not overlap with the duration limited by Scheduling.max_running_time. For example, if the job temporarily stops running and retries due to a [VM restart](/ai-platform/training/docs/overview#restarts), this cannot lead to a maximum wait time cancellation. However, independently of this constraint, AI Platform Training might stop a job if there are too many retries due to exhausted resources in a region. The following example describes how you might use this field: To cancel your job if it doesn't start running within 1 hour, set this field to `3600s` (1 hour * 60 minutes / hour * 60 seconds / minute). If the job is still in the `QUEUED` or `PREPARING` state after an hour of waiting, AI Platform Training cancels the job. If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: “` yaml trainingInput: scheduling: maxWaitTime: 3600s  “`
	MaxWaitTime pulumi.StringPtrInput `pulumi:"maxWaitTime"`
	// Optional. Job scheduling will be based on this priority, which in the range [0, 1000]. The bigger the number, the higher the priority. Default to 0 if not set. If there are multiple jobs requesting same type of accelerators, the high priority job will be scheduled prior to ones with low priority.
	Priority pulumi.IntPtrInput `pulumi:"priority"`
}

All parameters related to scheduling of training jobs.

func (GoogleCloudMlV1__SchedulingArgs) ElementType 

func (GoogleCloudMlV1__SchedulingArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__SchedulingArgs) ToGoogleCloudMlV1__SchedulingOutput 

func (i GoogleCloudMlV1__SchedulingArgs) ToGoogleCloudMlV1__SchedulingOutput() GoogleCloudMlV1__SchedulingOutput

func (GoogleCloudMlV1__SchedulingArgs) ToGoogleCloudMlV1__SchedulingOutputWithContext 

func (i GoogleCloudMlV1__SchedulingArgs) ToGoogleCloudMlV1__SchedulingOutputWithContext(ctx context.Context) GoogleCloudMlV1__SchedulingOutput

func (GoogleCloudMlV1__SchedulingArgs) ToGoogleCloudMlV1__SchedulingPtrOutput 

func (i GoogleCloudMlV1__SchedulingArgs) ToGoogleCloudMlV1__SchedulingPtrOutput() GoogleCloudMlV1__SchedulingPtrOutput

func (GoogleCloudMlV1__SchedulingArgs) ToGoogleCloudMlV1__SchedulingPtrOutputWithContext 

func (i GoogleCloudMlV1__SchedulingArgs) ToGoogleCloudMlV1__SchedulingPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__SchedulingPtrOutput

type GoogleCloudMlV1__SchedulingInput 

type GoogleCloudMlV1__SchedulingInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__SchedulingOutput() GoogleCloudMlV1__SchedulingOutput
	ToGoogleCloudMlV1__SchedulingOutputWithContext(context.Context) GoogleCloudMlV1__SchedulingOutput
}

GoogleCloudMlV1__SchedulingInput is an input type that accepts GoogleCloudMlV1__SchedulingArgs and GoogleCloudMlV1__SchedulingOutput values. You can construct a concrete instance of `GoogleCloudMlV1__SchedulingInput` via: 

GoogleCloudMlV1__SchedulingArgs{...}

type GoogleCloudMlV1__SchedulingOutput 

type GoogleCloudMlV1__SchedulingOutput struct{ *pulumi.OutputState }

All parameters related to scheduling of training jobs.

func (GoogleCloudMlV1__SchedulingOutput) ElementType 

func (GoogleCloudMlV1__SchedulingOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__SchedulingOutput) MaxRunningTime 

func (o GoogleCloudMlV1__SchedulingOutput) MaxRunningTime() pulumi.StringPtrOutput

Optional. The maximum job running time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, this field defaults to `604800s` (seven days). If the training job is still running after this duration, AI Platform Training cancels it. The duration is measured from when the job enters the `RUNNING` state; therefore it does not overlap with the duration limited by Scheduling.max_wait_time. For example, if you want to ensure your job runs for no more than 2 hours, set this field to `7200s` (2 hours * 60 minutes / hour * 60 seconds / minute). If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: ``` yaml trainingInput: scheduling: maxRunningTime: 7200s ```

func (GoogleCloudMlV1__SchedulingOutput) MaxWaitTime 

func (o GoogleCloudMlV1__SchedulingOutput) MaxWaitTime() pulumi.StringPtrOutput

Optional. The maximum job wait time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, there is no limit to the wait time. The minimum for this field is `1800s` (30 minutes). If the training job has not entered the `RUNNING` state after this duration, AI Platform Training cancels it. After the job begins running, it can no longer be cancelled due to the maximum wait time. Therefore the duration limited by this field does not overlap with the duration limited by Scheduling.max_running_time. For example, if the job temporarily stops running and retries due to a [VM restart](/ai-platform/training/docs/overview#restarts), this cannot lead to a maximum wait time cancellation. However, independently of this constraint, AI Platform Training might stop a job if there are too many retries due to exhausted resources in a region. The following example describes how you might use this field: To cancel your job if it doesn't start running within 1 hour, set this field to `3600s` (1 hour * 60 minutes / hour * 60 seconds / minute). If the job is still in the `QUEUED` or `PREPARING` state after an hour of waiting, AI Platform Training cancels the job. If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: ``` yaml trainingInput: scheduling: maxWaitTime: 3600s ```

func (GoogleCloudMlV1__SchedulingOutput) Priority added in v0.6.0 

func (o GoogleCloudMlV1__SchedulingOutput) Priority() pulumi.IntPtrOutput

Optional. Job scheduling will be based on this priority, which in the range [0, 1000]. The bigger the number, the higher the priority. Default to 0 if not set. If there are multiple jobs requesting same type of accelerators, the high priority job will be scheduled prior to ones with low priority.

func (GoogleCloudMlV1__SchedulingOutput) ToGoogleCloudMlV1__SchedulingOutput 

func (o GoogleCloudMlV1__SchedulingOutput) ToGoogleCloudMlV1__SchedulingOutput() GoogleCloudMlV1__SchedulingOutput

func (GoogleCloudMlV1__SchedulingOutput) ToGoogleCloudMlV1__SchedulingOutputWithContext 

func (o GoogleCloudMlV1__SchedulingOutput) ToGoogleCloudMlV1__SchedulingOutputWithContext(ctx context.Context) GoogleCloudMlV1__SchedulingOutput

func (GoogleCloudMlV1__SchedulingOutput) ToGoogleCloudMlV1__SchedulingPtrOutput 

func (o GoogleCloudMlV1__SchedulingOutput) ToGoogleCloudMlV1__SchedulingPtrOutput() GoogleCloudMlV1__SchedulingPtrOutput

func (GoogleCloudMlV1__SchedulingOutput) ToGoogleCloudMlV1__SchedulingPtrOutputWithContext 

func (o GoogleCloudMlV1__SchedulingOutput) ToGoogleCloudMlV1__SchedulingPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__SchedulingPtrOutput

type GoogleCloudMlV1__SchedulingPtrInput 

type GoogleCloudMlV1__SchedulingPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__SchedulingPtrOutput() GoogleCloudMlV1__SchedulingPtrOutput
	ToGoogleCloudMlV1__SchedulingPtrOutputWithContext(context.Context) GoogleCloudMlV1__SchedulingPtrOutput
}

GoogleCloudMlV1__SchedulingPtrInput is an input type that accepts GoogleCloudMlV1__SchedulingArgs, GoogleCloudMlV1__SchedulingPtr and GoogleCloudMlV1__SchedulingPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__SchedulingPtrInput` via: 

        GoogleCloudMlV1__SchedulingArgs{...}

or:

        nil

func GoogleCloudMlV1__SchedulingPtr 

func GoogleCloudMlV1__SchedulingPtr(v *GoogleCloudMlV1__SchedulingArgs) GoogleCloudMlV1__SchedulingPtrInput

type GoogleCloudMlV1__SchedulingPtrOutput 

type GoogleCloudMlV1__SchedulingPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__SchedulingPtrOutput) Elem 

func (o GoogleCloudMlV1__SchedulingPtrOutput) Elem() GoogleCloudMlV1__SchedulingOutput

func (GoogleCloudMlV1__SchedulingPtrOutput) ElementType 

func (GoogleCloudMlV1__SchedulingPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__SchedulingPtrOutput) MaxRunningTime 

func (o GoogleCloudMlV1__SchedulingPtrOutput) MaxRunningTime() pulumi.StringPtrOutput

Optional. The maximum job running time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, this field defaults to `604800s` (seven days). If the training job is still running after this duration, AI Platform Training cancels it. The duration is measured from when the job enters the `RUNNING` state; therefore it does not overlap with the duration limited by Scheduling.max_wait_time. For example, if you want to ensure your job runs for no more than 2 hours, set this field to `7200s` (2 hours * 60 minutes / hour * 60 seconds / minute). If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: ``` yaml trainingInput: scheduling: maxRunningTime: 7200s ```

func (GoogleCloudMlV1__SchedulingPtrOutput) MaxWaitTime 

func (o GoogleCloudMlV1__SchedulingPtrOutput) MaxWaitTime() pulumi.StringPtrOutput

Optional. The maximum job wait time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, there is no limit to the wait time. The minimum for this field is `1800s` (30 minutes). If the training job has not entered the `RUNNING` state after this duration, AI Platform Training cancels it. After the job begins running, it can no longer be cancelled due to the maximum wait time. Therefore the duration limited by this field does not overlap with the duration limited by Scheduling.max_running_time. For example, if the job temporarily stops running and retries due to a [VM restart](/ai-platform/training/docs/overview#restarts), this cannot lead to a maximum wait time cancellation. However, independently of this constraint, AI Platform Training might stop a job if there are too many retries due to exhausted resources in a region. The following example describes how you might use this field: To cancel your job if it doesn't start running within 1 hour, set this field to `3600s` (1 hour * 60 minutes / hour * 60 seconds / minute). If the job is still in the `QUEUED` or `PREPARING` state after an hour of waiting, AI Platform Training cancels the job. If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: ``` yaml trainingInput: scheduling: maxWaitTime: 3600s ```

func (GoogleCloudMlV1__SchedulingPtrOutput) Priority added in v0.6.0 

func (o GoogleCloudMlV1__SchedulingPtrOutput) Priority() pulumi.IntPtrOutput

Optional. Job scheduling will be based on this priority, which in the range [0, 1000]. The bigger the number, the higher the priority. Default to 0 if not set. If there are multiple jobs requesting same type of accelerators, the high priority job will be scheduled prior to ones with low priority.

func (GoogleCloudMlV1__SchedulingPtrOutput) ToGoogleCloudMlV1__SchedulingPtrOutput 

func (o GoogleCloudMlV1__SchedulingPtrOutput) ToGoogleCloudMlV1__SchedulingPtrOutput() GoogleCloudMlV1__SchedulingPtrOutput

func (GoogleCloudMlV1__SchedulingPtrOutput) ToGoogleCloudMlV1__SchedulingPtrOutputWithContext 

func (o GoogleCloudMlV1__SchedulingPtrOutput) ToGoogleCloudMlV1__SchedulingPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__SchedulingPtrOutput

type GoogleCloudMlV1__SchedulingResponse 

type GoogleCloudMlV1__SchedulingResponse struct {
	// Optional. The maximum job running time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, this field defaults to `604800s` (seven days). If the training job is still running after this duration, AI Platform Training cancels it. The duration is measured from when the job enters the `RUNNING` state; therefore it does not overlap with the duration limited by Scheduling.max_wait_time. For example, if you want to ensure your job runs for no more than 2 hours, set this field to `7200s` (2 hours * 60 minutes / hour * 60 seconds / minute). If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: “` yaml trainingInput: scheduling: maxRunningTime: 7200s  “`
	MaxRunningTime string `pulumi:"maxRunningTime"`
	// Optional. The maximum job wait time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, there is no limit to the wait time. The minimum for this field is `1800s` (30 minutes). If the training job has not entered the `RUNNING` state after this duration, AI Platform Training cancels it. After the job begins running, it can no longer be cancelled due to the maximum wait time. Therefore the duration limited by this field does not overlap with the duration limited by Scheduling.max_running_time. For example, if the job temporarily stops running and retries due to a [VM restart](/ai-platform/training/docs/overview#restarts), this cannot lead to a maximum wait time cancellation. However, independently of this constraint, AI Platform Training might stop a job if there are too many retries due to exhausted resources in a region. The following example describes how you might use this field: To cancel your job if it doesn't start running within 1 hour, set this field to `3600s` (1 hour * 60 minutes / hour * 60 seconds / minute). If the job is still in the `QUEUED` or `PREPARING` state after an hour of waiting, AI Platform Training cancels the job. If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: “` yaml trainingInput: scheduling: maxWaitTime: 3600s  “`
	MaxWaitTime string `pulumi:"maxWaitTime"`
	// Optional. Job scheduling will be based on this priority, which in the range [0, 1000]. The bigger the number, the higher the priority. Default to 0 if not set. If there are multiple jobs requesting same type of accelerators, the high priority job will be scheduled prior to ones with low priority.
	Priority int `pulumi:"priority"`
}

All parameters related to scheduling of training jobs.

type GoogleCloudMlV1__SchedulingResponseOutput 

type GoogleCloudMlV1__SchedulingResponseOutput struct{ *pulumi.OutputState }

All parameters related to scheduling of training jobs.

func (GoogleCloudMlV1__SchedulingResponseOutput) ElementType 

func (GoogleCloudMlV1__SchedulingResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__SchedulingResponseOutput) MaxRunningTime 

func (o GoogleCloudMlV1__SchedulingResponseOutput) MaxRunningTime() pulumi.StringOutput

Optional. The maximum job running time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, this field defaults to `604800s` (seven days). If the training job is still running after this duration, AI Platform Training cancels it. The duration is measured from when the job enters the `RUNNING` state; therefore it does not overlap with the duration limited by Scheduling.max_wait_time. For example, if you want to ensure your job runs for no more than 2 hours, set this field to `7200s` (2 hours * 60 minutes / hour * 60 seconds / minute). If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: ``` yaml trainingInput: scheduling: maxRunningTime: 7200s ```

func (GoogleCloudMlV1__SchedulingResponseOutput) MaxWaitTime 

func (o GoogleCloudMlV1__SchedulingResponseOutput) MaxWaitTime() pulumi.StringOutput

Optional. The maximum job wait time, expressed in seconds. The field can contain up to nine fractional digits, terminated by `s`. If not specified, there is no limit to the wait time. The minimum for this field is `1800s` (30 minutes). If the training job has not entered the `RUNNING` state after this duration, AI Platform Training cancels it. After the job begins running, it can no longer be cancelled due to the maximum wait time. Therefore the duration limited by this field does not overlap with the duration limited by Scheduling.max_running_time. For example, if the job temporarily stops running and retries due to a [VM restart](/ai-platform/training/docs/overview#restarts), this cannot lead to a maximum wait time cancellation. However, independently of this constraint, AI Platform Training might stop a job if there are too many retries due to exhausted resources in a region. The following example describes how you might use this field: To cancel your job if it doesn't start running within 1 hour, set this field to `3600s` (1 hour * 60 minutes / hour * 60 seconds / minute). If the job is still in the `QUEUED` or `PREPARING` state after an hour of waiting, AI Platform Training cancels the job. If you submit your training job using the `gcloud` tool, you can [specify this field in a `config.yaml` file](/ai-platform/training/docs/training-jobs#formatting_your_configuration_parameters). For example: ``` yaml trainingInput: scheduling: maxWaitTime: 3600s ```

func (GoogleCloudMlV1__SchedulingResponseOutput) Priority added in v0.6.0 

func (o GoogleCloudMlV1__SchedulingResponseOutput) Priority() pulumi.IntOutput

Optional. Job scheduling will be based on this priority, which in the range [0, 1000]. The bigger the number, the higher the priority. Default to 0 if not set. If there are multiple jobs requesting same type of accelerators, the high priority job will be scheduled prior to ones with low priority.

func (GoogleCloudMlV1__SchedulingResponseOutput) ToGoogleCloudMlV1__SchedulingResponseOutput 

func (o GoogleCloudMlV1__SchedulingResponseOutput) ToGoogleCloudMlV1__SchedulingResponseOutput() GoogleCloudMlV1__SchedulingResponseOutput

func (GoogleCloudMlV1__SchedulingResponseOutput) ToGoogleCloudMlV1__SchedulingResponseOutputWithContext 

func (o GoogleCloudMlV1__SchedulingResponseOutput) ToGoogleCloudMlV1__SchedulingResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__SchedulingResponseOutput

type GoogleCloudMlV1__StudyConfig 

type GoogleCloudMlV1__StudyConfig struct {
	// The search algorithm specified for the study.
	Algorithm *GoogleCloudMlV1__StudyConfigAlgorithm `pulumi:"algorithm"`
	// Configuration for automated stopping of unpromising Trials.
	AutomatedStoppingConfig *GoogleCloudMlV1__AutomatedStoppingConfig `pulumi:"automatedStoppingConfig"`
	// Metric specs for the study.
	Metrics []GoogleCloudMlV1_StudyConfig_MetricSpec `pulumi:"metrics"`
	// The set of parameters to tune.
	Parameters []GoogleCloudMlV1_StudyConfig_ParameterSpec `pulumi:"parameters"`
}

Represents configuration of a study.

type GoogleCloudMlV1__StudyConfigAlgorithm added in v0.4.0 

type GoogleCloudMlV1__StudyConfigAlgorithm string

The search algorithm specified for the study.

func (GoogleCloudMlV1__StudyConfigAlgorithm) ElementType added in v0.4.0 

func (GoogleCloudMlV1__StudyConfigAlgorithm) ElementType() reflect.Type

func (GoogleCloudMlV1__StudyConfigAlgorithm) ToGoogleCloudMlV1__StudyConfigAlgorithmOutput added in v0.6.0 

func (e GoogleCloudMlV1__StudyConfigAlgorithm) ToGoogleCloudMlV1__StudyConfigAlgorithmOutput() GoogleCloudMlV1__StudyConfigAlgorithmOutput

func (GoogleCloudMlV1__StudyConfigAlgorithm) ToGoogleCloudMlV1__StudyConfigAlgorithmOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__StudyConfigAlgorithm) ToGoogleCloudMlV1__StudyConfigAlgorithmOutputWithContext(ctx context.Context) GoogleCloudMlV1__StudyConfigAlgorithmOutput

func (GoogleCloudMlV1__StudyConfigAlgorithm) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__StudyConfigAlgorithm) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutput() GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput

func (GoogleCloudMlV1__StudyConfigAlgorithm) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__StudyConfigAlgorithm) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput

func (GoogleCloudMlV1__StudyConfigAlgorithm) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__StudyConfigAlgorithm) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__StudyConfigAlgorithm) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__StudyConfigAlgorithm) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__StudyConfigAlgorithm) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__StudyConfigAlgorithm) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__StudyConfigAlgorithm) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__StudyConfigAlgorithm) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__StudyConfigAlgorithmInput added in v0.6.0 

type GoogleCloudMlV1__StudyConfigAlgorithmInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__StudyConfigAlgorithmOutput() GoogleCloudMlV1__StudyConfigAlgorithmOutput
	ToGoogleCloudMlV1__StudyConfigAlgorithmOutputWithContext(context.Context) GoogleCloudMlV1__StudyConfigAlgorithmOutput
}

GoogleCloudMlV1__StudyConfigAlgorithmInput is an input type that accepts GoogleCloudMlV1__StudyConfigAlgorithmArgs and GoogleCloudMlV1__StudyConfigAlgorithmOutput values. You can construct a concrete instance of `GoogleCloudMlV1__StudyConfigAlgorithmInput` via: 

GoogleCloudMlV1__StudyConfigAlgorithmArgs{...}

type GoogleCloudMlV1__StudyConfigAlgorithmOutput added in v0.6.0 

type GoogleCloudMlV1__StudyConfigAlgorithmOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmOutput added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmOutput() GoogleCloudMlV1__StudyConfigAlgorithmOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmOutputWithContext(ctx context.Context) GoogleCloudMlV1__StudyConfigAlgorithmOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutput() GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__StudyConfigAlgorithmPtrInput added in v0.6.0 

type GoogleCloudMlV1__StudyConfigAlgorithmPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutput() GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput
	ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutputWithContext(context.Context) GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput
}

func GoogleCloudMlV1__StudyConfigAlgorithmPtr added in v0.6.0 

func GoogleCloudMlV1__StudyConfigAlgorithmPtr(v string) GoogleCloudMlV1__StudyConfigAlgorithmPtrInput

type GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput added in v0.6.0 

type GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) Elem() GoogleCloudMlV1__StudyConfigAlgorithmOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutput() GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ToGoogleCloudMlV1__StudyConfigAlgorithmPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__StudyConfigArgs 

type GoogleCloudMlV1__StudyConfigArgs struct {
	// The search algorithm specified for the study.
	Algorithm GoogleCloudMlV1__StudyConfigAlgorithmPtrInput `pulumi:"algorithm"`
	// Configuration for automated stopping of unpromising Trials.
	AutomatedStoppingConfig GoogleCloudMlV1__AutomatedStoppingConfigPtrInput `pulumi:"automatedStoppingConfig"`
	// Metric specs for the study.
	Metrics GoogleCloudMlV1_StudyConfig_MetricSpecArrayInput `pulumi:"metrics"`
	// The set of parameters to tune.
	Parameters GoogleCloudMlV1_StudyConfig_ParameterSpecArrayInput `pulumi:"parameters"`
}

Represents configuration of a study.

func (GoogleCloudMlV1__StudyConfigArgs) ElementType 

func (GoogleCloudMlV1__StudyConfigArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__StudyConfigArgs) ToGoogleCloudMlV1__StudyConfigOutput 

func (i GoogleCloudMlV1__StudyConfigArgs) ToGoogleCloudMlV1__StudyConfigOutput() GoogleCloudMlV1__StudyConfigOutput

func (GoogleCloudMlV1__StudyConfigArgs) ToGoogleCloudMlV1__StudyConfigOutputWithContext 

func (i GoogleCloudMlV1__StudyConfigArgs) ToGoogleCloudMlV1__StudyConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__StudyConfigOutput

type GoogleCloudMlV1__StudyConfigInput 

type GoogleCloudMlV1__StudyConfigInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__StudyConfigOutput() GoogleCloudMlV1__StudyConfigOutput
	ToGoogleCloudMlV1__StudyConfigOutputWithContext(context.Context) GoogleCloudMlV1__StudyConfigOutput
}

GoogleCloudMlV1__StudyConfigInput is an input type that accepts GoogleCloudMlV1__StudyConfigArgs and GoogleCloudMlV1__StudyConfigOutput values. You can construct a concrete instance of `GoogleCloudMlV1__StudyConfigInput` via: 

GoogleCloudMlV1__StudyConfigArgs{...}

type GoogleCloudMlV1__StudyConfigOutput 

type GoogleCloudMlV1__StudyConfigOutput struct{ *pulumi.OutputState }

Represents configuration of a study.

func (GoogleCloudMlV1__StudyConfigOutput) Algorithm 

func (o GoogleCloudMlV1__StudyConfigOutput) Algorithm() GoogleCloudMlV1__StudyConfigAlgorithmPtrOutput

The search algorithm specified for the study.

func (GoogleCloudMlV1__StudyConfigOutput) AutomatedStoppingConfig 

func (o GoogleCloudMlV1__StudyConfigOutput) AutomatedStoppingConfig() GoogleCloudMlV1__AutomatedStoppingConfigPtrOutput

Configuration for automated stopping of unpromising Trials.

func (GoogleCloudMlV1__StudyConfigOutput) ElementType 

func (GoogleCloudMlV1__StudyConfigOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__StudyConfigOutput) Metrics 

func (o GoogleCloudMlV1__StudyConfigOutput) Metrics() GoogleCloudMlV1_StudyConfig_MetricSpecArrayOutput

Metric specs for the study.

func (GoogleCloudMlV1__StudyConfigOutput) Parameters 

func (o GoogleCloudMlV1__StudyConfigOutput) Parameters() GoogleCloudMlV1_StudyConfig_ParameterSpecArrayOutput

The set of parameters to tune.

func (GoogleCloudMlV1__StudyConfigOutput) ToGoogleCloudMlV1__StudyConfigOutput 

func (o GoogleCloudMlV1__StudyConfigOutput) ToGoogleCloudMlV1__StudyConfigOutput() GoogleCloudMlV1__StudyConfigOutput

func (GoogleCloudMlV1__StudyConfigOutput) ToGoogleCloudMlV1__StudyConfigOutputWithContext 

func (o GoogleCloudMlV1__StudyConfigOutput) ToGoogleCloudMlV1__StudyConfigOutputWithContext(ctx context.Context) GoogleCloudMlV1__StudyConfigOutput

type GoogleCloudMlV1__StudyConfigResponse 

type GoogleCloudMlV1__StudyConfigResponse struct {
	// The search algorithm specified for the study.
	Algorithm string `pulumi:"algorithm"`
	// Configuration for automated stopping of unpromising Trials.
	AutomatedStoppingConfig GoogleCloudMlV1__AutomatedStoppingConfigResponse `pulumi:"automatedStoppingConfig"`
	// Metric specs for the study.
	Metrics []GoogleCloudMlV1_StudyConfig_MetricSpecResponse `pulumi:"metrics"`
	// The set of parameters to tune.
	Parameters []GoogleCloudMlV1_StudyConfig_ParameterSpecResponse `pulumi:"parameters"`
}

Represents configuration of a study.

type GoogleCloudMlV1__StudyConfigResponseOutput 

type GoogleCloudMlV1__StudyConfigResponseOutput struct{ *pulumi.OutputState }

Represents configuration of a study.

func (GoogleCloudMlV1__StudyConfigResponseOutput) Algorithm 

func (o GoogleCloudMlV1__StudyConfigResponseOutput) Algorithm() pulumi.StringOutput

The search algorithm specified for the study.

func (GoogleCloudMlV1__StudyConfigResponseOutput) AutomatedStoppingConfig 

func (o GoogleCloudMlV1__StudyConfigResponseOutput) AutomatedStoppingConfig() GoogleCloudMlV1__AutomatedStoppingConfigResponseOutput

Configuration for automated stopping of unpromising Trials.

func (GoogleCloudMlV1__StudyConfigResponseOutput) ElementType 

func (GoogleCloudMlV1__StudyConfigResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__StudyConfigResponseOutput) Metrics 

func (o GoogleCloudMlV1__StudyConfigResponseOutput) Metrics() GoogleCloudMlV1_StudyConfig_MetricSpecResponseArrayOutput

Metric specs for the study.

func (GoogleCloudMlV1__StudyConfigResponseOutput) Parameters 

func (o GoogleCloudMlV1__StudyConfigResponseOutput) Parameters() GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArrayOutput

The set of parameters to tune.

func (GoogleCloudMlV1__StudyConfigResponseOutput) ToGoogleCloudMlV1__StudyConfigResponseOutput 

func (o GoogleCloudMlV1__StudyConfigResponseOutput) ToGoogleCloudMlV1__StudyConfigResponseOutput() GoogleCloudMlV1__StudyConfigResponseOutput

func (GoogleCloudMlV1__StudyConfigResponseOutput) ToGoogleCloudMlV1__StudyConfigResponseOutputWithContext 

func (o GoogleCloudMlV1__StudyConfigResponseOutput) ToGoogleCloudMlV1__StudyConfigResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__StudyConfigResponseOutput

type GoogleCloudMlV1__TrainingInput 

type GoogleCloudMlV1__TrainingInput struct {
	// Optional. Command-line arguments passed to the training application when it starts. If your job uses a custom container, then the arguments are passed to the container's `ENTRYPOINT` command.
	Args []string `pulumi:"args"`
	// Optional. Whether you want AI Platform Training to enable [interactive shell access](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by TrainingOutput.web_access_uris or HyperparameterOutput.web_access_uris (within TrainingOutput.trials).
	EnableWebAccess *bool `pulumi:"enableWebAccess"`
	// Optional. Options for using customer-managed encryption keys (CMEK) to protect resources created by a training job, instead of using Google's default encryption. If this is set, then all resources created by the training job will be encrypted with the customer-managed encryption key that you specify. [Learn how and when to use CMEK with AI Platform Training](/ai-platform/training/docs/cmek).
	EncryptionConfig *GoogleCloudMlV1__EncryptionConfig `pulumi:"encryptionConfig"`
	// Optional. The configuration for evaluators. You should only set `evaluatorConfig.acceleratorConfig` if `evaluatorType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `evaluatorConfig.imageUri` only if you build a custom image for your evaluator. If `evaluatorConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	EvaluatorConfig *GoogleCloudMlV1__ReplicaConfig `pulumi:"evaluatorConfig"`
	// Optional. The number of evaluator replicas to use for the training job. Each replica in the cluster will be of the type specified in `evaluator_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `evaluator_type`. The default value is zero.
	EvaluatorCount *string `pulumi:"evaluatorCount"`
	// Optional. Specifies the type of virtual machine to use for your training job's evaluator nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `evaluatorCount` is greater than zero.
	EvaluatorType *string `pulumi:"evaluatorType"`
	// Optional. The set of Hyperparameters to tune.
	Hyperparameters *GoogleCloudMlV1__HyperparameterSpec `pulumi:"hyperparameters"`
	// Optional. A Google Cloud Storage path in which to store training outputs and other data needed for training. This path is passed to your TensorFlow program as the '--job-dir' command-line argument. The benefit of specifying this field is that Cloud ML validates the path for use in training.
	JobDir *string `pulumi:"jobDir"`
	// Optional. The configuration for your master worker. You should only set `masterConfig.acceleratorConfig` if `masterType` is set to a Compute Engine machine type. Learn about [restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `masterConfig.imageUri` only if you build a custom image. Only one of `masterConfig.imageUri` and `runtimeVersion` should be set. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	MasterConfig *GoogleCloudMlV1__ReplicaConfig `pulumi:"masterConfig"`
	// Optional. Specifies the type of virtual machine to use for your training job's master worker. You must specify this field when `scaleTier` is set to `CUSTOM`. You can use certain Compute Engine machine types directly in this field. See the [list of compatible Compute Engine machine types](/ai-platform/training/docs/machine-types#compute-engine-machine-types). Alternatively, you can use the certain legacy machine types in this field. See the [list of legacy machine types](/ai-platform/training/docs/machine-types#legacy-machine-types). Finally, if you want to use a TPU for training, specify `cloud_tpu` in this field. Learn more about the [special configuration options for training with TPUs](/ai-platform/training/docs/using-tpus#configuring_a_custom_tpu_machine).
	MasterType *string `pulumi:"masterType"`
	// Optional. The full name of the [Compute Engine network](/vpc/docs/vpc) to which the Job is peered. For example, `projects/12345/global/networks/myVPC`. The format of this field is `projects/{project}/global/networks/{network}`, where {project} is a project number (like `12345`) and {network} is network name. Private services access must already be configured for the network. If left unspecified, the Job is not peered with any network. [Learn about using VPC Network Peering.](/ai-platform/training/docs/vpc-peering).
	Network *string `pulumi:"network"`
	// The Google Cloud Storage location of the packages with the training program and any additional dependencies. The maximum number of package URIs is 100.
	PackageUris []string `pulumi:"packageUris"`
	// Optional. The configuration for parameter servers. You should only set `parameterServerConfig.acceleratorConfig` if `parameterServerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `parameterServerConfig.imageUri` only if you build a custom image for your parameter server. If `parameterServerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	ParameterServerConfig *GoogleCloudMlV1__ReplicaConfig `pulumi:"parameterServerConfig"`
	// Optional. The number of parameter server replicas to use for the training job. Each replica in the cluster will be of the type specified in `parameter_server_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `parameter_server_type`. The default value is zero.
	ParameterServerCount *string `pulumi:"parameterServerCount"`
	// Optional. Specifies the type of virtual machine to use for your training job's parameter server. The supported values are the same as those described in the entry for `master_type`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `parameter_server_count` is greater than zero.
	ParameterServerType *string `pulumi:"parameterServerType"`
	// The Python module name to run after installing the packages.
	PythonModule string `pulumi:"pythonModule"`
	// Optional. The version of Python used in training. You must either specify this field or specify `masterConfig.imageUri`. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).
	PythonVersion *string `pulumi:"pythonVersion"`
	// The region to run the training job in. See the [available regions](/ai-platform/training/docs/regions) for AI Platform Training.
	Region string `pulumi:"region"`
	// Optional. The AI Platform runtime version to use for training. You must either specify this field or specify `masterConfig.imageUri`. For more information, see the [runtime version list](/ai-platform/training/docs/runtime-version-list) and learn [how to manage runtime versions](/ai-platform/training/docs/versioning).
	RuntimeVersion *string `pulumi:"runtimeVersion"`
	// Specifies the machine types, the number of replicas for workers and parameter servers.
	ScaleTier GoogleCloudMlV1__TrainingInputScaleTier `pulumi:"scaleTier"`
	// Optional. Scheduling options for a training job.
	Scheduling *GoogleCloudMlV1__Scheduling `pulumi:"scheduling"`
	// Optional. The email address of a service account to use when running the training appplication. You must have the `iam.serviceAccounts.actAs` permission for the specified service account. In addition, the AI Platform Training Google-managed service account must have the `roles/iam.serviceAccountAdmin` role for the specified service account. [Learn more about configuring a service account.](/ai-platform/training/docs/custom-service-account) If not specified, the AI Platform Training Google-managed service account is used by default.
	ServiceAccount *string `pulumi:"serviceAccount"`
	// Optional. Use `chief` instead of `master` in the `TF_CONFIG` environment variable when training with a custom container. Defaults to `false`. [Learn more about this field.](/ai-platform/training/docs/distributed-training-details#chief-versus-master) This field has no effect for training jobs that don't use a custom container.
	UseChiefInTfConfig *bool `pulumi:"useChiefInTfConfig"`
	// Optional. The configuration for workers. You should only set `workerConfig.acceleratorConfig` if `workerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `workerConfig.imageUri` only if you build a custom image for your worker. If `workerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	WorkerConfig *GoogleCloudMlV1__ReplicaConfig `pulumi:"workerConfig"`
	// Optional. The number of worker replicas to use for the training job. Each replica in the cluster will be of the type specified in `worker_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `worker_type`. The default value is zero.
	WorkerCount *string `pulumi:"workerCount"`
	// Optional. Specifies the type of virtual machine to use for your training job's worker nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. If you use `cloud_tpu` for this value, see special instructions for [configuring a custom TPU machine](/ml-engine/docs/tensorflow/using-tpus#configuring_a_custom_tpu_machine). This value must be present when `scaleTier` is set to `CUSTOM` and `workerCount` is greater than zero.
	WorkerType *string `pulumi:"workerType"`
}

Represents input parameters for a training job. When using the gcloud command to submit your training job, you can specify the input parameters as command-line arguments and/or in a YAML configuration file referenced from the --config command-line argument. For details, see the guide to [submitting a training job](/ai-platform/training/docs/training-jobs).

type GoogleCloudMlV1__TrainingInputArgs 

type GoogleCloudMlV1__TrainingInputArgs struct {
	// Optional. Command-line arguments passed to the training application when it starts. If your job uses a custom container, then the arguments are passed to the container's `ENTRYPOINT` command.
	Args pulumi.StringArrayInput `pulumi:"args"`
	// Optional. Whether you want AI Platform Training to enable [interactive shell access](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by TrainingOutput.web_access_uris or HyperparameterOutput.web_access_uris (within TrainingOutput.trials).
	EnableWebAccess pulumi.BoolPtrInput `pulumi:"enableWebAccess"`
	// Optional. Options for using customer-managed encryption keys (CMEK) to protect resources created by a training job, instead of using Google's default encryption. If this is set, then all resources created by the training job will be encrypted with the customer-managed encryption key that you specify. [Learn how and when to use CMEK with AI Platform Training](/ai-platform/training/docs/cmek).
	EncryptionConfig GoogleCloudMlV1__EncryptionConfigPtrInput `pulumi:"encryptionConfig"`
	// Optional. The configuration for evaluators. You should only set `evaluatorConfig.acceleratorConfig` if `evaluatorType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `evaluatorConfig.imageUri` only if you build a custom image for your evaluator. If `evaluatorConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	EvaluatorConfig GoogleCloudMlV1__ReplicaConfigPtrInput `pulumi:"evaluatorConfig"`
	// Optional. The number of evaluator replicas to use for the training job. Each replica in the cluster will be of the type specified in `evaluator_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `evaluator_type`. The default value is zero.
	EvaluatorCount pulumi.StringPtrInput `pulumi:"evaluatorCount"`
	// Optional. Specifies the type of virtual machine to use for your training job's evaluator nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `evaluatorCount` is greater than zero.
	EvaluatorType pulumi.StringPtrInput `pulumi:"evaluatorType"`
	// Optional. The set of Hyperparameters to tune.
	Hyperparameters GoogleCloudMlV1__HyperparameterSpecPtrInput `pulumi:"hyperparameters"`
	// Optional. A Google Cloud Storage path in which to store training outputs and other data needed for training. This path is passed to your TensorFlow program as the '--job-dir' command-line argument. The benefit of specifying this field is that Cloud ML validates the path for use in training.
	JobDir pulumi.StringPtrInput `pulumi:"jobDir"`
	// Optional. The configuration for your master worker. You should only set `masterConfig.acceleratorConfig` if `masterType` is set to a Compute Engine machine type. Learn about [restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `masterConfig.imageUri` only if you build a custom image. Only one of `masterConfig.imageUri` and `runtimeVersion` should be set. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	MasterConfig GoogleCloudMlV1__ReplicaConfigPtrInput `pulumi:"masterConfig"`
	// Optional. Specifies the type of virtual machine to use for your training job's master worker. You must specify this field when `scaleTier` is set to `CUSTOM`. You can use certain Compute Engine machine types directly in this field. See the [list of compatible Compute Engine machine types](/ai-platform/training/docs/machine-types#compute-engine-machine-types). Alternatively, you can use the certain legacy machine types in this field. See the [list of legacy machine types](/ai-platform/training/docs/machine-types#legacy-machine-types). Finally, if you want to use a TPU for training, specify `cloud_tpu` in this field. Learn more about the [special configuration options for training with TPUs](/ai-platform/training/docs/using-tpus#configuring_a_custom_tpu_machine).
	MasterType pulumi.StringPtrInput `pulumi:"masterType"`
	// Optional. The full name of the [Compute Engine network](/vpc/docs/vpc) to which the Job is peered. For example, `projects/12345/global/networks/myVPC`. The format of this field is `projects/{project}/global/networks/{network}`, where {project} is a project number (like `12345`) and {network} is network name. Private services access must already be configured for the network. If left unspecified, the Job is not peered with any network. [Learn about using VPC Network Peering.](/ai-platform/training/docs/vpc-peering).
	Network pulumi.StringPtrInput `pulumi:"network"`
	// The Google Cloud Storage location of the packages with the training program and any additional dependencies. The maximum number of package URIs is 100.
	PackageUris pulumi.StringArrayInput `pulumi:"packageUris"`
	// Optional. The configuration for parameter servers. You should only set `parameterServerConfig.acceleratorConfig` if `parameterServerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `parameterServerConfig.imageUri` only if you build a custom image for your parameter server. If `parameterServerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	ParameterServerConfig GoogleCloudMlV1__ReplicaConfigPtrInput `pulumi:"parameterServerConfig"`
	// Optional. The number of parameter server replicas to use for the training job. Each replica in the cluster will be of the type specified in `parameter_server_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `parameter_server_type`. The default value is zero.
	ParameterServerCount pulumi.StringPtrInput `pulumi:"parameterServerCount"`
	// Optional. Specifies the type of virtual machine to use for your training job's parameter server. The supported values are the same as those described in the entry for `master_type`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `parameter_server_count` is greater than zero.
	ParameterServerType pulumi.StringPtrInput `pulumi:"parameterServerType"`
	// The Python module name to run after installing the packages.
	PythonModule pulumi.StringInput `pulumi:"pythonModule"`
	// Optional. The version of Python used in training. You must either specify this field or specify `masterConfig.imageUri`. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).
	PythonVersion pulumi.StringPtrInput `pulumi:"pythonVersion"`
	// The region to run the training job in. See the [available regions](/ai-platform/training/docs/regions) for AI Platform Training.
	Region pulumi.StringInput `pulumi:"region"`
	// Optional. The AI Platform runtime version to use for training. You must either specify this field or specify `masterConfig.imageUri`. For more information, see the [runtime version list](/ai-platform/training/docs/runtime-version-list) and learn [how to manage runtime versions](/ai-platform/training/docs/versioning).
	RuntimeVersion pulumi.StringPtrInput `pulumi:"runtimeVersion"`
	// Specifies the machine types, the number of replicas for workers and parameter servers.
	ScaleTier GoogleCloudMlV1__TrainingInputScaleTierInput `pulumi:"scaleTier"`
	// Optional. Scheduling options for a training job.
	Scheduling GoogleCloudMlV1__SchedulingPtrInput `pulumi:"scheduling"`
	// Optional. The email address of a service account to use when running the training appplication. You must have the `iam.serviceAccounts.actAs` permission for the specified service account. In addition, the AI Platform Training Google-managed service account must have the `roles/iam.serviceAccountAdmin` role for the specified service account. [Learn more about configuring a service account.](/ai-platform/training/docs/custom-service-account) If not specified, the AI Platform Training Google-managed service account is used by default.
	ServiceAccount pulumi.StringPtrInput `pulumi:"serviceAccount"`
	// Optional. Use `chief` instead of `master` in the `TF_CONFIG` environment variable when training with a custom container. Defaults to `false`. [Learn more about this field.](/ai-platform/training/docs/distributed-training-details#chief-versus-master) This field has no effect for training jobs that don't use a custom container.
	UseChiefInTfConfig pulumi.BoolPtrInput `pulumi:"useChiefInTfConfig"`
	// Optional. The configuration for workers. You should only set `workerConfig.acceleratorConfig` if `workerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `workerConfig.imageUri` only if you build a custom image for your worker. If `workerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	WorkerConfig GoogleCloudMlV1__ReplicaConfigPtrInput `pulumi:"workerConfig"`
	// Optional. The number of worker replicas to use for the training job. Each replica in the cluster will be of the type specified in `worker_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `worker_type`. The default value is zero.
	WorkerCount pulumi.StringPtrInput `pulumi:"workerCount"`
	// Optional. Specifies the type of virtual machine to use for your training job's worker nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. If you use `cloud_tpu` for this value, see special instructions for [configuring a custom TPU machine](/ml-engine/docs/tensorflow/using-tpus#configuring_a_custom_tpu_machine). This value must be present when `scaleTier` is set to `CUSTOM` and `workerCount` is greater than zero.
	WorkerType pulumi.StringPtrInput `pulumi:"workerType"`
}

Represents input parameters for a training job. When using the gcloud command to submit your training job, you can specify the input parameters as command-line arguments and/or in a YAML configuration file referenced from the --config command-line argument. For details, see the guide to [submitting a training job](/ai-platform/training/docs/training-jobs).

func (GoogleCloudMlV1__TrainingInputArgs) ElementType 

func (GoogleCloudMlV1__TrainingInputArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingInputArgs) ToGoogleCloudMlV1__TrainingInputOutput 

func (i GoogleCloudMlV1__TrainingInputArgs) ToGoogleCloudMlV1__TrainingInputOutput() GoogleCloudMlV1__TrainingInputOutput

func (GoogleCloudMlV1__TrainingInputArgs) ToGoogleCloudMlV1__TrainingInputOutputWithContext 

func (i GoogleCloudMlV1__TrainingInputArgs) ToGoogleCloudMlV1__TrainingInputOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputOutput

func (GoogleCloudMlV1__TrainingInputArgs) ToGoogleCloudMlV1__TrainingInputPtrOutput 

func (i GoogleCloudMlV1__TrainingInputArgs) ToGoogleCloudMlV1__TrainingInputPtrOutput() GoogleCloudMlV1__TrainingInputPtrOutput

func (GoogleCloudMlV1__TrainingInputArgs) ToGoogleCloudMlV1__TrainingInputPtrOutputWithContext 

func (i GoogleCloudMlV1__TrainingInputArgs) ToGoogleCloudMlV1__TrainingInputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputPtrOutput

type GoogleCloudMlV1__TrainingInputInput 

type GoogleCloudMlV1__TrainingInputInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__TrainingInputOutput() GoogleCloudMlV1__TrainingInputOutput
	ToGoogleCloudMlV1__TrainingInputOutputWithContext(context.Context) GoogleCloudMlV1__TrainingInputOutput
}

GoogleCloudMlV1__TrainingInputInput is an input type that accepts GoogleCloudMlV1__TrainingInputArgs and GoogleCloudMlV1__TrainingInputOutput values. You can construct a concrete instance of `GoogleCloudMlV1__TrainingInputInput` via: 

GoogleCloudMlV1__TrainingInputArgs{...}

type GoogleCloudMlV1__TrainingInputOutput 

type GoogleCloudMlV1__TrainingInputOutput struct{ *pulumi.OutputState }

Represents input parameters for a training job. When using the gcloud command to submit your training job, you can specify the input parameters as command-line arguments and/or in a YAML configuration file referenced from the --config command-line argument. For details, see the guide to [submitting a training job](/ai-platform/training/docs/training-jobs).

func (GoogleCloudMlV1__TrainingInputOutput) Args 

func (o GoogleCloudMlV1__TrainingInputOutput) Args() pulumi.StringArrayOutput

Optional. Command-line arguments passed to the training application when it starts. If your job uses a custom container, then the arguments are passed to the container's `ENTRYPOINT` command.

func (GoogleCloudMlV1__TrainingInputOutput) ElementType 

func (GoogleCloudMlV1__TrainingInputOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingInputOutput) EnableWebAccess added in v0.5.0 

func (o GoogleCloudMlV1__TrainingInputOutput) EnableWebAccess() pulumi.BoolPtrOutput

Optional. Whether you want AI Platform Training to enable [interactive shell access](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by TrainingOutput.web_access_uris or HyperparameterOutput.web_access_uris (within TrainingOutput.trials).

func (GoogleCloudMlV1__TrainingInputOutput) EncryptionConfig 

func (o GoogleCloudMlV1__TrainingInputOutput) EncryptionConfig() GoogleCloudMlV1__EncryptionConfigPtrOutput

Optional. Options for using customer-managed encryption keys (CMEK) to protect resources created by a training job, instead of using Google's default encryption. If this is set, then all resources created by the training job will be encrypted with the customer-managed encryption key that you specify. [Learn how and when to use CMEK with AI Platform Training](/ai-platform/training/docs/cmek).

func (GoogleCloudMlV1__TrainingInputOutput) EvaluatorConfig 

func (o GoogleCloudMlV1__TrainingInputOutput) EvaluatorConfig() GoogleCloudMlV1__ReplicaConfigPtrOutput

Optional. The configuration for evaluators. You should only set `evaluatorConfig.acceleratorConfig` if `evaluatorType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `evaluatorConfig.imageUri` only if you build a custom image for your evaluator. If `evaluatorConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputOutput) EvaluatorCount 

func (o GoogleCloudMlV1__TrainingInputOutput) EvaluatorCount() pulumi.StringPtrOutput

Optional. The number of evaluator replicas to use for the training job. Each replica in the cluster will be of the type specified in `evaluator_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `evaluator_type`. The default value is zero.

func (GoogleCloudMlV1__TrainingInputOutput) EvaluatorType 

func (o GoogleCloudMlV1__TrainingInputOutput) EvaluatorType() pulumi.StringPtrOutput

Optional. Specifies the type of virtual machine to use for your training job's evaluator nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `evaluatorCount` is greater than zero.

func (GoogleCloudMlV1__TrainingInputOutput) Hyperparameters 

func (o GoogleCloudMlV1__TrainingInputOutput) Hyperparameters() GoogleCloudMlV1__HyperparameterSpecPtrOutput

Optional. The set of Hyperparameters to tune.

func (GoogleCloudMlV1__TrainingInputOutput) JobDir 

func (o GoogleCloudMlV1__TrainingInputOutput) JobDir() pulumi.StringPtrOutput

Optional. A Google Cloud Storage path in which to store training outputs and other data needed for training. This path is passed to your TensorFlow program as the '--job-dir' command-line argument. The benefit of specifying this field is that Cloud ML validates the path for use in training.

func (GoogleCloudMlV1__TrainingInputOutput) MasterConfig 

func (o GoogleCloudMlV1__TrainingInputOutput) MasterConfig() GoogleCloudMlV1__ReplicaConfigPtrOutput

Optional. The configuration for your master worker. You should only set `masterConfig.acceleratorConfig` if `masterType` is set to a Compute Engine machine type. Learn about [restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `masterConfig.imageUri` only if you build a custom image. Only one of `masterConfig.imageUri` and `runtimeVersion` should be set. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputOutput) MasterType 

func (o GoogleCloudMlV1__TrainingInputOutput) MasterType() pulumi.StringPtrOutput

Optional. Specifies the type of virtual machine to use for your training job's master worker. You must specify this field when `scaleTier` is set to `CUSTOM`. You can use certain Compute Engine machine types directly in this field. See the [list of compatible Compute Engine machine types](/ai-platform/training/docs/machine-types#compute-engine-machine-types). Alternatively, you can use the certain legacy machine types in this field. See the [list of legacy machine types](/ai-platform/training/docs/machine-types#legacy-machine-types). Finally, if you want to use a TPU for training, specify `cloud_tpu` in this field. Learn more about the [special configuration options for training with TPUs](/ai-platform/training/docs/using-tpus#configuring_a_custom_tpu_machine).

func (GoogleCloudMlV1__TrainingInputOutput) Network 

func (o GoogleCloudMlV1__TrainingInputOutput) Network() pulumi.StringPtrOutput

Optional. The full name of the [Compute Engine network](/vpc/docs/vpc) to which the Job is peered. For example, `projects/12345/global/networks/myVPC`. The format of this field is `projects/{project}/global/networks/{network}`, where {project} is a project number (like `12345`) and {network} is network name. Private services access must already be configured for the network. If left unspecified, the Job is not peered with any network. [Learn about using VPC Network Peering.](/ai-platform/training/docs/vpc-peering).

func (GoogleCloudMlV1__TrainingInputOutput) PackageUris 

func (o GoogleCloudMlV1__TrainingInputOutput) PackageUris() pulumi.StringArrayOutput

The Google Cloud Storage location of the packages with the training program and any additional dependencies. The maximum number of package URIs is 100.

func (GoogleCloudMlV1__TrainingInputOutput) ParameterServerConfig 

func (o GoogleCloudMlV1__TrainingInputOutput) ParameterServerConfig() GoogleCloudMlV1__ReplicaConfigPtrOutput

Optional. The configuration for parameter servers. You should only set `parameterServerConfig.acceleratorConfig` if `parameterServerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `parameterServerConfig.imageUri` only if you build a custom image for your parameter server. If `parameterServerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputOutput) ParameterServerCount 

func (o GoogleCloudMlV1__TrainingInputOutput) ParameterServerCount() pulumi.StringPtrOutput

Optional. The number of parameter server replicas to use for the training job. Each replica in the cluster will be of the type specified in `parameter_server_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `parameter_server_type`. The default value is zero.

func (GoogleCloudMlV1__TrainingInputOutput) ParameterServerType 

func (o GoogleCloudMlV1__TrainingInputOutput) ParameterServerType() pulumi.StringPtrOutput

Optional. Specifies the type of virtual machine to use for your training job's parameter server. The supported values are the same as those described in the entry for `master_type`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `parameter_server_count` is greater than zero.

func (GoogleCloudMlV1__TrainingInputOutput) PythonModule 

func (o GoogleCloudMlV1__TrainingInputOutput) PythonModule() pulumi.StringOutput

The Python module name to run after installing the packages.

func (GoogleCloudMlV1__TrainingInputOutput) PythonVersion 

func (o GoogleCloudMlV1__TrainingInputOutput) PythonVersion() pulumi.StringPtrOutput

Optional. The version of Python used in training. You must either specify this field or specify `masterConfig.imageUri`. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).

func (GoogleCloudMlV1__TrainingInputOutput) Region 

func (o GoogleCloudMlV1__TrainingInputOutput) Region() pulumi.StringOutput

The region to run the training job in. See the [available regions](/ai-platform/training/docs/regions) for AI Platform Training.

func (GoogleCloudMlV1__TrainingInputOutput) RuntimeVersion 

func (o GoogleCloudMlV1__TrainingInputOutput) RuntimeVersion() pulumi.StringPtrOutput

Optional. The AI Platform runtime version to use for training. You must either specify this field or specify `masterConfig.imageUri`. For more information, see the [runtime version list](/ai-platform/training/docs/runtime-version-list) and learn [how to manage runtime versions](/ai-platform/training/docs/versioning).

func (GoogleCloudMlV1__TrainingInputOutput) ScaleTier 

func (o GoogleCloudMlV1__TrainingInputOutput) ScaleTier() GoogleCloudMlV1__TrainingInputScaleTierOutput

Specifies the machine types, the number of replicas for workers and parameter servers.

func (GoogleCloudMlV1__TrainingInputOutput) Scheduling 

func (o GoogleCloudMlV1__TrainingInputOutput) Scheduling() GoogleCloudMlV1__SchedulingPtrOutput

Optional. Scheduling options for a training job.

func (GoogleCloudMlV1__TrainingInputOutput) ServiceAccount 

func (o GoogleCloudMlV1__TrainingInputOutput) ServiceAccount() pulumi.StringPtrOutput

Optional. The email address of a service account to use when running the training appplication. You must have the `iam.serviceAccounts.actAs` permission for the specified service account. In addition, the AI Platform Training Google-managed service account must have the `roles/iam.serviceAccountAdmin` role for the specified service account. [Learn more about configuring a service account.](/ai-platform/training/docs/custom-service-account) If not specified, the AI Platform Training Google-managed service account is used by default.

func (GoogleCloudMlV1__TrainingInputOutput) ToGoogleCloudMlV1__TrainingInputOutput 

func (o GoogleCloudMlV1__TrainingInputOutput) ToGoogleCloudMlV1__TrainingInputOutput() GoogleCloudMlV1__TrainingInputOutput

func (GoogleCloudMlV1__TrainingInputOutput) ToGoogleCloudMlV1__TrainingInputOutputWithContext 

func (o GoogleCloudMlV1__TrainingInputOutput) ToGoogleCloudMlV1__TrainingInputOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputOutput

func (GoogleCloudMlV1__TrainingInputOutput) ToGoogleCloudMlV1__TrainingInputPtrOutput 

func (o GoogleCloudMlV1__TrainingInputOutput) ToGoogleCloudMlV1__TrainingInputPtrOutput() GoogleCloudMlV1__TrainingInputPtrOutput

func (GoogleCloudMlV1__TrainingInputOutput) ToGoogleCloudMlV1__TrainingInputPtrOutputWithContext 

func (o GoogleCloudMlV1__TrainingInputOutput) ToGoogleCloudMlV1__TrainingInputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputPtrOutput

func (GoogleCloudMlV1__TrainingInputOutput) UseChiefInTfConfig 

func (o GoogleCloudMlV1__TrainingInputOutput) UseChiefInTfConfig() pulumi.BoolPtrOutput

Optional. Use `chief` instead of `master` in the `TF_CONFIG` environment variable when training with a custom container. Defaults to `false`. [Learn more about this field.](/ai-platform/training/docs/distributed-training-details#chief-versus-master) This field has no effect for training jobs that don't use a custom container.

func (GoogleCloudMlV1__TrainingInputOutput) WorkerConfig 

func (o GoogleCloudMlV1__TrainingInputOutput) WorkerConfig() GoogleCloudMlV1__ReplicaConfigPtrOutput

Optional. The configuration for workers. You should only set `workerConfig.acceleratorConfig` if `workerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `workerConfig.imageUri` only if you build a custom image for your worker. If `workerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputOutput) WorkerCount 

func (o GoogleCloudMlV1__TrainingInputOutput) WorkerCount() pulumi.StringPtrOutput

Optional. The number of worker replicas to use for the training job. Each replica in the cluster will be of the type specified in `worker_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `worker_type`. The default value is zero.

func (GoogleCloudMlV1__TrainingInputOutput) WorkerType 

func (o GoogleCloudMlV1__TrainingInputOutput) WorkerType() pulumi.StringPtrOutput

Optional. Specifies the type of virtual machine to use for your training job's worker nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. If you use `cloud_tpu` for this value, see special instructions for [configuring a custom TPU machine](/ml-engine/docs/tensorflow/using-tpus#configuring_a_custom_tpu_machine). This value must be present when `scaleTier` is set to `CUSTOM` and `workerCount` is greater than zero.

type GoogleCloudMlV1__TrainingInputPtrInput 

type GoogleCloudMlV1__TrainingInputPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__TrainingInputPtrOutput() GoogleCloudMlV1__TrainingInputPtrOutput
	ToGoogleCloudMlV1__TrainingInputPtrOutputWithContext(context.Context) GoogleCloudMlV1__TrainingInputPtrOutput
}

GoogleCloudMlV1__TrainingInputPtrInput is an input type that accepts GoogleCloudMlV1__TrainingInputArgs, GoogleCloudMlV1__TrainingInputPtr and GoogleCloudMlV1__TrainingInputPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__TrainingInputPtrInput` via: 

        GoogleCloudMlV1__TrainingInputArgs{...}

or:

        nil

func GoogleCloudMlV1__TrainingInputPtr 

func GoogleCloudMlV1__TrainingInputPtr(v *GoogleCloudMlV1__TrainingInputArgs) GoogleCloudMlV1__TrainingInputPtrInput

type GoogleCloudMlV1__TrainingInputPtrOutput 

type GoogleCloudMlV1__TrainingInputPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__TrainingInputPtrOutput) Args 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) Args() pulumi.StringArrayOutput

Optional. Command-line arguments passed to the training application when it starts. If your job uses a custom container, then the arguments are passed to the container's `ENTRYPOINT` command.

func (GoogleCloudMlV1__TrainingInputPtrOutput) Elem 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) Elem() GoogleCloudMlV1__TrainingInputOutput

func (GoogleCloudMlV1__TrainingInputPtrOutput) ElementType 

func (GoogleCloudMlV1__TrainingInputPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingInputPtrOutput) EnableWebAccess added in v0.5.0 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) EnableWebAccess() pulumi.BoolPtrOutput

Optional. Whether you want AI Platform Training to enable [interactive shell access](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by TrainingOutput.web_access_uris or HyperparameterOutput.web_access_uris (within TrainingOutput.trials).

func (GoogleCloudMlV1__TrainingInputPtrOutput) EncryptionConfig 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) EncryptionConfig() GoogleCloudMlV1__EncryptionConfigPtrOutput

Optional. Options for using customer-managed encryption keys (CMEK) to protect resources created by a training job, instead of using Google's default encryption. If this is set, then all resources created by the training job will be encrypted with the customer-managed encryption key that you specify. [Learn how and when to use CMEK with AI Platform Training](/ai-platform/training/docs/cmek).

func (GoogleCloudMlV1__TrainingInputPtrOutput) EvaluatorConfig 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) EvaluatorConfig() GoogleCloudMlV1__ReplicaConfigPtrOutput

Optional. The configuration for evaluators. You should only set `evaluatorConfig.acceleratorConfig` if `evaluatorType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `evaluatorConfig.imageUri` only if you build a custom image for your evaluator. If `evaluatorConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputPtrOutput) EvaluatorCount 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) EvaluatorCount() pulumi.StringPtrOutput

Optional. The number of evaluator replicas to use for the training job. Each replica in the cluster will be of the type specified in `evaluator_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `evaluator_type`. The default value is zero.

func (GoogleCloudMlV1__TrainingInputPtrOutput) EvaluatorType 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) EvaluatorType() pulumi.StringPtrOutput

Optional. Specifies the type of virtual machine to use for your training job's evaluator nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `evaluatorCount` is greater than zero.

func (GoogleCloudMlV1__TrainingInputPtrOutput) Hyperparameters 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) Hyperparameters() GoogleCloudMlV1__HyperparameterSpecPtrOutput

Optional. The set of Hyperparameters to tune.

func (GoogleCloudMlV1__TrainingInputPtrOutput) JobDir 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) JobDir() pulumi.StringPtrOutput

Optional. A Google Cloud Storage path in which to store training outputs and other data needed for training. This path is passed to your TensorFlow program as the '--job-dir' command-line argument. The benefit of specifying this field is that Cloud ML validates the path for use in training.

func (GoogleCloudMlV1__TrainingInputPtrOutput) MasterConfig 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) MasterConfig() GoogleCloudMlV1__ReplicaConfigPtrOutput

Optional. The configuration for your master worker. You should only set `masterConfig.acceleratorConfig` if `masterType` is set to a Compute Engine machine type. Learn about [restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `masterConfig.imageUri` only if you build a custom image. Only one of `masterConfig.imageUri` and `runtimeVersion` should be set. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputPtrOutput) MasterType 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) MasterType() pulumi.StringPtrOutput

Optional. Specifies the type of virtual machine to use for your training job's master worker. You must specify this field when `scaleTier` is set to `CUSTOM`. You can use certain Compute Engine machine types directly in this field. See the [list of compatible Compute Engine machine types](/ai-platform/training/docs/machine-types#compute-engine-machine-types). Alternatively, you can use the certain legacy machine types in this field. See the [list of legacy machine types](/ai-platform/training/docs/machine-types#legacy-machine-types). Finally, if you want to use a TPU for training, specify `cloud_tpu` in this field. Learn more about the [special configuration options for training with TPUs](/ai-platform/training/docs/using-tpus#configuring_a_custom_tpu_machine).

func (GoogleCloudMlV1__TrainingInputPtrOutput) Network 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) Network() pulumi.StringPtrOutput

Optional. The full name of the [Compute Engine network](/vpc/docs/vpc) to which the Job is peered. For example, `projects/12345/global/networks/myVPC`. The format of this field is `projects/{project}/global/networks/{network}`, where {project} is a project number (like `12345`) and {network} is network name. Private services access must already be configured for the network. If left unspecified, the Job is not peered with any network. [Learn about using VPC Network Peering.](/ai-platform/training/docs/vpc-peering).

func (GoogleCloudMlV1__TrainingInputPtrOutput) PackageUris 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) PackageUris() pulumi.StringArrayOutput

The Google Cloud Storage location of the packages with the training program and any additional dependencies. The maximum number of package URIs is 100.

func (GoogleCloudMlV1__TrainingInputPtrOutput) ParameterServerConfig 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) ParameterServerConfig() GoogleCloudMlV1__ReplicaConfigPtrOutput

Optional. The configuration for parameter servers. You should only set `parameterServerConfig.acceleratorConfig` if `parameterServerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `parameterServerConfig.imageUri` only if you build a custom image for your parameter server. If `parameterServerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputPtrOutput) ParameterServerCount 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) ParameterServerCount() pulumi.StringPtrOutput

Optional. The number of parameter server replicas to use for the training job. Each replica in the cluster will be of the type specified in `parameter_server_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `parameter_server_type`. The default value is zero.

func (GoogleCloudMlV1__TrainingInputPtrOutput) ParameterServerType 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) ParameterServerType() pulumi.StringPtrOutput

Optional. Specifies the type of virtual machine to use for your training job's parameter server. The supported values are the same as those described in the entry for `master_type`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `parameter_server_count` is greater than zero.

func (GoogleCloudMlV1__TrainingInputPtrOutput) PythonModule 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) PythonModule() pulumi.StringPtrOutput

The Python module name to run after installing the packages.

func (GoogleCloudMlV1__TrainingInputPtrOutput) PythonVersion 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) PythonVersion() pulumi.StringPtrOutput

Optional. The version of Python used in training. You must either specify this field or specify `masterConfig.imageUri`. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).

func (GoogleCloudMlV1__TrainingInputPtrOutput) Region 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) Region() pulumi.StringPtrOutput

The region to run the training job in. See the [available regions](/ai-platform/training/docs/regions) for AI Platform Training.

func (GoogleCloudMlV1__TrainingInputPtrOutput) RuntimeVersion 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) RuntimeVersion() pulumi.StringPtrOutput

Optional. The AI Platform runtime version to use for training. You must either specify this field or specify `masterConfig.imageUri`. For more information, see the [runtime version list](/ai-platform/training/docs/runtime-version-list) and learn [how to manage runtime versions](/ai-platform/training/docs/versioning).

func (GoogleCloudMlV1__TrainingInputPtrOutput) ScaleTier 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) ScaleTier() GoogleCloudMlV1__TrainingInputScaleTierPtrOutput

Specifies the machine types, the number of replicas for workers and parameter servers.

func (GoogleCloudMlV1__TrainingInputPtrOutput) Scheduling 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) Scheduling() GoogleCloudMlV1__SchedulingPtrOutput

Optional. Scheduling options for a training job.

func (GoogleCloudMlV1__TrainingInputPtrOutput) ServiceAccount 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) ServiceAccount() pulumi.StringPtrOutput

Optional. The email address of a service account to use when running the training appplication. You must have the `iam.serviceAccounts.actAs` permission for the specified service account. In addition, the AI Platform Training Google-managed service account must have the `roles/iam.serviceAccountAdmin` role for the specified service account. [Learn more about configuring a service account.](/ai-platform/training/docs/custom-service-account) If not specified, the AI Platform Training Google-managed service account is used by default.

func (GoogleCloudMlV1__TrainingInputPtrOutput) ToGoogleCloudMlV1__TrainingInputPtrOutput 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) ToGoogleCloudMlV1__TrainingInputPtrOutput() GoogleCloudMlV1__TrainingInputPtrOutput

func (GoogleCloudMlV1__TrainingInputPtrOutput) ToGoogleCloudMlV1__TrainingInputPtrOutputWithContext 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) ToGoogleCloudMlV1__TrainingInputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputPtrOutput

func (GoogleCloudMlV1__TrainingInputPtrOutput) UseChiefInTfConfig 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) UseChiefInTfConfig() pulumi.BoolPtrOutput

Optional. Use `chief` instead of `master` in the `TF_CONFIG` environment variable when training with a custom container. Defaults to `false`. [Learn more about this field.](/ai-platform/training/docs/distributed-training-details#chief-versus-master) This field has no effect for training jobs that don't use a custom container.

func (GoogleCloudMlV1__TrainingInputPtrOutput) WorkerConfig 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) WorkerConfig() GoogleCloudMlV1__ReplicaConfigPtrOutput

Optional. The configuration for workers. You should only set `workerConfig.acceleratorConfig` if `workerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `workerConfig.imageUri` only if you build a custom image for your worker. If `workerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputPtrOutput) WorkerCount 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) WorkerCount() pulumi.StringPtrOutput

Optional. The number of worker replicas to use for the training job. Each replica in the cluster will be of the type specified in `worker_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `worker_type`. The default value is zero.

func (GoogleCloudMlV1__TrainingInputPtrOutput) WorkerType 

func (o GoogleCloudMlV1__TrainingInputPtrOutput) WorkerType() pulumi.StringPtrOutput

Optional. Specifies the type of virtual machine to use for your training job's worker nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. If you use `cloud_tpu` for this value, see special instructions for [configuring a custom TPU machine](/ml-engine/docs/tensorflow/using-tpus#configuring_a_custom_tpu_machine). This value must be present when `scaleTier` is set to `CUSTOM` and `workerCount` is greater than zero.

type GoogleCloudMlV1__TrainingInputResponse 

type GoogleCloudMlV1__TrainingInputResponse struct {
	// Optional. Command-line arguments passed to the training application when it starts. If your job uses a custom container, then the arguments are passed to the container's `ENTRYPOINT` command.
	Args []string `pulumi:"args"`
	// Optional. Whether you want AI Platform Training to enable [interactive shell access](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by TrainingOutput.web_access_uris or HyperparameterOutput.web_access_uris (within TrainingOutput.trials).
	EnableWebAccess bool `pulumi:"enableWebAccess"`
	// Optional. Options for using customer-managed encryption keys (CMEK) to protect resources created by a training job, instead of using Google's default encryption. If this is set, then all resources created by the training job will be encrypted with the customer-managed encryption key that you specify. [Learn how and when to use CMEK with AI Platform Training](/ai-platform/training/docs/cmek).
	EncryptionConfig GoogleCloudMlV1__EncryptionConfigResponse `pulumi:"encryptionConfig"`
	// Optional. The configuration for evaluators. You should only set `evaluatorConfig.acceleratorConfig` if `evaluatorType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `evaluatorConfig.imageUri` only if you build a custom image for your evaluator. If `evaluatorConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	EvaluatorConfig GoogleCloudMlV1__ReplicaConfigResponse `pulumi:"evaluatorConfig"`
	// Optional. The number of evaluator replicas to use for the training job. Each replica in the cluster will be of the type specified in `evaluator_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `evaluator_type`. The default value is zero.
	EvaluatorCount string `pulumi:"evaluatorCount"`
	// Optional. Specifies the type of virtual machine to use for your training job's evaluator nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `evaluatorCount` is greater than zero.
	EvaluatorType string `pulumi:"evaluatorType"`
	// Optional. The set of Hyperparameters to tune.
	Hyperparameters GoogleCloudMlV1__HyperparameterSpecResponse `pulumi:"hyperparameters"`
	// Optional. A Google Cloud Storage path in which to store training outputs and other data needed for training. This path is passed to your TensorFlow program as the '--job-dir' command-line argument. The benefit of specifying this field is that Cloud ML validates the path for use in training.
	JobDir string `pulumi:"jobDir"`
	// Optional. The configuration for your master worker. You should only set `masterConfig.acceleratorConfig` if `masterType` is set to a Compute Engine machine type. Learn about [restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `masterConfig.imageUri` only if you build a custom image. Only one of `masterConfig.imageUri` and `runtimeVersion` should be set. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	MasterConfig GoogleCloudMlV1__ReplicaConfigResponse `pulumi:"masterConfig"`
	// Optional. Specifies the type of virtual machine to use for your training job's master worker. You must specify this field when `scaleTier` is set to `CUSTOM`. You can use certain Compute Engine machine types directly in this field. See the [list of compatible Compute Engine machine types](/ai-platform/training/docs/machine-types#compute-engine-machine-types). Alternatively, you can use the certain legacy machine types in this field. See the [list of legacy machine types](/ai-platform/training/docs/machine-types#legacy-machine-types). Finally, if you want to use a TPU for training, specify `cloud_tpu` in this field. Learn more about the [special configuration options for training with TPUs](/ai-platform/training/docs/using-tpus#configuring_a_custom_tpu_machine).
	MasterType string `pulumi:"masterType"`
	// Optional. The full name of the [Compute Engine network](/vpc/docs/vpc) to which the Job is peered. For example, `projects/12345/global/networks/myVPC`. The format of this field is `projects/{project}/global/networks/{network}`, where {project} is a project number (like `12345`) and {network} is network name. Private services access must already be configured for the network. If left unspecified, the Job is not peered with any network. [Learn about using VPC Network Peering.](/ai-platform/training/docs/vpc-peering).
	Network string `pulumi:"network"`
	// The Google Cloud Storage location of the packages with the training program and any additional dependencies. The maximum number of package URIs is 100.
	PackageUris []string `pulumi:"packageUris"`
	// Optional. The configuration for parameter servers. You should only set `parameterServerConfig.acceleratorConfig` if `parameterServerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `parameterServerConfig.imageUri` only if you build a custom image for your parameter server. If `parameterServerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	ParameterServerConfig GoogleCloudMlV1__ReplicaConfigResponse `pulumi:"parameterServerConfig"`
	// Optional. The number of parameter server replicas to use for the training job. Each replica in the cluster will be of the type specified in `parameter_server_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `parameter_server_type`. The default value is zero.
	ParameterServerCount string `pulumi:"parameterServerCount"`
	// Optional. Specifies the type of virtual machine to use for your training job's parameter server. The supported values are the same as those described in the entry for `master_type`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `parameter_server_count` is greater than zero.
	ParameterServerType string `pulumi:"parameterServerType"`
	// The Python module name to run after installing the packages.
	PythonModule string `pulumi:"pythonModule"`
	// Optional. The version of Python used in training. You must either specify this field or specify `masterConfig.imageUri`. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).
	PythonVersion string `pulumi:"pythonVersion"`
	// The region to run the training job in. See the [available regions](/ai-platform/training/docs/regions) for AI Platform Training.
	Region string `pulumi:"region"`
	// Optional. The AI Platform runtime version to use for training. You must either specify this field or specify `masterConfig.imageUri`. For more information, see the [runtime version list](/ai-platform/training/docs/runtime-version-list) and learn [how to manage runtime versions](/ai-platform/training/docs/versioning).
	RuntimeVersion string `pulumi:"runtimeVersion"`
	// Specifies the machine types, the number of replicas for workers and parameter servers.
	ScaleTier string `pulumi:"scaleTier"`
	// Optional. Scheduling options for a training job.
	Scheduling GoogleCloudMlV1__SchedulingResponse `pulumi:"scheduling"`
	// Optional. The email address of a service account to use when running the training appplication. You must have the `iam.serviceAccounts.actAs` permission for the specified service account. In addition, the AI Platform Training Google-managed service account must have the `roles/iam.serviceAccountAdmin` role for the specified service account. [Learn more about configuring a service account.](/ai-platform/training/docs/custom-service-account) If not specified, the AI Platform Training Google-managed service account is used by default.
	ServiceAccount string `pulumi:"serviceAccount"`
	// Optional. Use `chief` instead of `master` in the `TF_CONFIG` environment variable when training with a custom container. Defaults to `false`. [Learn more about this field.](/ai-platform/training/docs/distributed-training-details#chief-versus-master) This field has no effect for training jobs that don't use a custom container.
	UseChiefInTfConfig bool `pulumi:"useChiefInTfConfig"`
	// Optional. The configuration for workers. You should only set `workerConfig.acceleratorConfig` if `workerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `workerConfig.imageUri` only if you build a custom image for your worker. If `workerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).
	WorkerConfig GoogleCloudMlV1__ReplicaConfigResponse `pulumi:"workerConfig"`
	// Optional. The number of worker replicas to use for the training job. Each replica in the cluster will be of the type specified in `worker_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `worker_type`. The default value is zero.
	WorkerCount string `pulumi:"workerCount"`
	// Optional. Specifies the type of virtual machine to use for your training job's worker nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. If you use `cloud_tpu` for this value, see special instructions for [configuring a custom TPU machine](/ml-engine/docs/tensorflow/using-tpus#configuring_a_custom_tpu_machine). This value must be present when `scaleTier` is set to `CUSTOM` and `workerCount` is greater than zero.
	WorkerType string `pulumi:"workerType"`
}

Represents input parameters for a training job. When using the gcloud command to submit your training job, you can specify the input parameters as command-line arguments and/or in a YAML configuration file referenced from the --config command-line argument. For details, see the guide to [submitting a training job](/ai-platform/training/docs/training-jobs).

type GoogleCloudMlV1__TrainingInputResponseOutput 

type GoogleCloudMlV1__TrainingInputResponseOutput struct{ *pulumi.OutputState }

Represents input parameters for a training job. When using the gcloud command to submit your training job, you can specify the input parameters as command-line arguments and/or in a YAML configuration file referenced from the --config command-line argument. For details, see the guide to [submitting a training job](/ai-platform/training/docs/training-jobs).

func (GoogleCloudMlV1__TrainingInputResponseOutput) Args 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) Args() pulumi.StringArrayOutput

Optional. Command-line arguments passed to the training application when it starts. If your job uses a custom container, then the arguments are passed to the container's `ENTRYPOINT` command.

func (GoogleCloudMlV1__TrainingInputResponseOutput) ElementType 

func (GoogleCloudMlV1__TrainingInputResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingInputResponseOutput) EnableWebAccess added in v0.5.0 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) EnableWebAccess() pulumi.BoolOutput

Optional. Whether you want AI Platform Training to enable [interactive shell access](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by TrainingOutput.web_access_uris or HyperparameterOutput.web_access_uris (within TrainingOutput.trials).

func (GoogleCloudMlV1__TrainingInputResponseOutput) EncryptionConfig 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) EncryptionConfig() GoogleCloudMlV1__EncryptionConfigResponseOutput

Optional. Options for using customer-managed encryption keys (CMEK) to protect resources created by a training job, instead of using Google's default encryption. If this is set, then all resources created by the training job will be encrypted with the customer-managed encryption key that you specify. [Learn how and when to use CMEK with AI Platform Training](/ai-platform/training/docs/cmek).

func (GoogleCloudMlV1__TrainingInputResponseOutput) EvaluatorConfig 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) EvaluatorConfig() GoogleCloudMlV1__ReplicaConfigResponseOutput

Optional. The configuration for evaluators. You should only set `evaluatorConfig.acceleratorConfig` if `evaluatorType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `evaluatorConfig.imageUri` only if you build a custom image for your evaluator. If `evaluatorConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputResponseOutput) EvaluatorCount 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) EvaluatorCount() pulumi.StringOutput

Optional. The number of evaluator replicas to use for the training job. Each replica in the cluster will be of the type specified in `evaluator_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `evaluator_type`. The default value is zero.

func (GoogleCloudMlV1__TrainingInputResponseOutput) EvaluatorType 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) EvaluatorType() pulumi.StringOutput

Optional. Specifies the type of virtual machine to use for your training job's evaluator nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `evaluatorCount` is greater than zero.

func (GoogleCloudMlV1__TrainingInputResponseOutput) Hyperparameters 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) Hyperparameters() GoogleCloudMlV1__HyperparameterSpecResponseOutput

Optional. The set of Hyperparameters to tune.

func (GoogleCloudMlV1__TrainingInputResponseOutput) JobDir 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) JobDir() pulumi.StringOutput

Optional. A Google Cloud Storage path in which to store training outputs and other data needed for training. This path is passed to your TensorFlow program as the '--job-dir' command-line argument. The benefit of specifying this field is that Cloud ML validates the path for use in training.

func (GoogleCloudMlV1__TrainingInputResponseOutput) MasterConfig 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) MasterConfig() GoogleCloudMlV1__ReplicaConfigResponseOutput

Optional. The configuration for your master worker. You should only set `masterConfig.acceleratorConfig` if `masterType` is set to a Compute Engine machine type. Learn about [restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `masterConfig.imageUri` only if you build a custom image. Only one of `masterConfig.imageUri` and `runtimeVersion` should be set. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputResponseOutput) MasterType 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) MasterType() pulumi.StringOutput

Optional. Specifies the type of virtual machine to use for your training job's master worker. You must specify this field when `scaleTier` is set to `CUSTOM`. You can use certain Compute Engine machine types directly in this field. See the [list of compatible Compute Engine machine types](/ai-platform/training/docs/machine-types#compute-engine-machine-types). Alternatively, you can use the certain legacy machine types in this field. See the [list of legacy machine types](/ai-platform/training/docs/machine-types#legacy-machine-types). Finally, if you want to use a TPU for training, specify `cloud_tpu` in this field. Learn more about the [special configuration options for training with TPUs](/ai-platform/training/docs/using-tpus#configuring_a_custom_tpu_machine).

func (GoogleCloudMlV1__TrainingInputResponseOutput) Network 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) Network() pulumi.StringOutput

Optional. The full name of the [Compute Engine network](/vpc/docs/vpc) to which the Job is peered. For example, `projects/12345/global/networks/myVPC`. The format of this field is `projects/{project}/global/networks/{network}`, where {project} is a project number (like `12345`) and {network} is network name. Private services access must already be configured for the network. If left unspecified, the Job is not peered with any network. [Learn about using VPC Network Peering.](/ai-platform/training/docs/vpc-peering).

func (GoogleCloudMlV1__TrainingInputResponseOutput) PackageUris 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) PackageUris() pulumi.StringArrayOutput

The Google Cloud Storage location of the packages with the training program and any additional dependencies. The maximum number of package URIs is 100.

func (GoogleCloudMlV1__TrainingInputResponseOutput) ParameterServerConfig 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) ParameterServerConfig() GoogleCloudMlV1__ReplicaConfigResponseOutput

Optional. The configuration for parameter servers. You should only set `parameterServerConfig.acceleratorConfig` if `parameterServerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `parameterServerConfig.imageUri` only if you build a custom image for your parameter server. If `parameterServerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputResponseOutput) ParameterServerCount 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) ParameterServerCount() pulumi.StringOutput

Optional. The number of parameter server replicas to use for the training job. Each replica in the cluster will be of the type specified in `parameter_server_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `parameter_server_type`. The default value is zero.

func (GoogleCloudMlV1__TrainingInputResponseOutput) ParameterServerType 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) ParameterServerType() pulumi.StringOutput

Optional. Specifies the type of virtual machine to use for your training job's parameter server. The supported values are the same as those described in the entry for `master_type`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. This value must be present when `scaleTier` is set to `CUSTOM` and `parameter_server_count` is greater than zero.

func (GoogleCloudMlV1__TrainingInputResponseOutput) PythonModule 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) PythonModule() pulumi.StringOutput

The Python module name to run after installing the packages.

func (GoogleCloudMlV1__TrainingInputResponseOutput) PythonVersion 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) PythonVersion() pulumi.StringOutput

Optional. The version of Python used in training. You must either specify this field or specify `masterConfig.imageUri`. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).

func (GoogleCloudMlV1__TrainingInputResponseOutput) Region 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) Region() pulumi.StringOutput

The region to run the training job in. See the [available regions](/ai-platform/training/docs/regions) for AI Platform Training.

func (GoogleCloudMlV1__TrainingInputResponseOutput) RuntimeVersion 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) RuntimeVersion() pulumi.StringOutput

Optional. The AI Platform runtime version to use for training. You must either specify this field or specify `masterConfig.imageUri`. For more information, see the [runtime version list](/ai-platform/training/docs/runtime-version-list) and learn [how to manage runtime versions](/ai-platform/training/docs/versioning).

func (GoogleCloudMlV1__TrainingInputResponseOutput) ScaleTier 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) ScaleTier() pulumi.StringOutput

Specifies the machine types, the number of replicas for workers and parameter servers.

func (GoogleCloudMlV1__TrainingInputResponseOutput) Scheduling 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) Scheduling() GoogleCloudMlV1__SchedulingResponseOutput

Optional. Scheduling options for a training job.

func (GoogleCloudMlV1__TrainingInputResponseOutput) ServiceAccount 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) ServiceAccount() pulumi.StringOutput

Optional. The email address of a service account to use when running the training appplication. You must have the `iam.serviceAccounts.actAs` permission for the specified service account. In addition, the AI Platform Training Google-managed service account must have the `roles/iam.serviceAccountAdmin` role for the specified service account. [Learn more about configuring a service account.](/ai-platform/training/docs/custom-service-account) If not specified, the AI Platform Training Google-managed service account is used by default.

func (GoogleCloudMlV1__TrainingInputResponseOutput) ToGoogleCloudMlV1__TrainingInputResponseOutput 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) ToGoogleCloudMlV1__TrainingInputResponseOutput() GoogleCloudMlV1__TrainingInputResponseOutput

func (GoogleCloudMlV1__TrainingInputResponseOutput) ToGoogleCloudMlV1__TrainingInputResponseOutputWithContext 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) ToGoogleCloudMlV1__TrainingInputResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputResponseOutput

func (GoogleCloudMlV1__TrainingInputResponseOutput) UseChiefInTfConfig 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) UseChiefInTfConfig() pulumi.BoolOutput

Optional. Use `chief` instead of `master` in the `TF_CONFIG` environment variable when training with a custom container. Defaults to `false`. [Learn more about this field.](/ai-platform/training/docs/distributed-training-details#chief-versus-master) This field has no effect for training jobs that don't use a custom container.

func (GoogleCloudMlV1__TrainingInputResponseOutput) WorkerConfig 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) WorkerConfig() GoogleCloudMlV1__ReplicaConfigResponseOutput

Optional. The configuration for workers. You should only set `workerConfig.acceleratorConfig` if `workerType` is set to a Compute Engine machine type. [Learn about restrictions on accelerator configurations for training.](/ai-platform/training/docs/using-gpus#compute-engine-machine-types-with-gpu) Set `workerConfig.imageUri` only if you build a custom image for your worker. If `workerConfig.imageUri` has not been set, AI Platform uses the value of `masterConfig.imageUri`. Learn more about [configuring custom containers](/ai-platform/training/docs/distributed-training-containers).

func (GoogleCloudMlV1__TrainingInputResponseOutput) WorkerCount 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) WorkerCount() pulumi.StringOutput

Optional. The number of worker replicas to use for the training job. Each replica in the cluster will be of the type specified in `worker_type`. This value can only be used when `scale_tier` is set to `CUSTOM`. If you set this value, you must also set `worker_type`. The default value is zero.

func (GoogleCloudMlV1__TrainingInputResponseOutput) WorkerType 

func (o GoogleCloudMlV1__TrainingInputResponseOutput) WorkerType() pulumi.StringOutput

Optional. Specifies the type of virtual machine to use for your training job's worker nodes. The supported values are the same as those described in the entry for `masterType`. This value must be consistent with the category of machine type that `masterType` uses. In other words, both must be Compute Engine machine types or both must be legacy machine types. If you use `cloud_tpu` for this value, see special instructions for [configuring a custom TPU machine](/ml-engine/docs/tensorflow/using-tpus#configuring_a_custom_tpu_machine). This value must be present when `scaleTier` is set to `CUSTOM` and `workerCount` is greater than zero.

type GoogleCloudMlV1__TrainingInputScaleTier added in v0.4.0 

type GoogleCloudMlV1__TrainingInputScaleTier string

Required. Specifies the machine types, the number of replicas for workers and parameter servers.

func (GoogleCloudMlV1__TrainingInputScaleTier) ElementType added in v0.4.0 

func (GoogleCloudMlV1__TrainingInputScaleTier) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingInputScaleTier) ToGoogleCloudMlV1__TrainingInputScaleTierOutput added in v0.6.0 

func (e GoogleCloudMlV1__TrainingInputScaleTier) ToGoogleCloudMlV1__TrainingInputScaleTierOutput() GoogleCloudMlV1__TrainingInputScaleTierOutput

func (GoogleCloudMlV1__TrainingInputScaleTier) ToGoogleCloudMlV1__TrainingInputScaleTierOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__TrainingInputScaleTier) ToGoogleCloudMlV1__TrainingInputScaleTierOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputScaleTierOutput

func (GoogleCloudMlV1__TrainingInputScaleTier) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutput added in v0.6.0 

func (e GoogleCloudMlV1__TrainingInputScaleTier) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutput() GoogleCloudMlV1__TrainingInputScaleTierPtrOutput

func (GoogleCloudMlV1__TrainingInputScaleTier) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutputWithContext added in v0.6.0 

func (e GoogleCloudMlV1__TrainingInputScaleTier) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputScaleTierPtrOutput

func (GoogleCloudMlV1__TrainingInputScaleTier) ToStringOutput added in v0.4.0 

func (e GoogleCloudMlV1__TrainingInputScaleTier) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__TrainingInputScaleTier) ToStringOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__TrainingInputScaleTier) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__TrainingInputScaleTier) ToStringPtrOutput added in v0.4.0 

func (e GoogleCloudMlV1__TrainingInputScaleTier) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__TrainingInputScaleTier) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleCloudMlV1__TrainingInputScaleTier) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__TrainingInputScaleTierInput added in v0.6.0 

type GoogleCloudMlV1__TrainingInputScaleTierInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__TrainingInputScaleTierOutput() GoogleCloudMlV1__TrainingInputScaleTierOutput
	ToGoogleCloudMlV1__TrainingInputScaleTierOutputWithContext(context.Context) GoogleCloudMlV1__TrainingInputScaleTierOutput
}

GoogleCloudMlV1__TrainingInputScaleTierInput is an input type that accepts GoogleCloudMlV1__TrainingInputScaleTierArgs and GoogleCloudMlV1__TrainingInputScaleTierOutput values. You can construct a concrete instance of `GoogleCloudMlV1__TrainingInputScaleTierInput` via: 

GoogleCloudMlV1__TrainingInputScaleTierArgs{...}

type GoogleCloudMlV1__TrainingInputScaleTierOutput added in v0.6.0 

type GoogleCloudMlV1__TrainingInputScaleTierOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ToGoogleCloudMlV1__TrainingInputScaleTierOutput added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierOutput) ToGoogleCloudMlV1__TrainingInputScaleTierOutput() GoogleCloudMlV1__TrainingInputScaleTierOutput

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ToGoogleCloudMlV1__TrainingInputScaleTierOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierOutput) ToGoogleCloudMlV1__TrainingInputScaleTierOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputScaleTierOutput

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierOutput) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutput() GoogleCloudMlV1__TrainingInputScaleTierPtrOutput

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierOutput) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputScaleTierPtrOutput

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ToStringOutput added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierOutput) ToStringOutput() pulumi.StringOutput

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__TrainingInputScaleTierOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__TrainingInputScaleTierPtrInput added in v0.6.0 

type GoogleCloudMlV1__TrainingInputScaleTierPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutput() GoogleCloudMlV1__TrainingInputScaleTierPtrOutput
	ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutputWithContext(context.Context) GoogleCloudMlV1__TrainingInputScaleTierPtrOutput
}

func GoogleCloudMlV1__TrainingInputScaleTierPtr added in v0.6.0 

func GoogleCloudMlV1__TrainingInputScaleTierPtr(v string) GoogleCloudMlV1__TrainingInputScaleTierPtrInput

type GoogleCloudMlV1__TrainingInputScaleTierPtrOutput added in v0.6.0 

type GoogleCloudMlV1__TrainingInputScaleTierPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) Elem added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) Elem() GoogleCloudMlV1__TrainingInputScaleTierOutput

func (GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ElementType added in v0.6.0 

func (GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutput() GoogleCloudMlV1__TrainingInputScaleTierPtrOutput

func (GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ToGoogleCloudMlV1__TrainingInputScaleTierPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingInputScaleTierPtrOutput

func (GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleCloudMlV1__TrainingInputScaleTierPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleCloudMlV1__TrainingOutput 

type GoogleCloudMlV1__TrainingOutput struct {
	// Details related to built-in algorithms jobs. Only set for built-in algorithms jobs.
	BuiltInAlgorithmOutput *GoogleCloudMlV1__BuiltInAlgorithmOutput `pulumi:"builtInAlgorithmOutput"`
	// The number of hyperparameter tuning trials that completed successfully. Only set for hyperparameter tuning jobs.
	CompletedTrialCount *string `pulumi:"completedTrialCount"`
	// The amount of ML units consumed by the job.
	ConsumedMLUnits *float64 `pulumi:"consumedMLUnits"`
	// The TensorFlow summary tag name used for optimizing hyperparameter tuning trials. See [`HyperparameterSpec.hyperparameterMetricTag`](#HyperparameterSpec.FIELDS.hyperparameter_metric_tag) for more information. Only set for hyperparameter tuning jobs.
	HyperparameterMetricTag *string `pulumi:"hyperparameterMetricTag"`
	// Whether this job is a built-in Algorithm job.
	IsBuiltInAlgorithmJob *bool `pulumi:"isBuiltInAlgorithmJob"`
	// Whether this job is a hyperparameter tuning job.
	IsHyperparameterTuningJob *bool `pulumi:"isHyperparameterTuningJob"`
	// Results for individual Hyperparameter trials. Only set for hyperparameter tuning jobs.
	Trials []GoogleCloudMlV1__HyperparameterOutput `pulumi:"trials"`
}

Represents results of a training job. Output only.

type GoogleCloudMlV1__TrainingOutputArgs 

type GoogleCloudMlV1__TrainingOutputArgs struct {
	// Details related to built-in algorithms jobs. Only set for built-in algorithms jobs.
	BuiltInAlgorithmOutput GoogleCloudMlV1__BuiltInAlgorithmOutputPtrInput `pulumi:"builtInAlgorithmOutput"`
	// The number of hyperparameter tuning trials that completed successfully. Only set for hyperparameter tuning jobs.
	CompletedTrialCount pulumi.StringPtrInput `pulumi:"completedTrialCount"`
	// The amount of ML units consumed by the job.
	ConsumedMLUnits pulumi.Float64PtrInput `pulumi:"consumedMLUnits"`
	// The TensorFlow summary tag name used for optimizing hyperparameter tuning trials. See [`HyperparameterSpec.hyperparameterMetricTag`](#HyperparameterSpec.FIELDS.hyperparameter_metric_tag) for more information. Only set for hyperparameter tuning jobs.
	HyperparameterMetricTag pulumi.StringPtrInput `pulumi:"hyperparameterMetricTag"`
	// Whether this job is a built-in Algorithm job.
	IsBuiltInAlgorithmJob pulumi.BoolPtrInput `pulumi:"isBuiltInAlgorithmJob"`
	// Whether this job is a hyperparameter tuning job.
	IsHyperparameterTuningJob pulumi.BoolPtrInput `pulumi:"isHyperparameterTuningJob"`
	// Results for individual Hyperparameter trials. Only set for hyperparameter tuning jobs.
	Trials GoogleCloudMlV1__HyperparameterOutputArrayInput `pulumi:"trials"`
}

Represents results of a training job. Output only.

func (GoogleCloudMlV1__TrainingOutputArgs) ElementType 

func (GoogleCloudMlV1__TrainingOutputArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingOutputArgs) ToGoogleCloudMlV1__TrainingOutputOutput 

func (i GoogleCloudMlV1__TrainingOutputArgs) ToGoogleCloudMlV1__TrainingOutputOutput() GoogleCloudMlV1__TrainingOutputOutput

func (GoogleCloudMlV1__TrainingOutputArgs) ToGoogleCloudMlV1__TrainingOutputOutputWithContext 

func (i GoogleCloudMlV1__TrainingOutputArgs) ToGoogleCloudMlV1__TrainingOutputOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingOutputOutput

func (GoogleCloudMlV1__TrainingOutputArgs) ToGoogleCloudMlV1__TrainingOutputPtrOutput 

func (i GoogleCloudMlV1__TrainingOutputArgs) ToGoogleCloudMlV1__TrainingOutputPtrOutput() GoogleCloudMlV1__TrainingOutputPtrOutput

func (GoogleCloudMlV1__TrainingOutputArgs) ToGoogleCloudMlV1__TrainingOutputPtrOutputWithContext 

func (i GoogleCloudMlV1__TrainingOutputArgs) ToGoogleCloudMlV1__TrainingOutputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingOutputPtrOutput

type GoogleCloudMlV1__TrainingOutputInput 

type GoogleCloudMlV1__TrainingOutputInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__TrainingOutputOutput() GoogleCloudMlV1__TrainingOutputOutput
	ToGoogleCloudMlV1__TrainingOutputOutputWithContext(context.Context) GoogleCloudMlV1__TrainingOutputOutput
}

GoogleCloudMlV1__TrainingOutputInput is an input type that accepts GoogleCloudMlV1__TrainingOutputArgs and GoogleCloudMlV1__TrainingOutputOutput values. You can construct a concrete instance of `GoogleCloudMlV1__TrainingOutputInput` via: 

GoogleCloudMlV1__TrainingOutputArgs{...}

type GoogleCloudMlV1__TrainingOutputOutput 

type GoogleCloudMlV1__TrainingOutputOutput struct{ *pulumi.OutputState }

Represents results of a training job. Output only.

func (GoogleCloudMlV1__TrainingOutputOutput) BuiltInAlgorithmOutput 

func (o GoogleCloudMlV1__TrainingOutputOutput) BuiltInAlgorithmOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput

Details related to built-in algorithms jobs. Only set for built-in algorithms jobs.

func (GoogleCloudMlV1__TrainingOutputOutput) CompletedTrialCount 

func (o GoogleCloudMlV1__TrainingOutputOutput) CompletedTrialCount() pulumi.StringPtrOutput

The number of hyperparameter tuning trials that completed successfully. Only set for hyperparameter tuning jobs.

func (GoogleCloudMlV1__TrainingOutputOutput) ConsumedMLUnits 

func (o GoogleCloudMlV1__TrainingOutputOutput) ConsumedMLUnits() pulumi.Float64PtrOutput

The amount of ML units consumed by the job.

func (GoogleCloudMlV1__TrainingOutputOutput) ElementType 

func (GoogleCloudMlV1__TrainingOutputOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingOutputOutput) HyperparameterMetricTag 

func (o GoogleCloudMlV1__TrainingOutputOutput) HyperparameterMetricTag() pulumi.StringPtrOutput

The TensorFlow summary tag name used for optimizing hyperparameter tuning trials. See [`HyperparameterSpec.hyperparameterMetricTag`](#HyperparameterSpec.FIELDS.hyperparameter_metric_tag) for more information. Only set for hyperparameter tuning jobs.

func (GoogleCloudMlV1__TrainingOutputOutput) IsBuiltInAlgorithmJob 

func (o GoogleCloudMlV1__TrainingOutputOutput) IsBuiltInAlgorithmJob() pulumi.BoolPtrOutput

Whether this job is a built-in Algorithm job.

func (GoogleCloudMlV1__TrainingOutputOutput) IsHyperparameterTuningJob 

func (o GoogleCloudMlV1__TrainingOutputOutput) IsHyperparameterTuningJob() pulumi.BoolPtrOutput

Whether this job is a hyperparameter tuning job.

func (GoogleCloudMlV1__TrainingOutputOutput) ToGoogleCloudMlV1__TrainingOutputOutput 

func (o GoogleCloudMlV1__TrainingOutputOutput) ToGoogleCloudMlV1__TrainingOutputOutput() GoogleCloudMlV1__TrainingOutputOutput

func (GoogleCloudMlV1__TrainingOutputOutput) ToGoogleCloudMlV1__TrainingOutputOutputWithContext 

func (o GoogleCloudMlV1__TrainingOutputOutput) ToGoogleCloudMlV1__TrainingOutputOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingOutputOutput

func (GoogleCloudMlV1__TrainingOutputOutput) ToGoogleCloudMlV1__TrainingOutputPtrOutput 

func (o GoogleCloudMlV1__TrainingOutputOutput) ToGoogleCloudMlV1__TrainingOutputPtrOutput() GoogleCloudMlV1__TrainingOutputPtrOutput

func (GoogleCloudMlV1__TrainingOutputOutput) ToGoogleCloudMlV1__TrainingOutputPtrOutputWithContext 

func (o GoogleCloudMlV1__TrainingOutputOutput) ToGoogleCloudMlV1__TrainingOutputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingOutputPtrOutput

func (GoogleCloudMlV1__TrainingOutputOutput) Trials 

func (o GoogleCloudMlV1__TrainingOutputOutput) Trials() GoogleCloudMlV1__HyperparameterOutputArrayOutput

Results for individual Hyperparameter trials. Only set for hyperparameter tuning jobs.

type GoogleCloudMlV1__TrainingOutputPtrInput 

type GoogleCloudMlV1__TrainingOutputPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__TrainingOutputPtrOutput() GoogleCloudMlV1__TrainingOutputPtrOutput
	ToGoogleCloudMlV1__TrainingOutputPtrOutputWithContext(context.Context) GoogleCloudMlV1__TrainingOutputPtrOutput
}

GoogleCloudMlV1__TrainingOutputPtrInput is an input type that accepts GoogleCloudMlV1__TrainingOutputArgs, GoogleCloudMlV1__TrainingOutputPtr and GoogleCloudMlV1__TrainingOutputPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__TrainingOutputPtrInput` via: 

        GoogleCloudMlV1__TrainingOutputArgs{...}

or:

        nil

func GoogleCloudMlV1__TrainingOutputPtr 

func GoogleCloudMlV1__TrainingOutputPtr(v *GoogleCloudMlV1__TrainingOutputArgs) GoogleCloudMlV1__TrainingOutputPtrInput

type GoogleCloudMlV1__TrainingOutputPtrOutput 

type GoogleCloudMlV1__TrainingOutputPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__TrainingOutputPtrOutput) BuiltInAlgorithmOutput 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) BuiltInAlgorithmOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputPtrOutput

Details related to built-in algorithms jobs. Only set for built-in algorithms jobs.

func (GoogleCloudMlV1__TrainingOutputPtrOutput) CompletedTrialCount 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) CompletedTrialCount() pulumi.StringPtrOutput

The number of hyperparameter tuning trials that completed successfully. Only set for hyperparameter tuning jobs.

func (GoogleCloudMlV1__TrainingOutputPtrOutput) ConsumedMLUnits 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) ConsumedMLUnits() pulumi.Float64PtrOutput

The amount of ML units consumed by the job.

func (GoogleCloudMlV1__TrainingOutputPtrOutput) Elem 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) Elem() GoogleCloudMlV1__TrainingOutputOutput

func (GoogleCloudMlV1__TrainingOutputPtrOutput) ElementType 

func (GoogleCloudMlV1__TrainingOutputPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingOutputPtrOutput) HyperparameterMetricTag 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) HyperparameterMetricTag() pulumi.StringPtrOutput

The TensorFlow summary tag name used for optimizing hyperparameter tuning trials. See [`HyperparameterSpec.hyperparameterMetricTag`](#HyperparameterSpec.FIELDS.hyperparameter_metric_tag) for more information. Only set for hyperparameter tuning jobs.

func (GoogleCloudMlV1__TrainingOutputPtrOutput) IsBuiltInAlgorithmJob 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) IsBuiltInAlgorithmJob() pulumi.BoolPtrOutput

Whether this job is a built-in Algorithm job.

func (GoogleCloudMlV1__TrainingOutputPtrOutput) IsHyperparameterTuningJob 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) IsHyperparameterTuningJob() pulumi.BoolPtrOutput

Whether this job is a hyperparameter tuning job.

func (GoogleCloudMlV1__TrainingOutputPtrOutput) ToGoogleCloudMlV1__TrainingOutputPtrOutput 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) ToGoogleCloudMlV1__TrainingOutputPtrOutput() GoogleCloudMlV1__TrainingOutputPtrOutput

func (GoogleCloudMlV1__TrainingOutputPtrOutput) ToGoogleCloudMlV1__TrainingOutputPtrOutputWithContext 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) ToGoogleCloudMlV1__TrainingOutputPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingOutputPtrOutput

func (GoogleCloudMlV1__TrainingOutputPtrOutput) Trials 

func (o GoogleCloudMlV1__TrainingOutputPtrOutput) Trials() GoogleCloudMlV1__HyperparameterOutputArrayOutput

Results for individual Hyperparameter trials. Only set for hyperparameter tuning jobs.

type GoogleCloudMlV1__TrainingOutputResponse 

type GoogleCloudMlV1__TrainingOutputResponse struct {
	// Details related to built-in algorithms jobs. Only set for built-in algorithms jobs.
	BuiltInAlgorithmOutput GoogleCloudMlV1__BuiltInAlgorithmOutputResponse `pulumi:"builtInAlgorithmOutput"`
	// The number of hyperparameter tuning trials that completed successfully. Only set for hyperparameter tuning jobs.
	CompletedTrialCount string `pulumi:"completedTrialCount"`
	// The amount of ML units consumed by the job.
	ConsumedMLUnits float64 `pulumi:"consumedMLUnits"`
	// The TensorFlow summary tag name used for optimizing hyperparameter tuning trials. See [`HyperparameterSpec.hyperparameterMetricTag`](#HyperparameterSpec.FIELDS.hyperparameter_metric_tag) for more information. Only set for hyperparameter tuning jobs.
	HyperparameterMetricTag string `pulumi:"hyperparameterMetricTag"`
	// Whether this job is a built-in Algorithm job.
	IsBuiltInAlgorithmJob bool `pulumi:"isBuiltInAlgorithmJob"`
	// Whether this job is a hyperparameter tuning job.
	IsHyperparameterTuningJob bool `pulumi:"isHyperparameterTuningJob"`
	// Results for individual Hyperparameter trials. Only set for hyperparameter tuning jobs.
	Trials []GoogleCloudMlV1__HyperparameterOutputResponse `pulumi:"trials"`
	// URIs for accessing [interactive shells](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) (one URI for each training node). Only available if training_input.enable_web_access is `true`. The keys are names of each node in the training job; for example, `master-replica-0` for the master node, `worker-replica-0` for the first worker, and `ps-replica-0` for the first parameter server. The values are the URIs for each node's interactive shell.
	WebAccessUris map[string]string `pulumi:"webAccessUris"`
}

Represents results of a training job. Output only.

type GoogleCloudMlV1__TrainingOutputResponseOutput 

type GoogleCloudMlV1__TrainingOutputResponseOutput struct{ *pulumi.OutputState }

Represents results of a training job. Output only.

func (GoogleCloudMlV1__TrainingOutputResponseOutput) BuiltInAlgorithmOutput 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) BuiltInAlgorithmOutput() GoogleCloudMlV1__BuiltInAlgorithmOutputResponseOutput

Details related to built-in algorithms jobs. Only set for built-in algorithms jobs.

func (GoogleCloudMlV1__TrainingOutputResponseOutput) CompletedTrialCount 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) CompletedTrialCount() pulumi.StringOutput

The number of hyperparameter tuning trials that completed successfully. Only set for hyperparameter tuning jobs.

func (GoogleCloudMlV1__TrainingOutputResponseOutput) ConsumedMLUnits 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) ConsumedMLUnits() pulumi.Float64Output

The amount of ML units consumed by the job.

func (GoogleCloudMlV1__TrainingOutputResponseOutput) ElementType 

func (GoogleCloudMlV1__TrainingOutputResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__TrainingOutputResponseOutput) HyperparameterMetricTag 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) HyperparameterMetricTag() pulumi.StringOutput

The TensorFlow summary tag name used for optimizing hyperparameter tuning trials. See [`HyperparameterSpec.hyperparameterMetricTag`](#HyperparameterSpec.FIELDS.hyperparameter_metric_tag) for more information. Only set for hyperparameter tuning jobs.

func (GoogleCloudMlV1__TrainingOutputResponseOutput) IsBuiltInAlgorithmJob 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) IsBuiltInAlgorithmJob() pulumi.BoolOutput

Whether this job is a built-in Algorithm job.

func (GoogleCloudMlV1__TrainingOutputResponseOutput) IsHyperparameterTuningJob 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) IsHyperparameterTuningJob() pulumi.BoolOutput

Whether this job is a hyperparameter tuning job.

func (GoogleCloudMlV1__TrainingOutputResponseOutput) ToGoogleCloudMlV1__TrainingOutputResponseOutput 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) ToGoogleCloudMlV1__TrainingOutputResponseOutput() GoogleCloudMlV1__TrainingOutputResponseOutput

func (GoogleCloudMlV1__TrainingOutputResponseOutput) ToGoogleCloudMlV1__TrainingOutputResponseOutputWithContext 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) ToGoogleCloudMlV1__TrainingOutputResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__TrainingOutputResponseOutput

func (GoogleCloudMlV1__TrainingOutputResponseOutput) Trials 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) Trials() GoogleCloudMlV1__HyperparameterOutputResponseArrayOutput

Results for individual Hyperparameter trials. Only set for hyperparameter tuning jobs.

func (GoogleCloudMlV1__TrainingOutputResponseOutput) WebAccessUris added in v0.5.0 

func (o GoogleCloudMlV1__TrainingOutputResponseOutput) WebAccessUris() pulumi.StringMapOutput

URIs for accessing [interactive shells](https://cloud.google.com/ai-platform/training/docs/monitor-debug-interactive-shell) (one URI for each training node). Only available if training_input.enable_web_access is `true`. The keys are names of each node in the training job; for example, `master-replica-0` for the master node, `worker-replica-0` for the first worker, and `ps-replica-0` for the first parameter server. The values are the URIs for each node's interactive shell.

type GoogleCloudMlV1__VersionResponse 

type GoogleCloudMlV1__VersionResponse struct {
	// Optional. Accelerator config for using GPUs for online prediction (beta). Only specify this field if you have specified a Compute Engine (N1) machine type in the `machineType` field. Learn more about [using GPUs for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).
	AcceleratorConfig GoogleCloudMlV1__AcceleratorConfigResponse `pulumi:"acceleratorConfig"`
	// Automatically scale the number of nodes used to serve the model in response to increases and decreases in traffic. Care should be taken to ramp up traffic according to the model's ability to scale or you will start seeing increases in latency and 429 response codes.
	AutoScaling GoogleCloudMlV1__AutoScalingResponse `pulumi:"autoScaling"`
	// Optional. Specifies a custom container to use for serving predictions. If you specify this field, then `machineType` is required. If you specify this field, then `deploymentUri` is optional. If you specify this field, then you must not specify `runtimeVersion`, `packageUris`, `framework`, `pythonVersion`, or `predictionClass`.
	Container GoogleCloudMlV1__ContainerSpecResponse `pulumi:"container"`
	// The time the version was created.
	CreateTime string `pulumi:"createTime"`
	// The Cloud Storage URI of a directory containing trained model artifacts to be used to create the model version. See the [guide to deploying models](/ai-platform/prediction/docs/deploying-models) for more information. The total number of files under this directory must not exceed 1000. During projects.models.versions.create, AI Platform Prediction copies all files from the specified directory to a location managed by the service. From then on, AI Platform Prediction uses these copies of the model artifacts to serve predictions, not the original files in Cloud Storage, so this location is useful only as a historical record. If you specify container, then this field is optional. Otherwise, it is required. Learn [how to use this field with a custom container](/ai-platform/prediction/docs/custom-container-requirements#artifacts).
	DeploymentUri string `pulumi:"deploymentUri"`
	// Optional. The description specified for the version when it was created.
	Description string `pulumi:"description"`
	// The details of a failure or a cancellation.
	ErrorMessage string `pulumi:"errorMessage"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetVersion`, and systems are expected to put that etag in the request to `UpdateVersion` to ensure that their change will be applied to the model as intended.
	Etag string `pulumi:"etag"`
	// Optional. Configures explainability features on the model's version. Some explanation features require additional metadata to be loaded as part of the model payload.
	ExplanationConfig GoogleCloudMlV1__ExplanationConfigResponse `pulumi:"explanationConfig"`
	// Optional. The machine learning framework AI Platform uses to train this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, `XGBOOST`. If you do not specify a framework, AI Platform will analyze files in the deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the model to 1.4 or greater. Do **not** specify a framework if you're deploying a [custom prediction routine](/ai-platform/prediction/docs/custom-prediction-routines) or if you're using a [custom container](/ai-platform/prediction/docs/use-custom-container).
	Framework string `pulumi:"framework"`
	// If true, this version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.methods.versions.setDefault.
	IsDefault bool `pulumi:"isDefault"`
	// Optional. One or more labels that you can add, to organize your model versions. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels map[string]string `pulumi:"labels"`
	// The [AI Platform (Unified) `Model`](https://cloud.google.com/ai-platform-unified/docs/reference/rest/v1beta1/projects.locations.models) ID for the last [model migration](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).
	LastMigrationModelId string `pulumi:"lastMigrationModelId"`
	// The last time this version was successfully [migrated to AI Platform (Unified)](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).
	LastMigrationTime string `pulumi:"lastMigrationTime"`
	// The time the version was last used for prediction.
	LastUseTime string `pulumi:"lastUseTime"`
	// Optional. The type of machine on which to serve the model. Currently only applies to online prediction service. To learn about valid values for this field, read [Choosing a machine type for online prediction](/ai-platform/prediction/docs/machine-types-online-prediction). If this field is not specified and you are using a [regional endpoint](/ai-platform/prediction/docs/regional-endpoints), then the machine type defaults to `n1-standard-2`. If this field is not specified and you are using the global endpoint (`ml.googleapis.com`), then the machine type defaults to `mls1-c1-m2`.
	MachineType string `pulumi:"machineType"`
	// Manually select the number of nodes to use for serving the model. You should generally use `auto_scaling` with an appropriate `min_nodes` instead, but this option is available if you want more predictable billing. Beware that latency and error rates will increase if the traffic exceeds that capability of the system to serve it based on the selected number of nodes.
	ManualScaling GoogleCloudMlV1__ManualScalingResponse `pulumi:"manualScaling"`
	// The name specified for the version when it was created. The version name must be unique within the model it is created in.
	Name string `pulumi:"name"`
	// Optional. Cloud Storage paths (`gs://…`) of packages for [custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines) or [scikit-learn pipelines with custom code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code). For a custom prediction routine, one of these packages must contain your Predictor class (see [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally, include any dependencies used by your Predictor or scikit-learn pipeline uses that are not already included in your selected [runtime version](/ml-engine/docs/tensorflow/runtime-version-list). If you specify this field, you must also set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
	PackageUris []string `pulumi:"packageUris"`
	// Optional. The fully qualified name (module_name.class_name) of a class that implements the Predictor interface described in this reference field. The module containing this class should be included in a package provided to the [`packageUris` field](#Version.FIELDS.package_uris). Specify this field if and only if you are deploying a [custom prediction routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines). If you specify this field, you must set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater and you must set `machineType` to a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction). The following code sample provides the Predictor interface: class Predictor(object): """Interface for constructing custom predictors.""" def predict(self, instances, **kwargs): """Performs custom prediction. Instances are the decoded values from the request. They have already been deserialized from JSON. Args: instances: A list of prediction input instances. **kwargs: A dictionary of keyword args provided as additional fields on the predict request body. Returns: A list of outputs containing the prediction results. This list must be JSON serializable. """ raise NotImplementedError() @classmethod def from_path(cls, model_dir): """Creates an instance of Predictor using the given path. Loading of the predictor should be done in this method. Args: model_dir: The local directory that contains the exported model file along with any additional files uploaded when creating the version resource. Returns: An instance implementing this Predictor class. """ raise NotImplementedError() Learn more about [the Predictor interface and custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
	PredictionClass string `pulumi:"predictionClass"`
	// The version of Python used in prediction. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).
	PythonVersion string `pulumi:"pythonVersion"`
	// Optional. *Only* specify this field in a projects.models.versions.patch request. Specifying it in a projects.models.versions.create request has no effect. Configures the request-response pair logging on predictions from this Version.
	RequestLoggingConfig GoogleCloudMlV1__RequestLoggingConfigResponse `pulumi:"requestLoggingConfig"`
	// Optional. Specifies paths on a custom container's HTTP server where AI Platform Prediction sends certain requests. If you specify this field, then you must also specify the `container` field. If you specify the `container` field and do not specify this field, it defaults to the following: “` json { "predict": "/v1/models/MODEL/versions/VERSION:predict", "health": "/v1/models/MODEL/versions/VERSION" }  “` See RouteMap for more details about these default values.
	Routes GoogleCloudMlV1__RouteMapResponse `pulumi:"routes"`
	// The AI Platform runtime version to use for this deployment. For more information, see the [runtime version list](/ml-engine/docs/runtime-version-list) and [how to manage runtime versions](/ml-engine/docs/versioning).
	RuntimeVersion string `pulumi:"runtimeVersion"`
	// Optional. Specifies the service account for resource access control. If you specify this field, then you must also specify either the `containerSpec` or the `predictionClass` field. Learn more about [using a custom service account](/ai-platform/prediction/docs/custom-service-account).
	ServiceAccount string `pulumi:"serviceAccount"`
	// The state of a version.
	State string `pulumi:"state"`
}

Represents a version of the model. Each version is a trained model deployed in the cloud, ready to handle prediction requests. A model can have multiple versions. You can get information about all of the versions of a given model by calling projects.models.versions.list.

type GoogleCloudMlV1__VersionResponseOutput 

type GoogleCloudMlV1__VersionResponseOutput struct{ *pulumi.OutputState }

Represents a version of the model. Each version is a trained model deployed in the cloud, ready to handle prediction requests. A model can have multiple versions. You can get information about all of the versions of a given model by calling projects.models.versions.list.

func (GoogleCloudMlV1__VersionResponseOutput) AcceleratorConfig 

func (o GoogleCloudMlV1__VersionResponseOutput) AcceleratorConfig() GoogleCloudMlV1__AcceleratorConfigResponseOutput

Optional. Accelerator config for using GPUs for online prediction (beta). Only specify this field if you have specified a Compute Engine (N1) machine type in the `machineType` field. Learn more about [using GPUs for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).

func (GoogleCloudMlV1__VersionResponseOutput) AutoScaling 

func (o GoogleCloudMlV1__VersionResponseOutput) AutoScaling() GoogleCloudMlV1__AutoScalingResponseOutput

Automatically scale the number of nodes used to serve the model in response to increases and decreases in traffic. Care should be taken to ramp up traffic according to the model's ability to scale or you will start seeing increases in latency and 429 response codes.

func (GoogleCloudMlV1__VersionResponseOutput) Container 

func (o GoogleCloudMlV1__VersionResponseOutput) Container() GoogleCloudMlV1__ContainerSpecResponseOutput

Optional. Specifies a custom container to use for serving predictions. If you specify this field, then `machineType` is required. If you specify this field, then `deploymentUri` is optional. If you specify this field, then you must not specify `runtimeVersion`, `packageUris`, `framework`, `pythonVersion`, or `predictionClass`.

func (GoogleCloudMlV1__VersionResponseOutput) CreateTime 

func (o GoogleCloudMlV1__VersionResponseOutput) CreateTime() pulumi.StringOutput

The time the version was created.

func (GoogleCloudMlV1__VersionResponseOutput) DeploymentUri 

func (o GoogleCloudMlV1__VersionResponseOutput) DeploymentUri() pulumi.StringOutput

The Cloud Storage URI of a directory containing trained model artifacts to be used to create the model version. See the [guide to deploying models](/ai-platform/prediction/docs/deploying-models) for more information. The total number of files under this directory must not exceed 1000. During projects.models.versions.create, AI Platform Prediction copies all files from the specified directory to a location managed by the service. From then on, AI Platform Prediction uses these copies of the model artifacts to serve predictions, not the original files in Cloud Storage, so this location is useful only as a historical record. If you specify container, then this field is optional. Otherwise, it is required. Learn [how to use this field with a custom container](/ai-platform/prediction/docs/custom-container-requirements#artifacts).

func (GoogleCloudMlV1__VersionResponseOutput) Description 

func (o GoogleCloudMlV1__VersionResponseOutput) Description() pulumi.StringOutput

Optional. The description specified for the version when it was created.

func (GoogleCloudMlV1__VersionResponseOutput) ElementType 

func (GoogleCloudMlV1__VersionResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__VersionResponseOutput) ErrorMessage 

func (o GoogleCloudMlV1__VersionResponseOutput) ErrorMessage() pulumi.StringOutput

The details of a failure or a cancellation.

func (GoogleCloudMlV1__VersionResponseOutput) Etag 

func (o GoogleCloudMlV1__VersionResponseOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetVersion`, and systems are expected to put that etag in the request to `UpdateVersion` to ensure that their change will be applied to the model as intended.

func (GoogleCloudMlV1__VersionResponseOutput) ExplanationConfig 

func (o GoogleCloudMlV1__VersionResponseOutput) ExplanationConfig() GoogleCloudMlV1__ExplanationConfigResponseOutput

Optional. Configures explainability features on the model's version. Some explanation features require additional metadata to be loaded as part of the model payload.

func (GoogleCloudMlV1__VersionResponseOutput) Framework 

func (o GoogleCloudMlV1__VersionResponseOutput) Framework() pulumi.StringOutput

Optional. The machine learning framework AI Platform uses to train this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, `XGBOOST`. If you do not specify a framework, AI Platform will analyze files in the deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the model to 1.4 or greater. Do **not** specify a framework if you're deploying a [custom prediction routine](/ai-platform/prediction/docs/custom-prediction-routines) or if you're using a [custom container](/ai-platform/prediction/docs/use-custom-container).

func (GoogleCloudMlV1__VersionResponseOutput) IsDefault 

func (o GoogleCloudMlV1__VersionResponseOutput) IsDefault() pulumi.BoolOutput

If true, this version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.methods.versions.setDefault.

func (GoogleCloudMlV1__VersionResponseOutput) Labels 

func (o GoogleCloudMlV1__VersionResponseOutput) Labels() pulumi.StringMapOutput

Optional. One or more labels that you can add, to organize your model versions. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

func (GoogleCloudMlV1__VersionResponseOutput) LastMigrationModelId 

func (o GoogleCloudMlV1__VersionResponseOutput) LastMigrationModelId() pulumi.StringOutput

The [AI Platform (Unified) `Model`](https://cloud.google.com/ai-platform-unified/docs/reference/rest/v1beta1/projects.locations.models) ID for the last [model migration](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).

func (GoogleCloudMlV1__VersionResponseOutput) LastMigrationTime 

func (o GoogleCloudMlV1__VersionResponseOutput) LastMigrationTime() pulumi.StringOutput

The last time this version was successfully [migrated to AI Platform (Unified)](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).

func (GoogleCloudMlV1__VersionResponseOutput) LastUseTime 

func (o GoogleCloudMlV1__VersionResponseOutput) LastUseTime() pulumi.StringOutput

The time the version was last used for prediction.

func (GoogleCloudMlV1__VersionResponseOutput) MachineType 

func (o GoogleCloudMlV1__VersionResponseOutput) MachineType() pulumi.StringOutput

Optional. The type of machine on which to serve the model. Currently only applies to online prediction service. To learn about valid values for this field, read [Choosing a machine type for online prediction](/ai-platform/prediction/docs/machine-types-online-prediction). If this field is not specified and you are using a [regional endpoint](/ai-platform/prediction/docs/regional-endpoints), then the machine type defaults to `n1-standard-2`. If this field is not specified and you are using the global endpoint (`ml.googleapis.com`), then the machine type defaults to `mls1-c1-m2`.

func (GoogleCloudMlV1__VersionResponseOutput) ManualScaling 

func (o GoogleCloudMlV1__VersionResponseOutput) ManualScaling() GoogleCloudMlV1__ManualScalingResponseOutput

Manually select the number of nodes to use for serving the model. You should generally use `auto_scaling` with an appropriate `min_nodes` instead, but this option is available if you want more predictable billing. Beware that latency and error rates will increase if the traffic exceeds that capability of the system to serve it based on the selected number of nodes.

func (GoogleCloudMlV1__VersionResponseOutput) Name 

func (o GoogleCloudMlV1__VersionResponseOutput) Name() pulumi.StringOutput

The name specified for the version when it was created. The version name must be unique within the model it is created in.

func (GoogleCloudMlV1__VersionResponseOutput) PackageUris 

func (o GoogleCloudMlV1__VersionResponseOutput) PackageUris() pulumi.StringArrayOutput

Optional. Cloud Storage paths (`gs://…`) of packages for [custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines) or [scikit-learn pipelines with custom code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code). For a custom prediction routine, one of these packages must contain your Predictor class (see [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally, include any dependencies used by your Predictor or scikit-learn pipeline uses that are not already included in your selected [runtime version](/ml-engine/docs/tensorflow/runtime-version-list). If you specify this field, you must also set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.

func (GoogleCloudMlV1__VersionResponseOutput) PredictionClass 

func (o GoogleCloudMlV1__VersionResponseOutput) PredictionClass() pulumi.StringOutput

Optional. The fully qualified name (module_name.class_name) of a class that implements the Predictor interface described in this reference field. The module containing this class should be included in a package provided to the [`packageUris` field](#Version.FIELDS.package_uris). Specify this field if and only if you are deploying a [custom prediction routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines). If you specify this field, you must set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater and you must set `machineType` to a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction). The following code sample provides the Predictor interface: class Predictor(object): """Interface for constructing custom predictors.""" def predict(self, instances, **kwargs): """Performs custom prediction. Instances are the decoded values from the request. They have already been deserialized from JSON. Args: instances: A list of prediction input instances. **kwargs: A dictionary of keyword args provided as additional fields on the predict request body. Returns: A list of outputs containing the prediction results. This list must be JSON serializable. """ raise NotImplementedError() @classmethod def from_path(cls, model_dir): """Creates an instance of Predictor using the given path. Loading of the predictor should be done in this method. Args: model_dir: The local directory that contains the exported model file along with any additional files uploaded when creating the version resource. Returns: An instance implementing this Predictor class. """ raise NotImplementedError() Learn more about [the Predictor interface and custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines).

func (GoogleCloudMlV1__VersionResponseOutput) PythonVersion 

func (o GoogleCloudMlV1__VersionResponseOutput) PythonVersion() pulumi.StringOutput

The version of Python used in prediction. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).

func (GoogleCloudMlV1__VersionResponseOutput) RequestLoggingConfig 

func (o GoogleCloudMlV1__VersionResponseOutput) RequestLoggingConfig() GoogleCloudMlV1__RequestLoggingConfigResponseOutput

Optional. *Only* specify this field in a projects.models.versions.patch request. Specifying it in a projects.models.versions.create request has no effect. Configures the request-response pair logging on predictions from this Version.

func (GoogleCloudMlV1__VersionResponseOutput) Routes 

func (o GoogleCloudMlV1__VersionResponseOutput) Routes() GoogleCloudMlV1__RouteMapResponseOutput

Optional. Specifies paths on a custom container's HTTP server where AI Platform Prediction sends certain requests. If you specify this field, then you must also specify the `container` field. If you specify the `container` field and do not specify this field, it defaults to the following: ``` json { "predict": "/v1/models/MODEL/versions/VERSION:predict", "health": "/v1/models/MODEL/versions/VERSION" } ``` See RouteMap for more details about these default values.

func (GoogleCloudMlV1__VersionResponseOutput) RuntimeVersion 

func (o GoogleCloudMlV1__VersionResponseOutput) RuntimeVersion() pulumi.StringOutput

The AI Platform runtime version to use for this deployment. For more information, see the [runtime version list](/ml-engine/docs/runtime-version-list) and [how to manage runtime versions](/ml-engine/docs/versioning).

func (GoogleCloudMlV1__VersionResponseOutput) ServiceAccount 

func (o GoogleCloudMlV1__VersionResponseOutput) ServiceAccount() pulumi.StringOutput

Optional. Specifies the service account for resource access control. If you specify this field, then you must also specify either the `containerSpec` or the `predictionClass` field. Learn more about [using a custom service account](/ai-platform/prediction/docs/custom-service-account).

func (GoogleCloudMlV1__VersionResponseOutput) State 

func (o GoogleCloudMlV1__VersionResponseOutput) State() pulumi.StringOutput

The state of a version.

func (GoogleCloudMlV1__VersionResponseOutput) ToGoogleCloudMlV1__VersionResponseOutput 

func (o GoogleCloudMlV1__VersionResponseOutput) ToGoogleCloudMlV1__VersionResponseOutput() GoogleCloudMlV1__VersionResponseOutput

func (GoogleCloudMlV1__VersionResponseOutput) ToGoogleCloudMlV1__VersionResponseOutputWithContext 

func (o GoogleCloudMlV1__VersionResponseOutput) ToGoogleCloudMlV1__VersionResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__VersionResponseOutput

type GoogleCloudMlV1__XraiAttribution 

type GoogleCloudMlV1__XraiAttribution struct {
	// Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.
	NumIntegralSteps *int `pulumi:"numIntegralSteps"`
}

Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.

type GoogleCloudMlV1__XraiAttributionArgs 

type GoogleCloudMlV1__XraiAttributionArgs struct {
	// Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.
	NumIntegralSteps pulumi.IntPtrInput `pulumi:"numIntegralSteps"`
}

Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.

func (GoogleCloudMlV1__XraiAttributionArgs) ElementType 

func (GoogleCloudMlV1__XraiAttributionArgs) ElementType() reflect.Type

func (GoogleCloudMlV1__XraiAttributionArgs) ToGoogleCloudMlV1__XraiAttributionOutput 

func (i GoogleCloudMlV1__XraiAttributionArgs) ToGoogleCloudMlV1__XraiAttributionOutput() GoogleCloudMlV1__XraiAttributionOutput

func (GoogleCloudMlV1__XraiAttributionArgs) ToGoogleCloudMlV1__XraiAttributionOutputWithContext 

func (i GoogleCloudMlV1__XraiAttributionArgs) ToGoogleCloudMlV1__XraiAttributionOutputWithContext(ctx context.Context) GoogleCloudMlV1__XraiAttributionOutput

func (GoogleCloudMlV1__XraiAttributionArgs) ToGoogleCloudMlV1__XraiAttributionPtrOutput 

func (i GoogleCloudMlV1__XraiAttributionArgs) ToGoogleCloudMlV1__XraiAttributionPtrOutput() GoogleCloudMlV1__XraiAttributionPtrOutput

func (GoogleCloudMlV1__XraiAttributionArgs) ToGoogleCloudMlV1__XraiAttributionPtrOutputWithContext 

func (i GoogleCloudMlV1__XraiAttributionArgs) ToGoogleCloudMlV1__XraiAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__XraiAttributionPtrOutput

type GoogleCloudMlV1__XraiAttributionInput 

type GoogleCloudMlV1__XraiAttributionInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__XraiAttributionOutput() GoogleCloudMlV1__XraiAttributionOutput
	ToGoogleCloudMlV1__XraiAttributionOutputWithContext(context.Context) GoogleCloudMlV1__XraiAttributionOutput
}

GoogleCloudMlV1__XraiAttributionInput is an input type that accepts GoogleCloudMlV1__XraiAttributionArgs and GoogleCloudMlV1__XraiAttributionOutput values. You can construct a concrete instance of `GoogleCloudMlV1__XraiAttributionInput` via: 

GoogleCloudMlV1__XraiAttributionArgs{...}

type GoogleCloudMlV1__XraiAttributionOutput 

type GoogleCloudMlV1__XraiAttributionOutput struct{ *pulumi.OutputState }

Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.

func (GoogleCloudMlV1__XraiAttributionOutput) ElementType 

func (GoogleCloudMlV1__XraiAttributionOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__XraiAttributionOutput) NumIntegralSteps 

func (o GoogleCloudMlV1__XraiAttributionOutput) NumIntegralSteps() pulumi.IntPtrOutput

Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.

func (GoogleCloudMlV1__XraiAttributionOutput) ToGoogleCloudMlV1__XraiAttributionOutput 

func (o GoogleCloudMlV1__XraiAttributionOutput) ToGoogleCloudMlV1__XraiAttributionOutput() GoogleCloudMlV1__XraiAttributionOutput

func (GoogleCloudMlV1__XraiAttributionOutput) ToGoogleCloudMlV1__XraiAttributionOutputWithContext 

func (o GoogleCloudMlV1__XraiAttributionOutput) ToGoogleCloudMlV1__XraiAttributionOutputWithContext(ctx context.Context) GoogleCloudMlV1__XraiAttributionOutput

func (GoogleCloudMlV1__XraiAttributionOutput) ToGoogleCloudMlV1__XraiAttributionPtrOutput 

func (o GoogleCloudMlV1__XraiAttributionOutput) ToGoogleCloudMlV1__XraiAttributionPtrOutput() GoogleCloudMlV1__XraiAttributionPtrOutput

func (GoogleCloudMlV1__XraiAttributionOutput) ToGoogleCloudMlV1__XraiAttributionPtrOutputWithContext 

func (o GoogleCloudMlV1__XraiAttributionOutput) ToGoogleCloudMlV1__XraiAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__XraiAttributionPtrOutput

type GoogleCloudMlV1__XraiAttributionPtrInput 

type GoogleCloudMlV1__XraiAttributionPtrInput interface {
	pulumi.Input

	ToGoogleCloudMlV1__XraiAttributionPtrOutput() GoogleCloudMlV1__XraiAttributionPtrOutput
	ToGoogleCloudMlV1__XraiAttributionPtrOutputWithContext(context.Context) GoogleCloudMlV1__XraiAttributionPtrOutput
}

GoogleCloudMlV1__XraiAttributionPtrInput is an input type that accepts GoogleCloudMlV1__XraiAttributionArgs, GoogleCloudMlV1__XraiAttributionPtr and GoogleCloudMlV1__XraiAttributionPtrOutput values. You can construct a concrete instance of `GoogleCloudMlV1__XraiAttributionPtrInput` via: 

        GoogleCloudMlV1__XraiAttributionArgs{...}

or:

        nil

func GoogleCloudMlV1__XraiAttributionPtr 

func GoogleCloudMlV1__XraiAttributionPtr(v *GoogleCloudMlV1__XraiAttributionArgs) GoogleCloudMlV1__XraiAttributionPtrInput

type GoogleCloudMlV1__XraiAttributionPtrOutput 

type GoogleCloudMlV1__XraiAttributionPtrOutput struct{ *pulumi.OutputState }

func (GoogleCloudMlV1__XraiAttributionPtrOutput) Elem 

func (o GoogleCloudMlV1__XraiAttributionPtrOutput) Elem() GoogleCloudMlV1__XraiAttributionOutput

func (GoogleCloudMlV1__XraiAttributionPtrOutput) ElementType 

func (GoogleCloudMlV1__XraiAttributionPtrOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__XraiAttributionPtrOutput) NumIntegralSteps 

func (o GoogleCloudMlV1__XraiAttributionPtrOutput) NumIntegralSteps() pulumi.IntPtrOutput

Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.

func (GoogleCloudMlV1__XraiAttributionPtrOutput) ToGoogleCloudMlV1__XraiAttributionPtrOutput 

func (o GoogleCloudMlV1__XraiAttributionPtrOutput) ToGoogleCloudMlV1__XraiAttributionPtrOutput() GoogleCloudMlV1__XraiAttributionPtrOutput

func (GoogleCloudMlV1__XraiAttributionPtrOutput) ToGoogleCloudMlV1__XraiAttributionPtrOutputWithContext 

func (o GoogleCloudMlV1__XraiAttributionPtrOutput) ToGoogleCloudMlV1__XraiAttributionPtrOutputWithContext(ctx context.Context) GoogleCloudMlV1__XraiAttributionPtrOutput

type GoogleCloudMlV1__XraiAttributionResponse 

type GoogleCloudMlV1__XraiAttributionResponse struct {
	// Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.
	NumIntegralSteps int `pulumi:"numIntegralSteps"`
}

Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.

type GoogleCloudMlV1__XraiAttributionResponseOutput 

type GoogleCloudMlV1__XraiAttributionResponseOutput struct{ *pulumi.OutputState }

Attributes credit by computing the XRAI taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Currently only implemented for models with natural image inputs.

func (GoogleCloudMlV1__XraiAttributionResponseOutput) ElementType 

func (GoogleCloudMlV1__XraiAttributionResponseOutput) ElementType() reflect.Type

func (GoogleCloudMlV1__XraiAttributionResponseOutput) NumIntegralSteps 

func (o GoogleCloudMlV1__XraiAttributionResponseOutput) NumIntegralSteps() pulumi.IntOutput

Number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range.

func (GoogleCloudMlV1__XraiAttributionResponseOutput) ToGoogleCloudMlV1__XraiAttributionResponseOutput 

func (o GoogleCloudMlV1__XraiAttributionResponseOutput) ToGoogleCloudMlV1__XraiAttributionResponseOutput() GoogleCloudMlV1__XraiAttributionResponseOutput

func (GoogleCloudMlV1__XraiAttributionResponseOutput) ToGoogleCloudMlV1__XraiAttributionResponseOutputWithContext 

func (o GoogleCloudMlV1__XraiAttributionResponseOutput) ToGoogleCloudMlV1__XraiAttributionResponseOutputWithContext(ctx context.Context) GoogleCloudMlV1__XraiAttributionResponseOutput

type GoogleIamV1__AuditConfig 

type GoogleIamV1__AuditConfig struct {
	// The configuration for logging of each type of permission.
	AuditLogConfigs []GoogleIamV1__AuditLogConfig `pulumi:"auditLogConfigs"`
	// Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.
	Service *string `pulumi:"service"`
}

Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.

type GoogleIamV1__AuditConfigArgs 

type GoogleIamV1__AuditConfigArgs struct {
	// The configuration for logging of each type of permission.
	AuditLogConfigs GoogleIamV1__AuditLogConfigArrayInput `pulumi:"auditLogConfigs"`
	// Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.
	Service pulumi.StringPtrInput `pulumi:"service"`
}

Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.

func (GoogleIamV1__AuditConfigArgs) ElementType 

func (GoogleIamV1__AuditConfigArgs) ElementType() reflect.Type

func (GoogleIamV1__AuditConfigArgs) ToGoogleIamV1__AuditConfigOutput 

func (i GoogleIamV1__AuditConfigArgs) ToGoogleIamV1__AuditConfigOutput() GoogleIamV1__AuditConfigOutput

func (GoogleIamV1__AuditConfigArgs) ToGoogleIamV1__AuditConfigOutputWithContext 

func (i GoogleIamV1__AuditConfigArgs) ToGoogleIamV1__AuditConfigOutputWithContext(ctx context.Context) GoogleIamV1__AuditConfigOutput

type GoogleIamV1__AuditConfigArray 

type GoogleIamV1__AuditConfigArray []GoogleIamV1__AuditConfigInput

func (GoogleIamV1__AuditConfigArray) ElementType 

func (GoogleIamV1__AuditConfigArray) ElementType() reflect.Type

func (GoogleIamV1__AuditConfigArray) ToGoogleIamV1__AuditConfigArrayOutput 

func (i GoogleIamV1__AuditConfigArray) ToGoogleIamV1__AuditConfigArrayOutput() GoogleIamV1__AuditConfigArrayOutput

func (GoogleIamV1__AuditConfigArray) ToGoogleIamV1__AuditConfigArrayOutputWithContext 

func (i GoogleIamV1__AuditConfigArray) ToGoogleIamV1__AuditConfigArrayOutputWithContext(ctx context.Context) GoogleIamV1__AuditConfigArrayOutput

type GoogleIamV1__AuditConfigArrayInput 

type GoogleIamV1__AuditConfigArrayInput interface {
	pulumi.Input

	ToGoogleIamV1__AuditConfigArrayOutput() GoogleIamV1__AuditConfigArrayOutput
	ToGoogleIamV1__AuditConfigArrayOutputWithContext(context.Context) GoogleIamV1__AuditConfigArrayOutput
}

GoogleIamV1__AuditConfigArrayInput is an input type that accepts GoogleIamV1__AuditConfigArray and GoogleIamV1__AuditConfigArrayOutput values. You can construct a concrete instance of `GoogleIamV1__AuditConfigArrayInput` via: 

GoogleIamV1__AuditConfigArray{ GoogleIamV1__AuditConfigArgs{...} }

type GoogleIamV1__AuditConfigArrayOutput 

type GoogleIamV1__AuditConfigArrayOutput struct{ *pulumi.OutputState }

func (GoogleIamV1__AuditConfigArrayOutput) ElementType 

func (GoogleIamV1__AuditConfigArrayOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditConfigArrayOutput) Index 

func (o GoogleIamV1__AuditConfigArrayOutput) Index(i pulumi.IntInput) GoogleIamV1__AuditConfigOutput

func (GoogleIamV1__AuditConfigArrayOutput) ToGoogleIamV1__AuditConfigArrayOutput 

func (o GoogleIamV1__AuditConfigArrayOutput) ToGoogleIamV1__AuditConfigArrayOutput() GoogleIamV1__AuditConfigArrayOutput

func (GoogleIamV1__AuditConfigArrayOutput) ToGoogleIamV1__AuditConfigArrayOutputWithContext 

func (o GoogleIamV1__AuditConfigArrayOutput) ToGoogleIamV1__AuditConfigArrayOutputWithContext(ctx context.Context) GoogleIamV1__AuditConfigArrayOutput

type GoogleIamV1__AuditConfigInput 

type GoogleIamV1__AuditConfigInput interface {
	pulumi.Input

	ToGoogleIamV1__AuditConfigOutput() GoogleIamV1__AuditConfigOutput
	ToGoogleIamV1__AuditConfigOutputWithContext(context.Context) GoogleIamV1__AuditConfigOutput
}

GoogleIamV1__AuditConfigInput is an input type that accepts GoogleIamV1__AuditConfigArgs and GoogleIamV1__AuditConfigOutput values. You can construct a concrete instance of `GoogleIamV1__AuditConfigInput` via: 

GoogleIamV1__AuditConfigArgs{...}

type GoogleIamV1__AuditConfigOutput 

type GoogleIamV1__AuditConfigOutput struct{ *pulumi.OutputState }

Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.

func (GoogleIamV1__AuditConfigOutput) AuditLogConfigs 

func (o GoogleIamV1__AuditConfigOutput) AuditLogConfigs() GoogleIamV1__AuditLogConfigArrayOutput

The configuration for logging of each type of permission.

func (GoogleIamV1__AuditConfigOutput) ElementType 

func (GoogleIamV1__AuditConfigOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditConfigOutput) Service 

func (o GoogleIamV1__AuditConfigOutput) Service() pulumi.StringPtrOutput

Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.

func (GoogleIamV1__AuditConfigOutput) ToGoogleIamV1__AuditConfigOutput 

func (o GoogleIamV1__AuditConfigOutput) ToGoogleIamV1__AuditConfigOutput() GoogleIamV1__AuditConfigOutput

func (GoogleIamV1__AuditConfigOutput) ToGoogleIamV1__AuditConfigOutputWithContext 

func (o GoogleIamV1__AuditConfigOutput) ToGoogleIamV1__AuditConfigOutputWithContext(ctx context.Context) GoogleIamV1__AuditConfigOutput

type GoogleIamV1__AuditConfigResponse 

type GoogleIamV1__AuditConfigResponse struct {
	// The configuration for logging of each type of permission.
	AuditLogConfigs []GoogleIamV1__AuditLogConfigResponse `pulumi:"auditLogConfigs"`
	// Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.
	Service string `pulumi:"service"`
}

Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.

type GoogleIamV1__AuditConfigResponseArrayOutput 

type GoogleIamV1__AuditConfigResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleIamV1__AuditConfigResponseArrayOutput) ElementType 

func (GoogleIamV1__AuditConfigResponseArrayOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditConfigResponseArrayOutput) Index 

func (o GoogleIamV1__AuditConfigResponseArrayOutput) Index(i pulumi.IntInput) GoogleIamV1__AuditConfigResponseOutput

func (GoogleIamV1__AuditConfigResponseArrayOutput) ToGoogleIamV1__AuditConfigResponseArrayOutput 

func (o GoogleIamV1__AuditConfigResponseArrayOutput) ToGoogleIamV1__AuditConfigResponseArrayOutput() GoogleIamV1__AuditConfigResponseArrayOutput

func (GoogleIamV1__AuditConfigResponseArrayOutput) ToGoogleIamV1__AuditConfigResponseArrayOutputWithContext 

func (o GoogleIamV1__AuditConfigResponseArrayOutput) ToGoogleIamV1__AuditConfigResponseArrayOutputWithContext(ctx context.Context) GoogleIamV1__AuditConfigResponseArrayOutput

type GoogleIamV1__AuditConfigResponseOutput 

type GoogleIamV1__AuditConfigResponseOutput struct{ *pulumi.OutputState }

Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.

func (GoogleIamV1__AuditConfigResponseOutput) AuditLogConfigs 

func (o GoogleIamV1__AuditConfigResponseOutput) AuditLogConfigs() GoogleIamV1__AuditLogConfigResponseArrayOutput

The configuration for logging of each type of permission.

func (GoogleIamV1__AuditConfigResponseOutput) ElementType 

func (GoogleIamV1__AuditConfigResponseOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditConfigResponseOutput) Service 

func (o GoogleIamV1__AuditConfigResponseOutput) Service() pulumi.StringOutput

Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.

func (GoogleIamV1__AuditConfigResponseOutput) ToGoogleIamV1__AuditConfigResponseOutput 

func (o GoogleIamV1__AuditConfigResponseOutput) ToGoogleIamV1__AuditConfigResponseOutput() GoogleIamV1__AuditConfigResponseOutput

func (GoogleIamV1__AuditConfigResponseOutput) ToGoogleIamV1__AuditConfigResponseOutputWithContext 

func (o GoogleIamV1__AuditConfigResponseOutput) ToGoogleIamV1__AuditConfigResponseOutputWithContext(ctx context.Context) GoogleIamV1__AuditConfigResponseOutput

type GoogleIamV1__AuditLogConfig 

type GoogleIamV1__AuditLogConfig struct {
	// Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.
	ExemptedMembers []string `pulumi:"exemptedMembers"`
	// The log type that this config enables.
	LogType *GoogleIamV1__AuditLogConfigLogType `pulumi:"logType"`
}

Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.

type GoogleIamV1__AuditLogConfigArgs 

type GoogleIamV1__AuditLogConfigArgs struct {
	// Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.
	ExemptedMembers pulumi.StringArrayInput `pulumi:"exemptedMembers"`
	// The log type that this config enables.
	LogType GoogleIamV1__AuditLogConfigLogTypePtrInput `pulumi:"logType"`
}

Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.

func (GoogleIamV1__AuditLogConfigArgs) ElementType 

func (GoogleIamV1__AuditLogConfigArgs) ElementType() reflect.Type

func (GoogleIamV1__AuditLogConfigArgs) ToGoogleIamV1__AuditLogConfigOutput 

func (i GoogleIamV1__AuditLogConfigArgs) ToGoogleIamV1__AuditLogConfigOutput() GoogleIamV1__AuditLogConfigOutput

func (GoogleIamV1__AuditLogConfigArgs) ToGoogleIamV1__AuditLogConfigOutputWithContext 

func (i GoogleIamV1__AuditLogConfigArgs) ToGoogleIamV1__AuditLogConfigOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigOutput

type GoogleIamV1__AuditLogConfigArray 

type GoogleIamV1__AuditLogConfigArray []GoogleIamV1__AuditLogConfigInput

func (GoogleIamV1__AuditLogConfigArray) ElementType 

func (GoogleIamV1__AuditLogConfigArray) ElementType() reflect.Type

func (GoogleIamV1__AuditLogConfigArray) ToGoogleIamV1__AuditLogConfigArrayOutput 

func (i GoogleIamV1__AuditLogConfigArray) ToGoogleIamV1__AuditLogConfigArrayOutput() GoogleIamV1__AuditLogConfigArrayOutput

func (GoogleIamV1__AuditLogConfigArray) ToGoogleIamV1__AuditLogConfigArrayOutputWithContext 

func (i GoogleIamV1__AuditLogConfigArray) ToGoogleIamV1__AuditLogConfigArrayOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigArrayOutput

type GoogleIamV1__AuditLogConfigArrayInput 

type GoogleIamV1__AuditLogConfigArrayInput interface {
	pulumi.Input

	ToGoogleIamV1__AuditLogConfigArrayOutput() GoogleIamV1__AuditLogConfigArrayOutput
	ToGoogleIamV1__AuditLogConfigArrayOutputWithContext(context.Context) GoogleIamV1__AuditLogConfigArrayOutput
}

GoogleIamV1__AuditLogConfigArrayInput is an input type that accepts GoogleIamV1__AuditLogConfigArray and GoogleIamV1__AuditLogConfigArrayOutput values. You can construct a concrete instance of `GoogleIamV1__AuditLogConfigArrayInput` via: 

GoogleIamV1__AuditLogConfigArray{ GoogleIamV1__AuditLogConfigArgs{...} }

type GoogleIamV1__AuditLogConfigArrayOutput 

type GoogleIamV1__AuditLogConfigArrayOutput struct{ *pulumi.OutputState }

func (GoogleIamV1__AuditLogConfigArrayOutput) ElementType 

func (GoogleIamV1__AuditLogConfigArrayOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditLogConfigArrayOutput) Index 

func (o GoogleIamV1__AuditLogConfigArrayOutput) Index(i pulumi.IntInput) GoogleIamV1__AuditLogConfigOutput

func (GoogleIamV1__AuditLogConfigArrayOutput) ToGoogleIamV1__AuditLogConfigArrayOutput 

func (o GoogleIamV1__AuditLogConfigArrayOutput) ToGoogleIamV1__AuditLogConfigArrayOutput() GoogleIamV1__AuditLogConfigArrayOutput

func (GoogleIamV1__AuditLogConfigArrayOutput) ToGoogleIamV1__AuditLogConfigArrayOutputWithContext 

func (o GoogleIamV1__AuditLogConfigArrayOutput) ToGoogleIamV1__AuditLogConfigArrayOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigArrayOutput

type GoogleIamV1__AuditLogConfigInput 

type GoogleIamV1__AuditLogConfigInput interface {
	pulumi.Input

	ToGoogleIamV1__AuditLogConfigOutput() GoogleIamV1__AuditLogConfigOutput
	ToGoogleIamV1__AuditLogConfigOutputWithContext(context.Context) GoogleIamV1__AuditLogConfigOutput
}

GoogleIamV1__AuditLogConfigInput is an input type that accepts GoogleIamV1__AuditLogConfigArgs and GoogleIamV1__AuditLogConfigOutput values. You can construct a concrete instance of `GoogleIamV1__AuditLogConfigInput` via: 

GoogleIamV1__AuditLogConfigArgs{...}

type GoogleIamV1__AuditLogConfigLogType added in v0.4.0 

type GoogleIamV1__AuditLogConfigLogType string

The log type that this config enables.

func (GoogleIamV1__AuditLogConfigLogType) ElementType added in v0.4.0 

func (GoogleIamV1__AuditLogConfigLogType) ElementType() reflect.Type

func (GoogleIamV1__AuditLogConfigLogType) ToGoogleIamV1__AuditLogConfigLogTypeOutput added in v0.6.0 

func (e GoogleIamV1__AuditLogConfigLogType) ToGoogleIamV1__AuditLogConfigLogTypeOutput() GoogleIamV1__AuditLogConfigLogTypeOutput

func (GoogleIamV1__AuditLogConfigLogType) ToGoogleIamV1__AuditLogConfigLogTypeOutputWithContext added in v0.6.0 

func (e GoogleIamV1__AuditLogConfigLogType) ToGoogleIamV1__AuditLogConfigLogTypeOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigLogTypeOutput

func (GoogleIamV1__AuditLogConfigLogType) ToGoogleIamV1__AuditLogConfigLogTypePtrOutput added in v0.6.0 

func (e GoogleIamV1__AuditLogConfigLogType) ToGoogleIamV1__AuditLogConfigLogTypePtrOutput() GoogleIamV1__AuditLogConfigLogTypePtrOutput

func (GoogleIamV1__AuditLogConfigLogType) ToGoogleIamV1__AuditLogConfigLogTypePtrOutputWithContext added in v0.6.0 

func (e GoogleIamV1__AuditLogConfigLogType) ToGoogleIamV1__AuditLogConfigLogTypePtrOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigLogTypePtrOutput

func (GoogleIamV1__AuditLogConfigLogType) ToStringOutput added in v0.4.0 

func (e GoogleIamV1__AuditLogConfigLogType) ToStringOutput() pulumi.StringOutput

func (GoogleIamV1__AuditLogConfigLogType) ToStringOutputWithContext added in v0.4.0 

func (e GoogleIamV1__AuditLogConfigLogType) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleIamV1__AuditLogConfigLogType) ToStringPtrOutput added in v0.4.0 

func (e GoogleIamV1__AuditLogConfigLogType) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleIamV1__AuditLogConfigLogType) ToStringPtrOutputWithContext added in v0.4.0 

func (e GoogleIamV1__AuditLogConfigLogType) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleIamV1__AuditLogConfigLogTypeInput added in v0.6.0 

type GoogleIamV1__AuditLogConfigLogTypeInput interface {
	pulumi.Input

	ToGoogleIamV1__AuditLogConfigLogTypeOutput() GoogleIamV1__AuditLogConfigLogTypeOutput
	ToGoogleIamV1__AuditLogConfigLogTypeOutputWithContext(context.Context) GoogleIamV1__AuditLogConfigLogTypeOutput
}

GoogleIamV1__AuditLogConfigLogTypeInput is an input type that accepts GoogleIamV1__AuditLogConfigLogTypeArgs and GoogleIamV1__AuditLogConfigLogTypeOutput values. You can construct a concrete instance of `GoogleIamV1__AuditLogConfigLogTypeInput` via: 

GoogleIamV1__AuditLogConfigLogTypeArgs{...}

type GoogleIamV1__AuditLogConfigLogTypeOutput added in v0.6.0 

type GoogleIamV1__AuditLogConfigLogTypeOutput struct{ *pulumi.OutputState }

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ElementType added in v0.6.0 

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ToGoogleIamV1__AuditLogConfigLogTypeOutput added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypeOutput) ToGoogleIamV1__AuditLogConfigLogTypeOutput() GoogleIamV1__AuditLogConfigLogTypeOutput

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ToGoogleIamV1__AuditLogConfigLogTypeOutputWithContext added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypeOutput) ToGoogleIamV1__AuditLogConfigLogTypeOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigLogTypeOutput

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ToGoogleIamV1__AuditLogConfigLogTypePtrOutput added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypeOutput) ToGoogleIamV1__AuditLogConfigLogTypePtrOutput() GoogleIamV1__AuditLogConfigLogTypePtrOutput

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ToGoogleIamV1__AuditLogConfigLogTypePtrOutputWithContext added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypeOutput) ToGoogleIamV1__AuditLogConfigLogTypePtrOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigLogTypePtrOutput

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ToStringOutput added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypeOutput) ToStringOutput() pulumi.StringOutput

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ToStringOutputWithContext added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypeOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypeOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleIamV1__AuditLogConfigLogTypeOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypeOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleIamV1__AuditLogConfigLogTypePtrInput added in v0.6.0 

type GoogleIamV1__AuditLogConfigLogTypePtrInput interface {
	pulumi.Input

	ToGoogleIamV1__AuditLogConfigLogTypePtrOutput() GoogleIamV1__AuditLogConfigLogTypePtrOutput
	ToGoogleIamV1__AuditLogConfigLogTypePtrOutputWithContext(context.Context) GoogleIamV1__AuditLogConfigLogTypePtrOutput
}

func GoogleIamV1__AuditLogConfigLogTypePtr added in v0.6.0 

func GoogleIamV1__AuditLogConfigLogTypePtr(v string) GoogleIamV1__AuditLogConfigLogTypePtrInput

type GoogleIamV1__AuditLogConfigLogTypePtrOutput added in v0.6.0 

type GoogleIamV1__AuditLogConfigLogTypePtrOutput struct{ *pulumi.OutputState }

func (GoogleIamV1__AuditLogConfigLogTypePtrOutput) Elem added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypePtrOutput) Elem() GoogleIamV1__AuditLogConfigLogTypeOutput

func (GoogleIamV1__AuditLogConfigLogTypePtrOutput) ElementType added in v0.6.0 

func (GoogleIamV1__AuditLogConfigLogTypePtrOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditLogConfigLogTypePtrOutput) ToGoogleIamV1__AuditLogConfigLogTypePtrOutput added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypePtrOutput) ToGoogleIamV1__AuditLogConfigLogTypePtrOutput() GoogleIamV1__AuditLogConfigLogTypePtrOutput

func (GoogleIamV1__AuditLogConfigLogTypePtrOutput) ToGoogleIamV1__AuditLogConfigLogTypePtrOutputWithContext added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypePtrOutput) ToGoogleIamV1__AuditLogConfigLogTypePtrOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigLogTypePtrOutput

func (GoogleIamV1__AuditLogConfigLogTypePtrOutput) ToStringPtrOutput added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypePtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (GoogleIamV1__AuditLogConfigLogTypePtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o GoogleIamV1__AuditLogConfigLogTypePtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

type GoogleIamV1__AuditLogConfigOutput 

type GoogleIamV1__AuditLogConfigOutput struct{ *pulumi.OutputState }

Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.

func (GoogleIamV1__AuditLogConfigOutput) ElementType 

func (GoogleIamV1__AuditLogConfigOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditLogConfigOutput) ExemptedMembers 

func (o GoogleIamV1__AuditLogConfigOutput) ExemptedMembers() pulumi.StringArrayOutput

Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.

func (GoogleIamV1__AuditLogConfigOutput) LogType 

func (o GoogleIamV1__AuditLogConfigOutput) LogType() GoogleIamV1__AuditLogConfigLogTypePtrOutput

The log type that this config enables.

func (GoogleIamV1__AuditLogConfigOutput) ToGoogleIamV1__AuditLogConfigOutput 

func (o GoogleIamV1__AuditLogConfigOutput) ToGoogleIamV1__AuditLogConfigOutput() GoogleIamV1__AuditLogConfigOutput

func (GoogleIamV1__AuditLogConfigOutput) ToGoogleIamV1__AuditLogConfigOutputWithContext 

func (o GoogleIamV1__AuditLogConfigOutput) ToGoogleIamV1__AuditLogConfigOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigOutput

type GoogleIamV1__AuditLogConfigResponse 

type GoogleIamV1__AuditLogConfigResponse struct {
	// Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.
	ExemptedMembers []string `pulumi:"exemptedMembers"`
	// The log type that this config enables.
	LogType string `pulumi:"logType"`
}

Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.

type GoogleIamV1__AuditLogConfigResponseArrayOutput 

type GoogleIamV1__AuditLogConfigResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleIamV1__AuditLogConfigResponseArrayOutput) ElementType 

func (GoogleIamV1__AuditLogConfigResponseArrayOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditLogConfigResponseArrayOutput) Index 

func (o GoogleIamV1__AuditLogConfigResponseArrayOutput) Index(i pulumi.IntInput) GoogleIamV1__AuditLogConfigResponseOutput

func (GoogleIamV1__AuditLogConfigResponseArrayOutput) ToGoogleIamV1__AuditLogConfigResponseArrayOutput 

func (o GoogleIamV1__AuditLogConfigResponseArrayOutput) ToGoogleIamV1__AuditLogConfigResponseArrayOutput() GoogleIamV1__AuditLogConfigResponseArrayOutput

func (GoogleIamV1__AuditLogConfigResponseArrayOutput) ToGoogleIamV1__AuditLogConfigResponseArrayOutputWithContext 

func (o GoogleIamV1__AuditLogConfigResponseArrayOutput) ToGoogleIamV1__AuditLogConfigResponseArrayOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigResponseArrayOutput

type GoogleIamV1__AuditLogConfigResponseOutput 

type GoogleIamV1__AuditLogConfigResponseOutput struct{ *pulumi.OutputState }

Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.

func (GoogleIamV1__AuditLogConfigResponseOutput) ElementType 

func (GoogleIamV1__AuditLogConfigResponseOutput) ElementType() reflect.Type

func (GoogleIamV1__AuditLogConfigResponseOutput) ExemptedMembers 

func (o GoogleIamV1__AuditLogConfigResponseOutput) ExemptedMembers() pulumi.StringArrayOutput

Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.

func (GoogleIamV1__AuditLogConfigResponseOutput) LogType 

func (o GoogleIamV1__AuditLogConfigResponseOutput) LogType() pulumi.StringOutput

The log type that this config enables.

func (GoogleIamV1__AuditLogConfigResponseOutput) ToGoogleIamV1__AuditLogConfigResponseOutput 

func (o GoogleIamV1__AuditLogConfigResponseOutput) ToGoogleIamV1__AuditLogConfigResponseOutput() GoogleIamV1__AuditLogConfigResponseOutput

func (GoogleIamV1__AuditLogConfigResponseOutput) ToGoogleIamV1__AuditLogConfigResponseOutputWithContext 

func (o GoogleIamV1__AuditLogConfigResponseOutput) ToGoogleIamV1__AuditLogConfigResponseOutputWithContext(ctx context.Context) GoogleIamV1__AuditLogConfigResponseOutput

type GoogleIamV1__Binding 

type GoogleIamV1__Binding struct {
	// The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Condition *GoogleType__Expr `pulumi:"condition"`
	// Specifies the principals requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`.
	Members []string `pulumi:"members"`
	// Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
	Role *string `pulumi:"role"`
}

Associates `members`, or principals, with a `role`.

type GoogleIamV1__BindingArgs 

type GoogleIamV1__BindingArgs struct {
	// The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Condition GoogleType__ExprPtrInput `pulumi:"condition"`
	// Specifies the principals requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`.
	Members pulumi.StringArrayInput `pulumi:"members"`
	// Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
	Role pulumi.StringPtrInput `pulumi:"role"`
}

Associates `members`, or principals, with a `role`.

func (GoogleIamV1__BindingArgs) ElementType 

func (GoogleIamV1__BindingArgs) ElementType() reflect.Type

func (GoogleIamV1__BindingArgs) ToGoogleIamV1__BindingOutput 

func (i GoogleIamV1__BindingArgs) ToGoogleIamV1__BindingOutput() GoogleIamV1__BindingOutput

func (GoogleIamV1__BindingArgs) ToGoogleIamV1__BindingOutputWithContext 

func (i GoogleIamV1__BindingArgs) ToGoogleIamV1__BindingOutputWithContext(ctx context.Context) GoogleIamV1__BindingOutput

type GoogleIamV1__BindingArray 

type GoogleIamV1__BindingArray []GoogleIamV1__BindingInput

func (GoogleIamV1__BindingArray) ElementType 

func (GoogleIamV1__BindingArray) ElementType() reflect.Type

func (GoogleIamV1__BindingArray) ToGoogleIamV1__BindingArrayOutput 

func (i GoogleIamV1__BindingArray) ToGoogleIamV1__BindingArrayOutput() GoogleIamV1__BindingArrayOutput

func (GoogleIamV1__BindingArray) ToGoogleIamV1__BindingArrayOutputWithContext 

func (i GoogleIamV1__BindingArray) ToGoogleIamV1__BindingArrayOutputWithContext(ctx context.Context) GoogleIamV1__BindingArrayOutput

type GoogleIamV1__BindingArrayInput 

type GoogleIamV1__BindingArrayInput interface {
	pulumi.Input

	ToGoogleIamV1__BindingArrayOutput() GoogleIamV1__BindingArrayOutput
	ToGoogleIamV1__BindingArrayOutputWithContext(context.Context) GoogleIamV1__BindingArrayOutput
}

GoogleIamV1__BindingArrayInput is an input type that accepts GoogleIamV1__BindingArray and GoogleIamV1__BindingArrayOutput values. You can construct a concrete instance of `GoogleIamV1__BindingArrayInput` via: 

GoogleIamV1__BindingArray{ GoogleIamV1__BindingArgs{...} }

type GoogleIamV1__BindingArrayOutput 

type GoogleIamV1__BindingArrayOutput struct{ *pulumi.OutputState }

func (GoogleIamV1__BindingArrayOutput) ElementType 

func (GoogleIamV1__BindingArrayOutput) ElementType() reflect.Type

func (GoogleIamV1__BindingArrayOutput) Index 

func (o GoogleIamV1__BindingArrayOutput) Index(i pulumi.IntInput) GoogleIamV1__BindingOutput

func (GoogleIamV1__BindingArrayOutput) ToGoogleIamV1__BindingArrayOutput 

func (o GoogleIamV1__BindingArrayOutput) ToGoogleIamV1__BindingArrayOutput() GoogleIamV1__BindingArrayOutput

func (GoogleIamV1__BindingArrayOutput) ToGoogleIamV1__BindingArrayOutputWithContext 

func (o GoogleIamV1__BindingArrayOutput) ToGoogleIamV1__BindingArrayOutputWithContext(ctx context.Context) GoogleIamV1__BindingArrayOutput

type GoogleIamV1__BindingInput 

type GoogleIamV1__BindingInput interface {
	pulumi.Input

	ToGoogleIamV1__BindingOutput() GoogleIamV1__BindingOutput
	ToGoogleIamV1__BindingOutputWithContext(context.Context) GoogleIamV1__BindingOutput
}

GoogleIamV1__BindingInput is an input type that accepts GoogleIamV1__BindingArgs and GoogleIamV1__BindingOutput values. You can construct a concrete instance of `GoogleIamV1__BindingInput` via: 

GoogleIamV1__BindingArgs{...}

type GoogleIamV1__BindingOutput 

type GoogleIamV1__BindingOutput struct{ *pulumi.OutputState }

Associates `members`, or principals, with a `role`.

func (GoogleIamV1__BindingOutput) Condition 

func (o GoogleIamV1__BindingOutput) Condition() GoogleType__ExprPtrOutput

The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

func (GoogleIamV1__BindingOutput) ElementType 

func (GoogleIamV1__BindingOutput) ElementType() reflect.Type

func (GoogleIamV1__BindingOutput) Members 

func (o GoogleIamV1__BindingOutput) Members() pulumi.StringArrayOutput

Specifies the principals requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`.

func (GoogleIamV1__BindingOutput) Role 

func (o GoogleIamV1__BindingOutput) Role() pulumi.StringPtrOutput

Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.

func (GoogleIamV1__BindingOutput) ToGoogleIamV1__BindingOutput 

func (o GoogleIamV1__BindingOutput) ToGoogleIamV1__BindingOutput() GoogleIamV1__BindingOutput

func (GoogleIamV1__BindingOutput) ToGoogleIamV1__BindingOutputWithContext 

func (o GoogleIamV1__BindingOutput) ToGoogleIamV1__BindingOutputWithContext(ctx context.Context) GoogleIamV1__BindingOutput

type GoogleIamV1__BindingResponse 

type GoogleIamV1__BindingResponse struct {
	// The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Condition GoogleType__ExprResponse `pulumi:"condition"`
	// Specifies the principals requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`.
	Members []string `pulumi:"members"`
	// Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
	Role string `pulumi:"role"`
}

Associates `members`, or principals, with a `role`.

type GoogleIamV1__BindingResponseArrayOutput 

type GoogleIamV1__BindingResponseArrayOutput struct{ *pulumi.OutputState }

func (GoogleIamV1__BindingResponseArrayOutput) ElementType 

func (GoogleIamV1__BindingResponseArrayOutput) ElementType() reflect.Type

func (GoogleIamV1__BindingResponseArrayOutput) Index 

func (o GoogleIamV1__BindingResponseArrayOutput) Index(i pulumi.IntInput) GoogleIamV1__BindingResponseOutput

func (GoogleIamV1__BindingResponseArrayOutput) ToGoogleIamV1__BindingResponseArrayOutput 

func (o GoogleIamV1__BindingResponseArrayOutput) ToGoogleIamV1__BindingResponseArrayOutput() GoogleIamV1__BindingResponseArrayOutput

func (GoogleIamV1__BindingResponseArrayOutput) ToGoogleIamV1__BindingResponseArrayOutputWithContext 

func (o GoogleIamV1__BindingResponseArrayOutput) ToGoogleIamV1__BindingResponseArrayOutputWithContext(ctx context.Context) GoogleIamV1__BindingResponseArrayOutput

type GoogleIamV1__BindingResponseOutput 

type GoogleIamV1__BindingResponseOutput struct{ *pulumi.OutputState }

Associates `members`, or principals, with a `role`.

func (GoogleIamV1__BindingResponseOutput) Condition 

func (o GoogleIamV1__BindingResponseOutput) Condition() GoogleType__ExprResponseOutput

The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

func (GoogleIamV1__BindingResponseOutput) ElementType 

func (GoogleIamV1__BindingResponseOutput) ElementType() reflect.Type

func (GoogleIamV1__BindingResponseOutput) Members 

func (o GoogleIamV1__BindingResponseOutput) Members() pulumi.StringArrayOutput

Specifies the principals requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`.

func (GoogleIamV1__BindingResponseOutput) Role 

func (o GoogleIamV1__BindingResponseOutput) Role() pulumi.StringOutput

Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.

func (GoogleIamV1__BindingResponseOutput) ToGoogleIamV1__BindingResponseOutput 

func (o GoogleIamV1__BindingResponseOutput) ToGoogleIamV1__BindingResponseOutput() GoogleIamV1__BindingResponseOutput

func (GoogleIamV1__BindingResponseOutput) ToGoogleIamV1__BindingResponseOutputWithContext 

func (o GoogleIamV1__BindingResponseOutput) ToGoogleIamV1__BindingResponseOutputWithContext(ctx context.Context) GoogleIamV1__BindingResponseOutput

type GoogleType__Expr 

type GoogleType__Expr struct {
	// Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
	Description *string `pulumi:"description"`
	// Textual representation of an expression in Common Expression Language syntax.
	Expression *string `pulumi:"expression"`
	// Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
	Location *string `pulumi:"location"`
	// Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
	Title *string `pulumi:"title"`
}

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

type GoogleType__ExprArgs 

type GoogleType__ExprArgs struct {
	// Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
	Description pulumi.StringPtrInput `pulumi:"description"`
	// Textual representation of an expression in Common Expression Language syntax.
	Expression pulumi.StringPtrInput `pulumi:"expression"`
	// Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
	Location pulumi.StringPtrInput `pulumi:"location"`
	// Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
	Title pulumi.StringPtrInput `pulumi:"title"`
}

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

func (GoogleType__ExprArgs) ElementType 

func (GoogleType__ExprArgs) ElementType() reflect.Type

func (GoogleType__ExprArgs) ToGoogleType__ExprOutput 

func (i GoogleType__ExprArgs) ToGoogleType__ExprOutput() GoogleType__ExprOutput

func (GoogleType__ExprArgs) ToGoogleType__ExprOutputWithContext 

func (i GoogleType__ExprArgs) ToGoogleType__ExprOutputWithContext(ctx context.Context) GoogleType__ExprOutput

func (GoogleType__ExprArgs) ToGoogleType__ExprPtrOutput 

func (i GoogleType__ExprArgs) ToGoogleType__ExprPtrOutput() GoogleType__ExprPtrOutput

func (GoogleType__ExprArgs) ToGoogleType__ExprPtrOutputWithContext 

func (i GoogleType__ExprArgs) ToGoogleType__ExprPtrOutputWithContext(ctx context.Context) GoogleType__ExprPtrOutput

type GoogleType__ExprInput 

type GoogleType__ExprInput interface {
	pulumi.Input

	ToGoogleType__ExprOutput() GoogleType__ExprOutput
	ToGoogleType__ExprOutputWithContext(context.Context) GoogleType__ExprOutput
}

GoogleType__ExprInput is an input type that accepts GoogleType__ExprArgs and GoogleType__ExprOutput values. You can construct a concrete instance of `GoogleType__ExprInput` via: 

GoogleType__ExprArgs{...}

type GoogleType__ExprOutput 

type GoogleType__ExprOutput struct{ *pulumi.OutputState }

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

func (GoogleType__ExprOutput) Description 

func (o GoogleType__ExprOutput) Description() pulumi.StringPtrOutput

Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.

func (GoogleType__ExprOutput) ElementType 

func (GoogleType__ExprOutput) ElementType() reflect.Type

func (GoogleType__ExprOutput) Expression 

func (o GoogleType__ExprOutput) Expression() pulumi.StringPtrOutput

Textual representation of an expression in Common Expression Language syntax.

func (GoogleType__ExprOutput) Location 

func (o GoogleType__ExprOutput) Location() pulumi.StringPtrOutput

Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.

func (GoogleType__ExprOutput) Title 

func (o GoogleType__ExprOutput) Title() pulumi.StringPtrOutput

Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.

func (GoogleType__ExprOutput) ToGoogleType__ExprOutput 

func (o GoogleType__ExprOutput) ToGoogleType__ExprOutput() GoogleType__ExprOutput

func (GoogleType__ExprOutput) ToGoogleType__ExprOutputWithContext 

func (o GoogleType__ExprOutput) ToGoogleType__ExprOutputWithContext(ctx context.Context) GoogleType__ExprOutput

func (GoogleType__ExprOutput) ToGoogleType__ExprPtrOutput 

func (o GoogleType__ExprOutput) ToGoogleType__ExprPtrOutput() GoogleType__ExprPtrOutput

func (GoogleType__ExprOutput) ToGoogleType__ExprPtrOutputWithContext 

func (o GoogleType__ExprOutput) ToGoogleType__ExprPtrOutputWithContext(ctx context.Context) GoogleType__ExprPtrOutput

type GoogleType__ExprPtrInput 

type GoogleType__ExprPtrInput interface {
	pulumi.Input

	ToGoogleType__ExprPtrOutput() GoogleType__ExprPtrOutput
	ToGoogleType__ExprPtrOutputWithContext(context.Context) GoogleType__ExprPtrOutput
}

GoogleType__ExprPtrInput is an input type that accepts GoogleType__ExprArgs, GoogleType__ExprPtr and GoogleType__ExprPtrOutput values. You can construct a concrete instance of `GoogleType__ExprPtrInput` via: 

        GoogleType__ExprArgs{...}

or:

        nil

func GoogleType__ExprPtr 

func GoogleType__ExprPtr(v *GoogleType__ExprArgs) GoogleType__ExprPtrInput

type GoogleType__ExprPtrOutput 

type GoogleType__ExprPtrOutput struct{ *pulumi.OutputState }

func (GoogleType__ExprPtrOutput) Description 

func (o GoogleType__ExprPtrOutput) Description() pulumi.StringPtrOutput

Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.

func (GoogleType__ExprPtrOutput) Elem 

func (o GoogleType__ExprPtrOutput) Elem() GoogleType__ExprOutput

func (GoogleType__ExprPtrOutput) ElementType 

func (GoogleType__ExprPtrOutput) ElementType() reflect.Type

func (GoogleType__ExprPtrOutput) Expression 

func (o GoogleType__ExprPtrOutput) Expression() pulumi.StringPtrOutput

Textual representation of an expression in Common Expression Language syntax.

func (GoogleType__ExprPtrOutput) Location 

func (o GoogleType__ExprPtrOutput) Location() pulumi.StringPtrOutput

Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.

func (GoogleType__ExprPtrOutput) Title 

func (o GoogleType__ExprPtrOutput) Title() pulumi.StringPtrOutput

Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.

func (GoogleType__ExprPtrOutput) ToGoogleType__ExprPtrOutput 

func (o GoogleType__ExprPtrOutput) ToGoogleType__ExprPtrOutput() GoogleType__ExprPtrOutput

func (GoogleType__ExprPtrOutput) ToGoogleType__ExprPtrOutputWithContext 

func (o GoogleType__ExprPtrOutput) ToGoogleType__ExprPtrOutputWithContext(ctx context.Context) GoogleType__ExprPtrOutput

type GoogleType__ExprResponse 

type GoogleType__ExprResponse struct {
	// Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
	Description string `pulumi:"description"`
	// Textual representation of an expression in Common Expression Language syntax.
	Expression string `pulumi:"expression"`
	// Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
	Location string `pulumi:"location"`
	// Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
	Title string `pulumi:"title"`
}

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

type GoogleType__ExprResponseOutput 

type GoogleType__ExprResponseOutput struct{ *pulumi.OutputState }

Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.

func (GoogleType__ExprResponseOutput) Description 

func (o GoogleType__ExprResponseOutput) Description() pulumi.StringOutput

Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.

func (GoogleType__ExprResponseOutput) ElementType 

func (GoogleType__ExprResponseOutput) ElementType() reflect.Type

func (GoogleType__ExprResponseOutput) Expression 

func (o GoogleType__ExprResponseOutput) Expression() pulumi.StringOutput

Textual representation of an expression in Common Expression Language syntax.

func (GoogleType__ExprResponseOutput) Location 

func (o GoogleType__ExprResponseOutput) Location() pulumi.StringOutput

Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.

func (GoogleType__ExprResponseOutput) Title 

func (o GoogleType__ExprResponseOutput) Title() pulumi.StringOutput

Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.

func (GoogleType__ExprResponseOutput) ToGoogleType__ExprResponseOutput 

func (o GoogleType__ExprResponseOutput) ToGoogleType__ExprResponseOutput() GoogleType__ExprResponseOutput

func (GoogleType__ExprResponseOutput) ToGoogleType__ExprResponseOutputWithContext 

func (o GoogleType__ExprResponseOutput) ToGoogleType__ExprResponseOutputWithContext(ctx context.Context) GoogleType__ExprResponseOutput

type Job 

type Job struct {
	pulumi.CustomResourceState

	// When the job was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// When the job processing was completed.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// The details of a failure or a cancellation.
	ErrorMessage pulumi.StringOutput `pulumi:"errorMessage"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a job from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform job updates in order to avoid race conditions: An `etag` is returned in the response to `GetJob`, and systems are expected to put that etag in the request to `UpdateJob` to ensure that their change will be applied to the same version of the job.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// The user-specified id of the job.
	JobId pulumi.StringOutput `pulumi:"jobId"`
	// It's only effect when the job is in QUEUED state. If it's positive, it indicates the job's position in the job scheduler. It's 0 when the job is already scheduled.
	JobPosition pulumi.StringOutput `pulumi:"jobPosition"`
	// Optional. One or more labels that you can add, to organize your jobs. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels pulumi.StringMapOutput `pulumi:"labels"`
	// Input parameters to create a prediction job.
	PredictionInput GoogleCloudMlV1__PredictionInputResponseOutput `pulumi:"predictionInput"`
	// The current prediction job result.
	PredictionOutput GoogleCloudMlV1__PredictionOutputResponseOutput `pulumi:"predictionOutput"`
	// When the job processing was started.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The detailed state of a job.
	State pulumi.StringOutput `pulumi:"state"`
	// Input parameters to create a training job.
	TrainingInput GoogleCloudMlV1__TrainingInputResponseOutput `pulumi:"trainingInput"`
	// The current training job result.
	TrainingOutput GoogleCloudMlV1__TrainingOutputResponseOutput `pulumi:"trainingOutput"`
}

Creates a training or a batch prediction job. Auto-naming is currently not supported for this resource. Note - this resource's API doesn't support deletion. When deleted, the resource will persist on Google Cloud even though it will be deleted from Pulumi state.

func GetJob 

func GetJob(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *JobState, opts ...pulumi.ResourceOption) (*Job, error)

GetJob gets an existing Job resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewJob 

func NewJob(ctx *pulumi.Context,
	name string, args *JobArgs, opts ...pulumi.ResourceOption) (*Job, error)

NewJob registers a new resource with the given unique name, arguments, and options.

func (*Job) ElementType 

func (*Job) ElementType() reflect.Type

func (*Job) ToJobOutput 

func (i *Job) ToJobOutput() JobOutput

func (*Job) ToJobOutputWithContext 

func (i *Job) ToJobOutputWithContext(ctx context.Context) JobOutput

type JobArgs 

type JobArgs struct {
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a job from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform job updates in order to avoid race conditions: An `etag` is returned in the response to `GetJob`, and systems are expected to put that etag in the request to `UpdateJob` to ensure that their change will be applied to the same version of the job.
	Etag pulumi.StringPtrInput
	// The user-specified id of the job.
	JobId pulumi.StringInput
	// Optional. One or more labels that you can add, to organize your jobs. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels pulumi.StringMapInput
	// Input parameters to create a prediction job.
	PredictionInput GoogleCloudMlV1__PredictionInputPtrInput
	// The current prediction job result.
	PredictionOutput GoogleCloudMlV1__PredictionOutputPtrInput
	Project          pulumi.StringPtrInput
	// Input parameters to create a training job.
	TrainingInput GoogleCloudMlV1__TrainingInputPtrInput
	// The current training job result.
	TrainingOutput GoogleCloudMlV1__TrainingOutputPtrInput
}

The set of arguments for constructing a Job resource.

func (JobArgs) ElementType 

func (JobArgs) ElementType() reflect.Type

type JobIamPolicy 

type JobIamPolicy struct {
	pulumi.CustomResourceState

	// Specifies cloud audit logging configuration for this policy.
	AuditConfigs GoogleIamV1__AuditConfigResponseArrayOutput `pulumi:"auditConfigs"`
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings GoogleIamV1__BindingResponseArrayOutput `pulumi:"bindings"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntOutput `pulumi:"version"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors. Note - this resource's API doesn't support deletion. When deleted, the resource will persist on Google Cloud even though it will be deleted from Pulumi state.

func GetJobIamPolicy 

func GetJobIamPolicy(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *JobIamPolicyState, opts ...pulumi.ResourceOption) (*JobIamPolicy, error)

GetJobIamPolicy gets an existing JobIamPolicy resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewJobIamPolicy 

func NewJobIamPolicy(ctx *pulumi.Context,
	name string, args *JobIamPolicyArgs, opts ...pulumi.ResourceOption) (*JobIamPolicy, error)

NewJobIamPolicy registers a new resource with the given unique name, arguments, and options.

func (*JobIamPolicy) ElementType 

func (*JobIamPolicy) ElementType() reflect.Type

func (*JobIamPolicy) ToJobIamPolicyOutput 

func (i *JobIamPolicy) ToJobIamPolicyOutput() JobIamPolicyOutput

func (*JobIamPolicy) ToJobIamPolicyOutputWithContext 

func (i *JobIamPolicy) ToJobIamPolicyOutputWithContext(ctx context.Context) JobIamPolicyOutput

type JobIamPolicyArgs 

type JobIamPolicyArgs struct {
	// Specifies cloud audit logging configuration for this policy.
	AuditConfigs GoogleIamV1__AuditConfigArrayInput
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings GoogleIamV1__BindingArrayInput
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag    pulumi.StringPtrInput
	JobId   pulumi.StringInput
	Project pulumi.StringPtrInput
	// OPTIONAL: A FieldMask specifying which fields of the policy to modify. Only the fields in the mask will be modified. If no mask is provided, the following default mask is used: `paths: "bindings, etag"`
	UpdateMask pulumi.StringPtrInput
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntPtrInput
}

The set of arguments for constructing a JobIamPolicy resource.

func (JobIamPolicyArgs) ElementType 

func (JobIamPolicyArgs) ElementType() reflect.Type

type JobIamPolicyInput 

type JobIamPolicyInput interface {
	pulumi.Input

	ToJobIamPolicyOutput() JobIamPolicyOutput
	ToJobIamPolicyOutputWithContext(ctx context.Context) JobIamPolicyOutput
}

type JobIamPolicyOutput 

type JobIamPolicyOutput struct{ *pulumi.OutputState }

func (JobIamPolicyOutput) ElementType 

func (JobIamPolicyOutput) ElementType() reflect.Type

func (JobIamPolicyOutput) ToJobIamPolicyOutput 

func (o JobIamPolicyOutput) ToJobIamPolicyOutput() JobIamPolicyOutput

func (JobIamPolicyOutput) ToJobIamPolicyOutputWithContext 

func (o JobIamPolicyOutput) ToJobIamPolicyOutputWithContext(ctx context.Context) JobIamPolicyOutput

type JobIamPolicyState 

type JobIamPolicyState struct {
}

func (JobIamPolicyState) ElementType 

func (JobIamPolicyState) ElementType() reflect.Type

type JobInput 

type JobInput interface {
	pulumi.Input

	ToJobOutput() JobOutput
	ToJobOutputWithContext(ctx context.Context) JobOutput
}

type JobOutput 

type JobOutput struct{ *pulumi.OutputState }

func (JobOutput) ElementType 

func (JobOutput) ElementType() reflect.Type

func (JobOutput) ToJobOutput 

func (o JobOutput) ToJobOutput() JobOutput

func (JobOutput) ToJobOutputWithContext 

func (o JobOutput) ToJobOutputWithContext(ctx context.Context) JobOutput

type JobState 

type JobState struct {
}

func (JobState) ElementType 

func (JobState) ElementType() reflect.Type

type LookupJobArgs added in v0.4.0 

type LookupJobArgs struct {
	JobId   string  `pulumi:"jobId"`
	Project *string `pulumi:"project"`
}

type LookupJobIamPolicyArgs added in v0.4.0 

type LookupJobIamPolicyArgs struct {
	JobId                         string  `pulumi:"jobId"`
	OptionsRequestedPolicyVersion *string `pulumi:"optionsRequestedPolicyVersion"`
	Project                       *string `pulumi:"project"`
}

type LookupJobIamPolicyOutputArgs added in v0.8.0 

type LookupJobIamPolicyOutputArgs struct {
	JobId                         pulumi.StringInput    `pulumi:"jobId"`
	OptionsRequestedPolicyVersion pulumi.StringPtrInput `pulumi:"optionsRequestedPolicyVersion"`
	Project                       pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupJobIamPolicyOutputArgs) ElementType added in v0.8.0 

func (LookupJobIamPolicyOutputArgs) ElementType() reflect.Type

type LookupJobIamPolicyResult added in v0.4.0 

type LookupJobIamPolicyResult struct {
	// Specifies cloud audit logging configuration for this policy.
	AuditConfigs []GoogleIamV1__AuditConfigResponse `pulumi:"auditConfigs"`
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings []GoogleIamV1__BindingResponse `pulumi:"bindings"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag string `pulumi:"etag"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version int `pulumi:"version"`
}

func LookupJobIamPolicy added in v0.4.0 

func LookupJobIamPolicy(ctx *pulumi.Context, args *LookupJobIamPolicyArgs, opts ...pulumi.InvokeOption) (*LookupJobIamPolicyResult, error)

Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

type LookupJobIamPolicyResultOutput added in v0.8.0 

type LookupJobIamPolicyResultOutput struct{ *pulumi.OutputState }

func LookupJobIamPolicyOutput added in v0.8.0 

func LookupJobIamPolicyOutput(ctx *pulumi.Context, args LookupJobIamPolicyOutputArgs, opts ...pulumi.InvokeOption) LookupJobIamPolicyResultOutput

func (LookupJobIamPolicyResultOutput) AuditConfigs added in v0.8.0 

func (o LookupJobIamPolicyResultOutput) AuditConfigs() GoogleIamV1__AuditConfigResponseArrayOutput

Specifies cloud audit logging configuration for this policy.

func (LookupJobIamPolicyResultOutput) Bindings added in v0.8.0 

func (o LookupJobIamPolicyResultOutput) Bindings() GoogleIamV1__BindingResponseArrayOutput

Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.

func (LookupJobIamPolicyResultOutput) ElementType added in v0.8.0 

func (LookupJobIamPolicyResultOutput) ElementType() reflect.Type

func (LookupJobIamPolicyResultOutput) Etag added in v0.8.0 

func (o LookupJobIamPolicyResultOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.

func (LookupJobIamPolicyResultOutput) ToLookupJobIamPolicyResultOutput added in v0.8.0 

func (o LookupJobIamPolicyResultOutput) ToLookupJobIamPolicyResultOutput() LookupJobIamPolicyResultOutput

func (LookupJobIamPolicyResultOutput) ToLookupJobIamPolicyResultOutputWithContext added in v0.8.0 

func (o LookupJobIamPolicyResultOutput) ToLookupJobIamPolicyResultOutputWithContext(ctx context.Context) LookupJobIamPolicyResultOutput

func (LookupJobIamPolicyResultOutput) Version added in v0.8.0 

func (o LookupJobIamPolicyResultOutput) Version() pulumi.IntOutput

Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

type LookupJobOutputArgs added in v0.8.0 

type LookupJobOutputArgs struct {
	JobId   pulumi.StringInput    `pulumi:"jobId"`
	Project pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupJobOutputArgs) ElementType added in v0.8.0 

func (LookupJobOutputArgs) ElementType() reflect.Type

type LookupJobResult added in v0.4.0 

type LookupJobResult struct {
	// When the job was created.
	CreateTime string `pulumi:"createTime"`
	// When the job processing was completed.
	EndTime string `pulumi:"endTime"`
	// The details of a failure or a cancellation.
	ErrorMessage string `pulumi:"errorMessage"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a job from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform job updates in order to avoid race conditions: An `etag` is returned in the response to `GetJob`, and systems are expected to put that etag in the request to `UpdateJob` to ensure that their change will be applied to the same version of the job.
	Etag string `pulumi:"etag"`
	// The user-specified id of the job.
	JobId string `pulumi:"jobId"`
	// It's only effect when the job is in QUEUED state. If it's positive, it indicates the job's position in the job scheduler. It's 0 when the job is already scheduled.
	JobPosition string `pulumi:"jobPosition"`
	// Optional. One or more labels that you can add, to organize your jobs. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels map[string]string `pulumi:"labels"`
	// Input parameters to create a prediction job.
	PredictionInput GoogleCloudMlV1__PredictionInputResponse `pulumi:"predictionInput"`
	// The current prediction job result.
	PredictionOutput GoogleCloudMlV1__PredictionOutputResponse `pulumi:"predictionOutput"`
	// When the job processing was started.
	StartTime string `pulumi:"startTime"`
	// The detailed state of a job.
	State string `pulumi:"state"`
	// Input parameters to create a training job.
	TrainingInput GoogleCloudMlV1__TrainingInputResponse `pulumi:"trainingInput"`
	// The current training job result.
	TrainingOutput GoogleCloudMlV1__TrainingOutputResponse `pulumi:"trainingOutput"`
}

func LookupJob added in v0.4.0 

func LookupJob(ctx *pulumi.Context, args *LookupJobArgs, opts ...pulumi.InvokeOption) (*LookupJobResult, error)

Describes a job.

type LookupJobResultOutput added in v0.8.0 

type LookupJobResultOutput struct{ *pulumi.OutputState }

func LookupJobOutput added in v0.8.0 

func LookupJobOutput(ctx *pulumi.Context, args LookupJobOutputArgs, opts ...pulumi.InvokeOption) LookupJobResultOutput

func (LookupJobResultOutput) CreateTime added in v0.8.0 

func (o LookupJobResultOutput) CreateTime() pulumi.StringOutput

When the job was created.

func (LookupJobResultOutput) ElementType added in v0.8.0 

func (LookupJobResultOutput) ElementType() reflect.Type

func (LookupJobResultOutput) EndTime added in v0.8.0 

func (o LookupJobResultOutput) EndTime() pulumi.StringOutput

When the job processing was completed.

func (LookupJobResultOutput) ErrorMessage added in v0.8.0 

func (o LookupJobResultOutput) ErrorMessage() pulumi.StringOutput

The details of a failure or a cancellation.

func (LookupJobResultOutput) Etag added in v0.8.0 

func (o LookupJobResultOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a job from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform job updates in order to avoid race conditions: An `etag` is returned in the response to `GetJob`, and systems are expected to put that etag in the request to `UpdateJob` to ensure that their change will be applied to the same version of the job.

func (LookupJobResultOutput) JobId added in v0.8.0 

func (o LookupJobResultOutput) JobId() pulumi.StringOutput

The user-specified id of the job.

func (LookupJobResultOutput) JobPosition added in v0.9.0 

func (o LookupJobResultOutput) JobPosition() pulumi.StringOutput

It's only effect when the job is in QUEUED state. If it's positive, it indicates the job's position in the job scheduler. It's 0 when the job is already scheduled.

func (LookupJobResultOutput) Labels added in v0.8.0 

func (o LookupJobResultOutput) Labels() pulumi.StringMapOutput

Optional. One or more labels that you can add, to organize your jobs. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

func (LookupJobResultOutput) PredictionInput added in v0.8.0 

func (o LookupJobResultOutput) PredictionInput() GoogleCloudMlV1__PredictionInputResponseOutput

Input parameters to create a prediction job.

func (LookupJobResultOutput) PredictionOutput added in v0.8.0 

func (o LookupJobResultOutput) PredictionOutput() GoogleCloudMlV1__PredictionOutputResponseOutput

The current prediction job result.

func (LookupJobResultOutput) StartTime added in v0.8.0 

func (o LookupJobResultOutput) StartTime() pulumi.StringOutput

When the job processing was started.

func (LookupJobResultOutput) State added in v0.8.0 

func (o LookupJobResultOutput) State() pulumi.StringOutput

The detailed state of a job.

func (LookupJobResultOutput) ToLookupJobResultOutput added in v0.8.0 

func (o LookupJobResultOutput) ToLookupJobResultOutput() LookupJobResultOutput

func (LookupJobResultOutput) ToLookupJobResultOutputWithContext added in v0.8.0 

func (o LookupJobResultOutput) ToLookupJobResultOutputWithContext(ctx context.Context) LookupJobResultOutput

func (LookupJobResultOutput) TrainingInput added in v0.8.0 

func (o LookupJobResultOutput) TrainingInput() GoogleCloudMlV1__TrainingInputResponseOutput

Input parameters to create a training job.

func (LookupJobResultOutput) TrainingOutput added in v0.8.0 

func (o LookupJobResultOutput) TrainingOutput() GoogleCloudMlV1__TrainingOutputResponseOutput

The current training job result.

type LookupModelArgs added in v0.4.0 

type LookupModelArgs struct {
	ModelId string  `pulumi:"modelId"`
	Project *string `pulumi:"project"`
}

type LookupModelIamPolicyArgs added in v0.4.0 

type LookupModelIamPolicyArgs struct {
	ModelId                       string  `pulumi:"modelId"`
	OptionsRequestedPolicyVersion *string `pulumi:"optionsRequestedPolicyVersion"`
	Project                       *string `pulumi:"project"`
}

type LookupModelIamPolicyOutputArgs added in v0.8.0 

type LookupModelIamPolicyOutputArgs struct {
	ModelId                       pulumi.StringInput    `pulumi:"modelId"`
	OptionsRequestedPolicyVersion pulumi.StringPtrInput `pulumi:"optionsRequestedPolicyVersion"`
	Project                       pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupModelIamPolicyOutputArgs) ElementType added in v0.8.0 

func (LookupModelIamPolicyOutputArgs) ElementType() reflect.Type

type LookupModelIamPolicyResult added in v0.4.0 

type LookupModelIamPolicyResult struct {
	// Specifies cloud audit logging configuration for this policy.
	AuditConfigs []GoogleIamV1__AuditConfigResponse `pulumi:"auditConfigs"`
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings []GoogleIamV1__BindingResponse `pulumi:"bindings"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag string `pulumi:"etag"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version int `pulumi:"version"`
}

func LookupModelIamPolicy added in v0.4.0 

func LookupModelIamPolicy(ctx *pulumi.Context, args *LookupModelIamPolicyArgs, opts ...pulumi.InvokeOption) (*LookupModelIamPolicyResult, error)

Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

type LookupModelIamPolicyResultOutput added in v0.8.0 

type LookupModelIamPolicyResultOutput struct{ *pulumi.OutputState }

func LookupModelIamPolicyOutput added in v0.8.0 

func LookupModelIamPolicyOutput(ctx *pulumi.Context, args LookupModelIamPolicyOutputArgs, opts ...pulumi.InvokeOption) LookupModelIamPolicyResultOutput

func (LookupModelIamPolicyResultOutput) AuditConfigs added in v0.8.0 

func (o LookupModelIamPolicyResultOutput) AuditConfigs() GoogleIamV1__AuditConfigResponseArrayOutput

Specifies cloud audit logging configuration for this policy.

func (LookupModelIamPolicyResultOutput) Bindings added in v0.8.0 

func (o LookupModelIamPolicyResultOutput) Bindings() GoogleIamV1__BindingResponseArrayOutput

Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.

func (LookupModelIamPolicyResultOutput) ElementType added in v0.8.0 

func (LookupModelIamPolicyResultOutput) ElementType() reflect.Type

func (LookupModelIamPolicyResultOutput) Etag added in v0.8.0 

func (o LookupModelIamPolicyResultOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.

func (LookupModelIamPolicyResultOutput) ToLookupModelIamPolicyResultOutput added in v0.8.0 

func (o LookupModelIamPolicyResultOutput) ToLookupModelIamPolicyResultOutput() LookupModelIamPolicyResultOutput

func (LookupModelIamPolicyResultOutput) ToLookupModelIamPolicyResultOutputWithContext added in v0.8.0 

func (o LookupModelIamPolicyResultOutput) ToLookupModelIamPolicyResultOutputWithContext(ctx context.Context) LookupModelIamPolicyResultOutput

func (LookupModelIamPolicyResultOutput) Version added in v0.8.0 

func (o LookupModelIamPolicyResultOutput) Version() pulumi.IntOutput

Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).

type LookupModelOutputArgs added in v0.8.0 

type LookupModelOutputArgs struct {
	ModelId pulumi.StringInput    `pulumi:"modelId"`
	Project pulumi.StringPtrInput `pulumi:"project"`
}

func (LookupModelOutputArgs) ElementType added in v0.8.0 

func (LookupModelOutputArgs) ElementType() reflect.Type

type LookupModelResult added in v0.4.0 

type LookupModelResult struct {
	// The default version of the model. This version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.models.versions.setDefault.
	DefaultVersion GoogleCloudMlV1__VersionResponse `pulumi:"defaultVersion"`
	// Optional. The description specified for the model when it was created.
	Description string `pulumi:"description"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended.
	Etag string `pulumi:"etag"`
	// Optional. One or more labels that you can add, to organize your models. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels map[string]string `pulumi:"labels"`
	// The name specified for the model when it was created. The model name must be unique within the project it is created in.
	Name string `pulumi:"name"`
	// Optional. If true, online prediction nodes send `stderr` and `stdout` streams to Cloud Logging. These can be more verbose than the standard access logs (see `onlinePredictionLogging`) and can incur higher cost. However, they are helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high QPS. Estimate your costs before enabling this option. Default is false.
	OnlinePredictionConsoleLogging bool `pulumi:"onlinePredictionConsoleLogging"`
	// Optional. If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each request. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option. Default is false.
	OnlinePredictionLogging bool `pulumi:"onlinePredictionLogging"`
	// Optional. The list of regions where the model is going to be deployed. Only one region per model is supported. Defaults to 'us-central1' if nothing is set. See the available regions for AI Platform services. Note: * No matter where a model is deployed, it can always be accessed by users from anywhere, both for online and batch prediction. * The region for a batch prediction job is set by the region field when submitting the batch prediction job and does not take its value from this field.
	Regions []string `pulumi:"regions"`
}

func LookupModel added in v0.4.0 

func LookupModel(ctx *pulumi.Context, args *LookupModelArgs, opts ...pulumi.InvokeOption) (*LookupModelResult, error)

Gets information about a model, including its name, the description (if set), and the default version (if at least one version of the model has been deployed).

type LookupModelResultOutput added in v0.8.0 

type LookupModelResultOutput struct{ *pulumi.OutputState }

func LookupModelOutput added in v0.8.0 

func LookupModelOutput(ctx *pulumi.Context, args LookupModelOutputArgs, opts ...pulumi.InvokeOption) LookupModelResultOutput

func (LookupModelResultOutput) DefaultVersion added in v0.8.0 

func (o LookupModelResultOutput) DefaultVersion() GoogleCloudMlV1__VersionResponseOutput

The default version of the model. This version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.models.versions.setDefault.

func (LookupModelResultOutput) Description added in v0.8.0 

func (o LookupModelResultOutput) Description() pulumi.StringOutput

Optional. The description specified for the model when it was created.

func (LookupModelResultOutput) ElementType added in v0.8.0 

func (LookupModelResultOutput) ElementType() reflect.Type

func (LookupModelResultOutput) Etag added in v0.8.0 

func (o LookupModelResultOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended.

func (LookupModelResultOutput) Labels added in v0.8.0 

func (o LookupModelResultOutput) Labels() pulumi.StringMapOutput

Optional. One or more labels that you can add, to organize your models. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

func (LookupModelResultOutput) Name added in v0.8.0 

func (o LookupModelResultOutput) Name() pulumi.StringOutput

The name specified for the model when it was created. The model name must be unique within the project it is created in.

func (LookupModelResultOutput) OnlinePredictionConsoleLogging added in v0.8.0 

func (o LookupModelResultOutput) OnlinePredictionConsoleLogging() pulumi.BoolOutput

Optional. If true, online prediction nodes send `stderr` and `stdout` streams to Cloud Logging. These can be more verbose than the standard access logs (see `onlinePredictionLogging`) and can incur higher cost. However, they are helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high QPS. Estimate your costs before enabling this option. Default is false.

func (LookupModelResultOutput) OnlinePredictionLogging added in v0.8.0 

func (o LookupModelResultOutput) OnlinePredictionLogging() pulumi.BoolOutput

Optional. If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each request. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option. Default is false.

func (LookupModelResultOutput) Regions added in v0.8.0 

func (o LookupModelResultOutput) Regions() pulumi.StringArrayOutput

Optional. The list of regions where the model is going to be deployed. Only one region per model is supported. Defaults to 'us-central1' if nothing is set. See the available regions for AI Platform services. Note: * No matter where a model is deployed, it can always be accessed by users from anywhere, both for online and batch prediction. * The region for a batch prediction job is set by the region field when submitting the batch prediction job and does not take its value from this field.

func (LookupModelResultOutput) ToLookupModelResultOutput added in v0.8.0 

func (o LookupModelResultOutput) ToLookupModelResultOutput() LookupModelResultOutput

func (LookupModelResultOutput) ToLookupModelResultOutputWithContext added in v0.8.0 

func (o LookupModelResultOutput) ToLookupModelResultOutputWithContext(ctx context.Context) LookupModelResultOutput

type LookupStudyArgs added in v0.4.0 

type LookupStudyArgs struct {
	Location string  `pulumi:"location"`
	Project  *string `pulumi:"project"`
	StudyId  string  `pulumi:"studyId"`
}

type LookupStudyOutputArgs added in v0.8.0 

type LookupStudyOutputArgs struct {
	Location pulumi.StringInput    `pulumi:"location"`
	Project  pulumi.StringPtrInput `pulumi:"project"`
	StudyId  pulumi.StringInput    `pulumi:"studyId"`
}

func (LookupStudyOutputArgs) ElementType added in v0.8.0 

func (LookupStudyOutputArgs) ElementType() reflect.Type

type LookupStudyResult added in v0.4.0 

type LookupStudyResult struct {
	// Time at which the study was created.
	CreateTime string `pulumi:"createTime"`
	// A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
	InactiveReason string `pulumi:"inactiveReason"`
	// The name of a study.
	Name string `pulumi:"name"`
	// The detailed state of a study.
	State string `pulumi:"state"`
	// Configuration of the study.
	StudyConfig GoogleCloudMlV1__StudyConfigResponse `pulumi:"studyConfig"`
}

func LookupStudy added in v0.4.0 

func LookupStudy(ctx *pulumi.Context, args *LookupStudyArgs, opts ...pulumi.InvokeOption) (*LookupStudyResult, error)

Gets a study.

type LookupStudyResultOutput added in v0.8.0 

type LookupStudyResultOutput struct{ *pulumi.OutputState }

func LookupStudyOutput added in v0.8.0 

func LookupStudyOutput(ctx *pulumi.Context, args LookupStudyOutputArgs, opts ...pulumi.InvokeOption) LookupStudyResultOutput

func (LookupStudyResultOutput) CreateTime added in v0.8.0 

func (o LookupStudyResultOutput) CreateTime() pulumi.StringOutput

Time at which the study was created.

func (LookupStudyResultOutput) ElementType added in v0.8.0 

func (LookupStudyResultOutput) ElementType() reflect.Type

func (LookupStudyResultOutput) InactiveReason added in v0.8.0 

func (o LookupStudyResultOutput) InactiveReason() pulumi.StringOutput

A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.

func (LookupStudyResultOutput) Name added in v0.8.0 

func (o LookupStudyResultOutput) Name() pulumi.StringOutput

The name of a study.

func (LookupStudyResultOutput) State added in v0.8.0 

func (o LookupStudyResultOutput) State() pulumi.StringOutput

The detailed state of a study.

func (LookupStudyResultOutput) StudyConfig added in v0.8.0 

func (o LookupStudyResultOutput) StudyConfig() GoogleCloudMlV1__StudyConfigResponseOutput

Configuration of the study.

func (LookupStudyResultOutput) ToLookupStudyResultOutput added in v0.8.0 

func (o LookupStudyResultOutput) ToLookupStudyResultOutput() LookupStudyResultOutput

func (LookupStudyResultOutput) ToLookupStudyResultOutputWithContext added in v0.8.0 

func (o LookupStudyResultOutput) ToLookupStudyResultOutputWithContext(ctx context.Context) LookupStudyResultOutput

type LookupTrialArgs added in v0.4.0 

type LookupTrialArgs struct {
	Location string  `pulumi:"location"`
	Project  *string `pulumi:"project"`
	StudyId  string  `pulumi:"studyId"`
	TrialId  string  `pulumi:"trialId"`
}

type LookupTrialOutputArgs added in v0.8.0 

type LookupTrialOutputArgs struct {
	Location pulumi.StringInput    `pulumi:"location"`
	Project  pulumi.StringPtrInput `pulumi:"project"`
	StudyId  pulumi.StringInput    `pulumi:"studyId"`
	TrialId  pulumi.StringInput    `pulumi:"trialId"`
}

func (LookupTrialOutputArgs) ElementType added in v0.8.0 

func (LookupTrialOutputArgs) ElementType() reflect.Type

type LookupTrialResult added in v0.4.0 

type LookupTrialResult struct {
	// The identifier of the client that originally requested this trial.
	ClientId string `pulumi:"clientId"`
	// Time at which the trial's status changed to COMPLETED.
	EndTime string `pulumi:"endTime"`
	// The final measurement containing the objective value.
	FinalMeasurement GoogleCloudMlV1__MeasurementResponse `pulumi:"finalMeasurement"`
	// A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
	InfeasibleReason string `pulumi:"infeasibleReason"`
	// A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
	Measurements []GoogleCloudMlV1__MeasurementResponse `pulumi:"measurements"`
	// Name of the trial assigned by the service.
	Name string `pulumi:"name"`
	// The parameters of the trial.
	Parameters []GoogleCloudMlV1_Trial_ParameterResponse `pulumi:"parameters"`
	// Time at which the trial was started.
	StartTime string `pulumi:"startTime"`
	// The detailed state of a trial.
	State string `pulumi:"state"`
	// If true, the parameters in this trial are not attempted again.
	TrialInfeasible bool `pulumi:"trialInfeasible"`
}

func LookupTrial added in v0.4.0 

func LookupTrial(ctx *pulumi.Context, args *LookupTrialArgs, opts ...pulumi.InvokeOption) (*LookupTrialResult, error)

Gets a trial.

type LookupTrialResultOutput added in v0.8.0 

type LookupTrialResultOutput struct{ *pulumi.OutputState }

func LookupTrialOutput added in v0.8.0 

func LookupTrialOutput(ctx *pulumi.Context, args LookupTrialOutputArgs, opts ...pulumi.InvokeOption) LookupTrialResultOutput

func (LookupTrialResultOutput) ClientId added in v0.8.0 

func (o LookupTrialResultOutput) ClientId() pulumi.StringOutput

The identifier of the client that originally requested this trial.

func (LookupTrialResultOutput) ElementType added in v0.8.0 

func (LookupTrialResultOutput) ElementType() reflect.Type

func (LookupTrialResultOutput) EndTime added in v0.8.0 

func (o LookupTrialResultOutput) EndTime() pulumi.StringOutput

Time at which the trial's status changed to COMPLETED.

func (LookupTrialResultOutput) FinalMeasurement added in v0.8.0 

func (o LookupTrialResultOutput) FinalMeasurement() GoogleCloudMlV1__MeasurementResponseOutput

The final measurement containing the objective value.

func (LookupTrialResultOutput) InfeasibleReason added in v0.8.0 

func (o LookupTrialResultOutput) InfeasibleReason() pulumi.StringOutput

A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.

func (LookupTrialResultOutput) Measurements added in v0.8.0 

func (o LookupTrialResultOutput) Measurements() GoogleCloudMlV1__MeasurementResponseArrayOutput

A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.

func (LookupTrialResultOutput) Name added in v0.8.0 

func (o LookupTrialResultOutput) Name() pulumi.StringOutput

Name of the trial assigned by the service.

func (LookupTrialResultOutput) Parameters added in v0.8.0 

func (o LookupTrialResultOutput) Parameters() GoogleCloudMlV1_Trial_ParameterResponseArrayOutput

The parameters of the trial.

func (LookupTrialResultOutput) StartTime added in v0.8.0 

func (o LookupTrialResultOutput) StartTime() pulumi.StringOutput

Time at which the trial was started.

func (LookupTrialResultOutput) State added in v0.8.0 

func (o LookupTrialResultOutput) State() pulumi.StringOutput

The detailed state of a trial.

func (LookupTrialResultOutput) ToLookupTrialResultOutput added in v0.8.0 

func (o LookupTrialResultOutput) ToLookupTrialResultOutput() LookupTrialResultOutput

func (LookupTrialResultOutput) ToLookupTrialResultOutputWithContext added in v0.8.0 

func (o LookupTrialResultOutput) ToLookupTrialResultOutputWithContext(ctx context.Context) LookupTrialResultOutput

func (LookupTrialResultOutput) TrialInfeasible added in v0.8.0 

func (o LookupTrialResultOutput) TrialInfeasible() pulumi.BoolOutput

If true, the parameters in this trial are not attempted again.

type LookupVersionArgs added in v0.4.0 

type LookupVersionArgs struct {
	ModelId   string  `pulumi:"modelId"`
	Project   *string `pulumi:"project"`
	VersionId string  `pulumi:"versionId"`
}

type LookupVersionOutputArgs added in v0.8.0 

type LookupVersionOutputArgs struct {
	ModelId   pulumi.StringInput    `pulumi:"modelId"`
	Project   pulumi.StringPtrInput `pulumi:"project"`
	VersionId pulumi.StringInput    `pulumi:"versionId"`
}

func (LookupVersionOutputArgs) ElementType added in v0.8.0 

func (LookupVersionOutputArgs) ElementType() reflect.Type

type LookupVersionResult added in v0.4.0 

type LookupVersionResult struct {
	// Optional. Accelerator config for using GPUs for online prediction (beta). Only specify this field if you have specified a Compute Engine (N1) machine type in the `machineType` field. Learn more about [using GPUs for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).
	AcceleratorConfig GoogleCloudMlV1__AcceleratorConfigResponse `pulumi:"acceleratorConfig"`
	// Automatically scale the number of nodes used to serve the model in response to increases and decreases in traffic. Care should be taken to ramp up traffic according to the model's ability to scale or you will start seeing increases in latency and 429 response codes.
	AutoScaling GoogleCloudMlV1__AutoScalingResponse `pulumi:"autoScaling"`
	// Optional. Specifies a custom container to use for serving predictions. If you specify this field, then `machineType` is required. If you specify this field, then `deploymentUri` is optional. If you specify this field, then you must not specify `runtimeVersion`, `packageUris`, `framework`, `pythonVersion`, or `predictionClass`.
	Container GoogleCloudMlV1__ContainerSpecResponse `pulumi:"container"`
	// The time the version was created.
	CreateTime string `pulumi:"createTime"`
	// The Cloud Storage URI of a directory containing trained model artifacts to be used to create the model version. See the [guide to deploying models](/ai-platform/prediction/docs/deploying-models) for more information. The total number of files under this directory must not exceed 1000. During projects.models.versions.create, AI Platform Prediction copies all files from the specified directory to a location managed by the service. From then on, AI Platform Prediction uses these copies of the model artifacts to serve predictions, not the original files in Cloud Storage, so this location is useful only as a historical record. If you specify container, then this field is optional. Otherwise, it is required. Learn [how to use this field with a custom container](/ai-platform/prediction/docs/custom-container-requirements#artifacts).
	DeploymentUri string `pulumi:"deploymentUri"`
	// Optional. The description specified for the version when it was created.
	Description string `pulumi:"description"`
	// The details of a failure or a cancellation.
	ErrorMessage string `pulumi:"errorMessage"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetVersion`, and systems are expected to put that etag in the request to `UpdateVersion` to ensure that their change will be applied to the model as intended.
	Etag string `pulumi:"etag"`
	// Optional. Configures explainability features on the model's version. Some explanation features require additional metadata to be loaded as part of the model payload.
	ExplanationConfig GoogleCloudMlV1__ExplanationConfigResponse `pulumi:"explanationConfig"`
	// Optional. The machine learning framework AI Platform uses to train this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, `XGBOOST`. If you do not specify a framework, AI Platform will analyze files in the deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the model to 1.4 or greater. Do **not** specify a framework if you're deploying a [custom prediction routine](/ai-platform/prediction/docs/custom-prediction-routines) or if you're using a [custom container](/ai-platform/prediction/docs/use-custom-container).
	Framework string `pulumi:"framework"`
	// If true, this version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.methods.versions.setDefault.
	IsDefault bool `pulumi:"isDefault"`
	// Optional. One or more labels that you can add, to organize your model versions. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels map[string]string `pulumi:"labels"`
	// The [AI Platform (Unified) `Model`](https://cloud.google.com/ai-platform-unified/docs/reference/rest/v1beta1/projects.locations.models) ID for the last [model migration](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).
	LastMigrationModelId string `pulumi:"lastMigrationModelId"`
	// The last time this version was successfully [migrated to AI Platform (Unified)](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).
	LastMigrationTime string `pulumi:"lastMigrationTime"`
	// The time the version was last used for prediction.
	LastUseTime string `pulumi:"lastUseTime"`
	// Optional. The type of machine on which to serve the model. Currently only applies to online prediction service. To learn about valid values for this field, read [Choosing a machine type for online prediction](/ai-platform/prediction/docs/machine-types-online-prediction). If this field is not specified and you are using a [regional endpoint](/ai-platform/prediction/docs/regional-endpoints), then the machine type defaults to `n1-standard-2`. If this field is not specified and you are using the global endpoint (`ml.googleapis.com`), then the machine type defaults to `mls1-c1-m2`.
	MachineType string `pulumi:"machineType"`
	// Manually select the number of nodes to use for serving the model. You should generally use `auto_scaling` with an appropriate `min_nodes` instead, but this option is available if you want more predictable billing. Beware that latency and error rates will increase if the traffic exceeds that capability of the system to serve it based on the selected number of nodes.
	ManualScaling GoogleCloudMlV1__ManualScalingResponse `pulumi:"manualScaling"`
	// The name specified for the version when it was created. The version name must be unique within the model it is created in.
	Name string `pulumi:"name"`
	// Optional. Cloud Storage paths (`gs://…`) of packages for [custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines) or [scikit-learn pipelines with custom code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code). For a custom prediction routine, one of these packages must contain your Predictor class (see [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally, include any dependencies used by your Predictor or scikit-learn pipeline uses that are not already included in your selected [runtime version](/ml-engine/docs/tensorflow/runtime-version-list). If you specify this field, you must also set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
	PackageUris []string `pulumi:"packageUris"`
	// Optional. The fully qualified name (module_name.class_name) of a class that implements the Predictor interface described in this reference field. The module containing this class should be included in a package provided to the [`packageUris` field](#Version.FIELDS.package_uris). Specify this field if and only if you are deploying a [custom prediction routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines). If you specify this field, you must set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater and you must set `machineType` to a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction). The following code sample provides the Predictor interface: class Predictor(object): """Interface for constructing custom predictors.""" def predict(self, instances, **kwargs): """Performs custom prediction. Instances are the decoded values from the request. They have already been deserialized from JSON. Args: instances: A list of prediction input instances. **kwargs: A dictionary of keyword args provided as additional fields on the predict request body. Returns: A list of outputs containing the prediction results. This list must be JSON serializable. """ raise NotImplementedError() @classmethod def from_path(cls, model_dir): """Creates an instance of Predictor using the given path. Loading of the predictor should be done in this method. Args: model_dir: The local directory that contains the exported model file along with any additional files uploaded when creating the version resource. Returns: An instance implementing this Predictor class. """ raise NotImplementedError() Learn more about [the Predictor interface and custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
	PredictionClass string `pulumi:"predictionClass"`
	// The version of Python used in prediction. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).
	PythonVersion string `pulumi:"pythonVersion"`
	// Optional. *Only* specify this field in a projects.models.versions.patch request. Specifying it in a projects.models.versions.create request has no effect. Configures the request-response pair logging on predictions from this Version.
	RequestLoggingConfig GoogleCloudMlV1__RequestLoggingConfigResponse `pulumi:"requestLoggingConfig"`
	// Optional. Specifies paths on a custom container's HTTP server where AI Platform Prediction sends certain requests. If you specify this field, then you must also specify the `container` field. If you specify the `container` field and do not specify this field, it defaults to the following: “` json { "predict": "/v1/models/MODEL/versions/VERSION:predict", "health": "/v1/models/MODEL/versions/VERSION" }  “` See RouteMap for more details about these default values.
	Routes GoogleCloudMlV1__RouteMapResponse `pulumi:"routes"`
	// The AI Platform runtime version to use for this deployment. For more information, see the [runtime version list](/ml-engine/docs/runtime-version-list) and [how to manage runtime versions](/ml-engine/docs/versioning).
	RuntimeVersion string `pulumi:"runtimeVersion"`
	// Optional. Specifies the service account for resource access control. If you specify this field, then you must also specify either the `containerSpec` or the `predictionClass` field. Learn more about [using a custom service account](/ai-platform/prediction/docs/custom-service-account).
	ServiceAccount string `pulumi:"serviceAccount"`
	// The state of a version.
	State string `pulumi:"state"`
}

func LookupVersion added in v0.4.0 

func LookupVersion(ctx *pulumi.Context, args *LookupVersionArgs, opts ...pulumi.InvokeOption) (*LookupVersionResult, error)

Gets information about a model version. Models can have multiple versions. You can call projects.models.versions.list to get the same information that this method returns for all of the versions of a model.

type LookupVersionResultOutput added in v0.8.0 

type LookupVersionResultOutput struct{ *pulumi.OutputState }

func LookupVersionOutput added in v0.8.0 

func LookupVersionOutput(ctx *pulumi.Context, args LookupVersionOutputArgs, opts ...pulumi.InvokeOption) LookupVersionResultOutput

func (LookupVersionResultOutput) AcceleratorConfig added in v0.8.0 

func (o LookupVersionResultOutput) AcceleratorConfig() GoogleCloudMlV1__AcceleratorConfigResponseOutput

Optional. Accelerator config for using GPUs for online prediction (beta). Only specify this field if you have specified a Compute Engine (N1) machine type in the `machineType` field. Learn more about [using GPUs for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).

func (LookupVersionResultOutput) AutoScaling added in v0.8.0 

func (o LookupVersionResultOutput) AutoScaling() GoogleCloudMlV1__AutoScalingResponseOutput

Automatically scale the number of nodes used to serve the model in response to increases and decreases in traffic. Care should be taken to ramp up traffic according to the model's ability to scale or you will start seeing increases in latency and 429 response codes.

func (LookupVersionResultOutput) Container added in v0.8.0 

func (o LookupVersionResultOutput) Container() GoogleCloudMlV1__ContainerSpecResponseOutput

Optional. Specifies a custom container to use for serving predictions. If you specify this field, then `machineType` is required. If you specify this field, then `deploymentUri` is optional. If you specify this field, then you must not specify `runtimeVersion`, `packageUris`, `framework`, `pythonVersion`, or `predictionClass`.

func (LookupVersionResultOutput) CreateTime added in v0.8.0 

func (o LookupVersionResultOutput) CreateTime() pulumi.StringOutput

The time the version was created.

func (LookupVersionResultOutput) DeploymentUri added in v0.8.0 

func (o LookupVersionResultOutput) DeploymentUri() pulumi.StringOutput

The Cloud Storage URI of a directory containing trained model artifacts to be used to create the model version. See the [guide to deploying models](/ai-platform/prediction/docs/deploying-models) for more information. The total number of files under this directory must not exceed 1000. During projects.models.versions.create, AI Platform Prediction copies all files from the specified directory to a location managed by the service. From then on, AI Platform Prediction uses these copies of the model artifacts to serve predictions, not the original files in Cloud Storage, so this location is useful only as a historical record. If you specify container, then this field is optional. Otherwise, it is required. Learn [how to use this field with a custom container](/ai-platform/prediction/docs/custom-container-requirements#artifacts).

func (LookupVersionResultOutput) Description added in v0.8.0 

func (o LookupVersionResultOutput) Description() pulumi.StringOutput

Optional. The description specified for the version when it was created.

func (LookupVersionResultOutput) ElementType added in v0.8.0 

func (LookupVersionResultOutput) ElementType() reflect.Type

func (LookupVersionResultOutput) ErrorMessage added in v0.8.0 

func (o LookupVersionResultOutput) ErrorMessage() pulumi.StringOutput

The details of a failure or a cancellation.

func (LookupVersionResultOutput) Etag added in v0.8.0 

func (o LookupVersionResultOutput) Etag() pulumi.StringOutput

`etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetVersion`, and systems are expected to put that etag in the request to `UpdateVersion` to ensure that their change will be applied to the model as intended.

func (LookupVersionResultOutput) ExplanationConfig added in v0.8.0 

func (o LookupVersionResultOutput) ExplanationConfig() GoogleCloudMlV1__ExplanationConfigResponseOutput

Optional. Configures explainability features on the model's version. Some explanation features require additional metadata to be loaded as part of the model payload.

func (LookupVersionResultOutput) Framework added in v0.8.0 

func (o LookupVersionResultOutput) Framework() pulumi.StringOutput

Optional. The machine learning framework AI Platform uses to train this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, `XGBOOST`. If you do not specify a framework, AI Platform will analyze files in the deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the model to 1.4 or greater. Do **not** specify a framework if you're deploying a [custom prediction routine](/ai-platform/prediction/docs/custom-prediction-routines) or if you're using a [custom container](/ai-platform/prediction/docs/use-custom-container).

func (LookupVersionResultOutput) IsDefault added in v0.8.0 

func (o LookupVersionResultOutput) IsDefault() pulumi.BoolOutput

If true, this version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.methods.versions.setDefault.

func (LookupVersionResultOutput) Labels added in v0.8.0 

func (o LookupVersionResultOutput) Labels() pulumi.StringMapOutput

Optional. One or more labels that you can add, to organize your model versions. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.

func (LookupVersionResultOutput) LastMigrationModelId added in v0.8.0 

func (o LookupVersionResultOutput) LastMigrationModelId() pulumi.StringOutput

The [AI Platform (Unified) `Model`](https://cloud.google.com/ai-platform-unified/docs/reference/rest/v1beta1/projects.locations.models) ID for the last [model migration](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).

func (LookupVersionResultOutput) LastMigrationTime added in v0.8.0 

func (o LookupVersionResultOutput) LastMigrationTime() pulumi.StringOutput

The last time this version was successfully [migrated to AI Platform (Unified)](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).

func (LookupVersionResultOutput) LastUseTime added in v0.8.0 

func (o LookupVersionResultOutput) LastUseTime() pulumi.StringOutput

The time the version was last used for prediction.

func (LookupVersionResultOutput) MachineType added in v0.8.0 

func (o LookupVersionResultOutput) MachineType() pulumi.StringOutput

Optional. The type of machine on which to serve the model. Currently only applies to online prediction service. To learn about valid values for this field, read [Choosing a machine type for online prediction](/ai-platform/prediction/docs/machine-types-online-prediction). If this field is not specified and you are using a [regional endpoint](/ai-platform/prediction/docs/regional-endpoints), then the machine type defaults to `n1-standard-2`. If this field is not specified and you are using the global endpoint (`ml.googleapis.com`), then the machine type defaults to `mls1-c1-m2`.

func (LookupVersionResultOutput) ManualScaling added in v0.8.0 

func (o LookupVersionResultOutput) ManualScaling() GoogleCloudMlV1__ManualScalingResponseOutput

Manually select the number of nodes to use for serving the model. You should generally use `auto_scaling` with an appropriate `min_nodes` instead, but this option is available if you want more predictable billing. Beware that latency and error rates will increase if the traffic exceeds that capability of the system to serve it based on the selected number of nodes.

func (LookupVersionResultOutput) Name added in v0.8.0 

func (o LookupVersionResultOutput) Name() pulumi.StringOutput

The name specified for the version when it was created. The version name must be unique within the model it is created in.

func (LookupVersionResultOutput) PackageUris added in v0.8.0 

func (o LookupVersionResultOutput) PackageUris() pulumi.StringArrayOutput

Optional. Cloud Storage paths (`gs://…`) of packages for [custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines) or [scikit-learn pipelines with custom code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code). For a custom prediction routine, one of these packages must contain your Predictor class (see [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally, include any dependencies used by your Predictor or scikit-learn pipeline uses that are not already included in your selected [runtime version](/ml-engine/docs/tensorflow/runtime-version-list). If you specify this field, you must also set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.

func (LookupVersionResultOutput) PredictionClass added in v0.8.0 

func (o LookupVersionResultOutput) PredictionClass() pulumi.StringOutput

Optional. The fully qualified name (module_name.class_name) of a class that implements the Predictor interface described in this reference field. The module containing this class should be included in a package provided to the [`packageUris` field](#Version.FIELDS.package_uris). Specify this field if and only if you are deploying a [custom prediction routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines). If you specify this field, you must set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater and you must set `machineType` to a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction). The following code sample provides the Predictor interface: class Predictor(object): """Interface for constructing custom predictors.""" def predict(self, instances, **kwargs): """Performs custom prediction. Instances are the decoded values from the request. They have already been deserialized from JSON. Args: instances: A list of prediction input instances. **kwargs: A dictionary of keyword args provided as additional fields on the predict request body. Returns: A list of outputs containing the prediction results. This list must be JSON serializable. """ raise NotImplementedError() @classmethod def from_path(cls, model_dir): """Creates an instance of Predictor using the given path. Loading of the predictor should be done in this method. Args: model_dir: The local directory that contains the exported model file along with any additional files uploaded when creating the version resource. Returns: An instance implementing this Predictor class. """ raise NotImplementedError() Learn more about [the Predictor interface and custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines).

func (LookupVersionResultOutput) PythonVersion added in v0.8.0 

func (o LookupVersionResultOutput) PythonVersion() pulumi.StringOutput

The version of Python used in prediction. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).

func (LookupVersionResultOutput) RequestLoggingConfig added in v0.8.0 

func (o LookupVersionResultOutput) RequestLoggingConfig() GoogleCloudMlV1__RequestLoggingConfigResponseOutput

Optional. *Only* specify this field in a projects.models.versions.patch request. Specifying it in a projects.models.versions.create request has no effect. Configures the request-response pair logging on predictions from this Version.

func (LookupVersionResultOutput) Routes added in v0.8.0 

func (o LookupVersionResultOutput) Routes() GoogleCloudMlV1__RouteMapResponseOutput

Optional. Specifies paths on a custom container's HTTP server where AI Platform Prediction sends certain requests. If you specify this field, then you must also specify the `container` field. If you specify the `container` field and do not specify this field, it defaults to the following: ``` json { "predict": "/v1/models/MODEL/versions/VERSION:predict", "health": "/v1/models/MODEL/versions/VERSION" } ``` See RouteMap for more details about these default values.

func (LookupVersionResultOutput) RuntimeVersion added in v0.8.0 

func (o LookupVersionResultOutput) RuntimeVersion() pulumi.StringOutput

The AI Platform runtime version to use for this deployment. For more information, see the [runtime version list](/ml-engine/docs/runtime-version-list) and [how to manage runtime versions](/ml-engine/docs/versioning).

func (LookupVersionResultOutput) ServiceAccount added in v0.8.0 

func (o LookupVersionResultOutput) ServiceAccount() pulumi.StringOutput

Optional. Specifies the service account for resource access control. If you specify this field, then you must also specify either the `containerSpec` or the `predictionClass` field. Learn more about [using a custom service account](/ai-platform/prediction/docs/custom-service-account).

func (LookupVersionResultOutput) State added in v0.8.0 

func (o LookupVersionResultOutput) State() pulumi.StringOutput

The state of a version.

func (LookupVersionResultOutput) ToLookupVersionResultOutput added in v0.8.0 

func (o LookupVersionResultOutput) ToLookupVersionResultOutput() LookupVersionResultOutput

func (LookupVersionResultOutput) ToLookupVersionResultOutputWithContext added in v0.8.0 

func (o LookupVersionResultOutput) ToLookupVersionResultOutputWithContext(ctx context.Context) LookupVersionResultOutput

type Model 

type Model struct {
	pulumi.CustomResourceState

	// The default version of the model. This version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.models.versions.setDefault.
	DefaultVersion GoogleCloudMlV1__VersionResponseOutput `pulumi:"defaultVersion"`
	// Optional. The description specified for the model when it was created.
	Description pulumi.StringOutput `pulumi:"description"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Optional. One or more labels that you can add, to organize your models. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels pulumi.StringMapOutput `pulumi:"labels"`
	// The name specified for the model when it was created. The model name must be unique within the project it is created in.
	Name pulumi.StringOutput `pulumi:"name"`
	// Optional. If true, online prediction nodes send `stderr` and `stdout` streams to Cloud Logging. These can be more verbose than the standard access logs (see `onlinePredictionLogging`) and can incur higher cost. However, they are helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high QPS. Estimate your costs before enabling this option. Default is false.
	OnlinePredictionConsoleLogging pulumi.BoolOutput `pulumi:"onlinePredictionConsoleLogging"`
	// Optional. If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each request. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option. Default is false.
	OnlinePredictionLogging pulumi.BoolOutput `pulumi:"onlinePredictionLogging"`
	// Optional. The list of regions where the model is going to be deployed. Only one region per model is supported. Defaults to 'us-central1' if nothing is set. See the available regions for AI Platform services. Note: * No matter where a model is deployed, it can always be accessed by users from anywhere, both for online and batch prediction. * The region for a batch prediction job is set by the region field when submitting the batch prediction job and does not take its value from this field.
	Regions pulumi.StringArrayOutput `pulumi:"regions"`
}

Creates a model which will later contain one or more versions. You must add at least one version before you can request predictions from the model. Add versions by calling projects.models.versions.create.

func GetModel 

func GetModel(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *ModelState, opts ...pulumi.ResourceOption) (*Model, error)

GetModel gets an existing Model resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewModel 

func NewModel(ctx *pulumi.Context,
	name string, args *ModelArgs, opts ...pulumi.ResourceOption) (*Model, error)

NewModel registers a new resource with the given unique name, arguments, and options.

func (*Model) ElementType 

func (*Model) ElementType() reflect.Type

func (*Model) ToModelOutput 

func (i *Model) ToModelOutput() ModelOutput

func (*Model) ToModelOutputWithContext 

func (i *Model) ToModelOutputWithContext(ctx context.Context) ModelOutput

type ModelArgs 

type ModelArgs struct {
	// Optional. The description specified for the model when it was created.
	Description pulumi.StringPtrInput
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetModel`, and systems are expected to put that etag in the request to `UpdateModel` to ensure that their change will be applied to the model as intended.
	Etag pulumi.StringPtrInput
	// Optional. One or more labels that you can add, to organize your models. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels pulumi.StringMapInput
	// The name specified for the model when it was created. The model name must be unique within the project it is created in.
	Name pulumi.StringPtrInput
	// Optional. If true, online prediction nodes send `stderr` and `stdout` streams to Cloud Logging. These can be more verbose than the standard access logs (see `onlinePredictionLogging`) and can incur higher cost. However, they are helpful for debugging. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high QPS. Estimate your costs before enabling this option. Default is false.
	OnlinePredictionConsoleLogging pulumi.BoolPtrInput
	// Optional. If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each request. Note that [logs may incur a cost](/stackdriver/pricing), especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option. Default is false.
	OnlinePredictionLogging pulumi.BoolPtrInput
	Project                 pulumi.StringPtrInput
	// Optional. The list of regions where the model is going to be deployed. Only one region per model is supported. Defaults to 'us-central1' if nothing is set. See the available regions for AI Platform services. Note: * No matter where a model is deployed, it can always be accessed by users from anywhere, both for online and batch prediction. * The region for a batch prediction job is set by the region field when submitting the batch prediction job and does not take its value from this field.
	Regions pulumi.StringArrayInput
}

The set of arguments for constructing a Model resource.

func (ModelArgs) ElementType 

func (ModelArgs) ElementType() reflect.Type

type ModelIamPolicy 

type ModelIamPolicy struct {
	pulumi.CustomResourceState

	// Specifies cloud audit logging configuration for this policy.
	AuditConfigs GoogleIamV1__AuditConfigResponseArrayOutput `pulumi:"auditConfigs"`
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings GoogleIamV1__BindingResponseArrayOutput `pulumi:"bindings"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntOutput `pulumi:"version"`
}

Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors. Note - this resource's API doesn't support deletion. When deleted, the resource will persist on Google Cloud even though it will be deleted from Pulumi state.

func GetModelIamPolicy 

func GetModelIamPolicy(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *ModelIamPolicyState, opts ...pulumi.ResourceOption) (*ModelIamPolicy, error)

GetModelIamPolicy gets an existing ModelIamPolicy resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewModelIamPolicy 

func NewModelIamPolicy(ctx *pulumi.Context,
	name string, args *ModelIamPolicyArgs, opts ...pulumi.ResourceOption) (*ModelIamPolicy, error)

NewModelIamPolicy registers a new resource with the given unique name, arguments, and options.

func (*ModelIamPolicy) ElementType 

func (*ModelIamPolicy) ElementType() reflect.Type

func (*ModelIamPolicy) ToModelIamPolicyOutput 

func (i *ModelIamPolicy) ToModelIamPolicyOutput() ModelIamPolicyOutput

func (*ModelIamPolicy) ToModelIamPolicyOutputWithContext 

func (i *ModelIamPolicy) ToModelIamPolicyOutputWithContext(ctx context.Context) ModelIamPolicyOutput

type ModelIamPolicyArgs 

type ModelIamPolicyArgs struct {
	// Specifies cloud audit logging configuration for this policy.
	AuditConfigs GoogleIamV1__AuditConfigArrayInput
	// Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`.
	Bindings GoogleIamV1__BindingArrayInput
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
	Etag    pulumi.StringPtrInput
	ModelId pulumi.StringInput
	Project pulumi.StringPtrInput
	// OPTIONAL: A FieldMask specifying which fields of the policy to modify. Only the fields in the mask will be modified. If no mask is provided, the following default mask is used: `paths: "bindings, etag"`
	UpdateMask pulumi.StringPtrInput
	// Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
	Version pulumi.IntPtrInput
}

The set of arguments for constructing a ModelIamPolicy resource.

func (ModelIamPolicyArgs) ElementType 

func (ModelIamPolicyArgs) ElementType() reflect.Type

type ModelIamPolicyInput 

type ModelIamPolicyInput interface {
	pulumi.Input

	ToModelIamPolicyOutput() ModelIamPolicyOutput
	ToModelIamPolicyOutputWithContext(ctx context.Context) ModelIamPolicyOutput
}

type ModelIamPolicyOutput 

type ModelIamPolicyOutput struct{ *pulumi.OutputState }

func (ModelIamPolicyOutput) ElementType 

func (ModelIamPolicyOutput) ElementType() reflect.Type

func (ModelIamPolicyOutput) ToModelIamPolicyOutput 

func (o ModelIamPolicyOutput) ToModelIamPolicyOutput() ModelIamPolicyOutput

func (ModelIamPolicyOutput) ToModelIamPolicyOutputWithContext 

func (o ModelIamPolicyOutput) ToModelIamPolicyOutputWithContext(ctx context.Context) ModelIamPolicyOutput

type ModelIamPolicyState 

type ModelIamPolicyState struct {
}

func (ModelIamPolicyState) ElementType 

func (ModelIamPolicyState) ElementType() reflect.Type

type ModelInput 

type ModelInput interface {
	pulumi.Input

	ToModelOutput() ModelOutput
	ToModelOutputWithContext(ctx context.Context) ModelOutput
}

type ModelOutput 

type ModelOutput struct{ *pulumi.OutputState }

func (ModelOutput) ElementType 

func (ModelOutput) ElementType() reflect.Type

func (ModelOutput) ToModelOutput 

func (o ModelOutput) ToModelOutput() ModelOutput

func (ModelOutput) ToModelOutputWithContext 

func (o ModelOutput) ToModelOutputWithContext(ctx context.Context) ModelOutput

type ModelState 

type ModelState struct {
}

func (ModelState) ElementType 

func (ModelState) ElementType() reflect.Type

type Study 

type Study struct {
	pulumi.CustomResourceState

	// Time at which the study was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
	InactiveReason pulumi.StringOutput `pulumi:"inactiveReason"`
	// The name of a study.
	Name pulumi.StringOutput `pulumi:"name"`
	// The detailed state of a study.
	State pulumi.StringOutput `pulumi:"state"`
	// Configuration of the study.
	StudyConfig GoogleCloudMlV1__StudyConfigResponseOutput `pulumi:"studyConfig"`
}

Creates a study. Auto-naming is currently not supported for this resource.

func GetStudy 

func GetStudy(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *StudyState, opts ...pulumi.ResourceOption) (*Study, error)

GetStudy gets an existing Study resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewStudy 

func NewStudy(ctx *pulumi.Context,
	name string, args *StudyArgs, opts ...pulumi.ResourceOption) (*Study, error)

NewStudy registers a new resource with the given unique name, arguments, and options.

func (*Study) ElementType 

func (*Study) ElementType() reflect.Type

func (*Study) ToStudyOutput 

func (i *Study) ToStudyOutput() StudyOutput

func (*Study) ToStudyOutputWithContext 

func (i *Study) ToStudyOutputWithContext(ctx context.Context) StudyOutput

type StudyArgs 

type StudyArgs struct {
	Location pulumi.StringPtrInput
	Project  pulumi.StringPtrInput
	// Configuration of the study.
	StudyConfig GoogleCloudMlV1__StudyConfigInput
	StudyId     pulumi.StringInput
}

The set of arguments for constructing a Study resource.

func (StudyArgs) ElementType 

func (StudyArgs) ElementType() reflect.Type

type StudyInput 

type StudyInput interface {
	pulumi.Input

	ToStudyOutput() StudyOutput
	ToStudyOutputWithContext(ctx context.Context) StudyOutput
}

type StudyOutput 

type StudyOutput struct{ *pulumi.OutputState }

func (StudyOutput) ElementType 

func (StudyOutput) ElementType() reflect.Type

func (StudyOutput) ToStudyOutput 

func (o StudyOutput) ToStudyOutput() StudyOutput

func (StudyOutput) ToStudyOutputWithContext 

func (o StudyOutput) ToStudyOutputWithContext(ctx context.Context) StudyOutput

type StudyState 

type StudyState struct {
}

func (StudyState) ElementType 

func (StudyState) ElementType() reflect.Type

type Trial added in v0.3.0 

type Trial struct {
	pulumi.CustomResourceState

	// The identifier of the client that originally requested this trial.
	ClientId pulumi.StringOutput `pulumi:"clientId"`
	// Time at which the trial's status changed to COMPLETED.
	EndTime pulumi.StringOutput `pulumi:"endTime"`
	// The final measurement containing the objective value.
	FinalMeasurement GoogleCloudMlV1__MeasurementResponseOutput `pulumi:"finalMeasurement"`
	// A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
	InfeasibleReason pulumi.StringOutput `pulumi:"infeasibleReason"`
	// A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
	Measurements GoogleCloudMlV1__MeasurementResponseArrayOutput `pulumi:"measurements"`
	// Name of the trial assigned by the service.
	Name pulumi.StringOutput `pulumi:"name"`
	// The parameters of the trial.
	Parameters GoogleCloudMlV1_Trial_ParameterResponseArrayOutput `pulumi:"parameters"`
	// Time at which the trial was started.
	StartTime pulumi.StringOutput `pulumi:"startTime"`
	// The detailed state of a trial.
	State pulumi.StringOutput `pulumi:"state"`
	// If true, the parameters in this trial are not attempted again.
	TrialInfeasible pulumi.BoolOutput `pulumi:"trialInfeasible"`
}

Adds a user provided trial to a study. Auto-naming is currently not supported for this resource.

func GetTrial added in v0.3.0 

func GetTrial(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *TrialState, opts ...pulumi.ResourceOption) (*Trial, error)

GetTrial gets an existing Trial resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewTrial added in v0.3.0 

func NewTrial(ctx *pulumi.Context,
	name string, args *TrialArgs, opts ...pulumi.ResourceOption) (*Trial, error)

NewTrial registers a new resource with the given unique name, arguments, and options.

func (*Trial) ElementType added in v0.3.0 

func (*Trial) ElementType() reflect.Type

func (*Trial) ToTrialOutput added in v0.3.0 

func (i *Trial) ToTrialOutput() TrialOutput

func (*Trial) ToTrialOutputWithContext added in v0.3.0 

func (i *Trial) ToTrialOutputWithContext(ctx context.Context) TrialOutput

type TrialArgs added in v0.3.0 

type TrialArgs struct {
	// The final measurement containing the objective value.
	FinalMeasurement GoogleCloudMlV1__MeasurementPtrInput
	Location         pulumi.StringPtrInput
	// A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
	Measurements GoogleCloudMlV1__MeasurementArrayInput
	// The parameters of the trial.
	Parameters GoogleCloudMlV1_Trial_ParameterArrayInput
	Project    pulumi.StringPtrInput
	// The detailed state of a trial.
	State   TrialStateEnumPtrInput
	StudyId pulumi.StringInput
}

The set of arguments for constructing a Trial resource.

func (TrialArgs) ElementType added in v0.3.0 

func (TrialArgs) ElementType() reflect.Type

type TrialInput added in v0.3.0 

type TrialInput interface {
	pulumi.Input

	ToTrialOutput() TrialOutput
	ToTrialOutputWithContext(ctx context.Context) TrialOutput
}

type TrialOutput added in v0.3.0 

type TrialOutput struct{ *pulumi.OutputState }

func (TrialOutput) ElementType added in v0.3.0 

func (TrialOutput) ElementType() reflect.Type

func (TrialOutput) ToTrialOutput added in v0.3.0 

func (o TrialOutput) ToTrialOutput() TrialOutput

func (TrialOutput) ToTrialOutputWithContext added in v0.3.0 

func (o TrialOutput) ToTrialOutputWithContext(ctx context.Context) TrialOutput

type TrialState added in v0.3.0 

type TrialState struct {
}

func (TrialState) ElementType added in v0.3.0 

func (TrialState) ElementType() reflect.Type

type TrialStateEnum added in v0.4.0 

type TrialStateEnum string

The detailed state of a trial.

func (TrialStateEnum) ElementType added in v0.4.0 

func (TrialStateEnum) ElementType() reflect.Type

func (TrialStateEnum) ToStringOutput added in v0.4.0 

func (e TrialStateEnum) ToStringOutput() pulumi.StringOutput

func (TrialStateEnum) ToStringOutputWithContext added in v0.4.0 

func (e TrialStateEnum) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (TrialStateEnum) ToStringPtrOutput added in v0.4.0 

func (e TrialStateEnum) ToStringPtrOutput() pulumi.StringPtrOutput

func (TrialStateEnum) ToStringPtrOutputWithContext added in v0.4.0 

func (e TrialStateEnum) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

func (TrialStateEnum) ToTrialStateEnumOutput added in v0.6.0 

func (e TrialStateEnum) ToTrialStateEnumOutput() TrialStateEnumOutput

func (TrialStateEnum) ToTrialStateEnumOutputWithContext added in v0.6.0 

func (e TrialStateEnum) ToTrialStateEnumOutputWithContext(ctx context.Context) TrialStateEnumOutput

func (TrialStateEnum) ToTrialStateEnumPtrOutput added in v0.6.0 

func (e TrialStateEnum) ToTrialStateEnumPtrOutput() TrialStateEnumPtrOutput

func (TrialStateEnum) ToTrialStateEnumPtrOutputWithContext added in v0.6.0 

func (e TrialStateEnum) ToTrialStateEnumPtrOutputWithContext(ctx context.Context) TrialStateEnumPtrOutput

type TrialStateEnumInput added in v0.6.0 

type TrialStateEnumInput interface {
	pulumi.Input

	ToTrialStateEnumOutput() TrialStateEnumOutput
	ToTrialStateEnumOutputWithContext(context.Context) TrialStateEnumOutput
}

TrialStateEnumInput is an input type that accepts TrialStateEnumArgs and TrialStateEnumOutput values. You can construct a concrete instance of `TrialStateEnumInput` via: 

TrialStateEnumArgs{...}

type TrialStateEnumOutput added in v0.6.0 

type TrialStateEnumOutput struct{ *pulumi.OutputState }

func (TrialStateEnumOutput) ElementType added in v0.6.0 

func (TrialStateEnumOutput) ElementType() reflect.Type

func (TrialStateEnumOutput) ToStringOutput added in v0.6.0 

func (o TrialStateEnumOutput) ToStringOutput() pulumi.StringOutput

func (TrialStateEnumOutput) ToStringOutputWithContext added in v0.6.0 

func (o TrialStateEnumOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (TrialStateEnumOutput) ToStringPtrOutput added in v0.6.0 

func (o TrialStateEnumOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (TrialStateEnumOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o TrialStateEnumOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

func (TrialStateEnumOutput) ToTrialStateEnumOutput added in v0.6.0 

func (o TrialStateEnumOutput) ToTrialStateEnumOutput() TrialStateEnumOutput

func (TrialStateEnumOutput) ToTrialStateEnumOutputWithContext added in v0.6.0 

func (o TrialStateEnumOutput) ToTrialStateEnumOutputWithContext(ctx context.Context) TrialStateEnumOutput

func (TrialStateEnumOutput) ToTrialStateEnumPtrOutput added in v0.6.0 

func (o TrialStateEnumOutput) ToTrialStateEnumPtrOutput() TrialStateEnumPtrOutput

func (TrialStateEnumOutput) ToTrialStateEnumPtrOutputWithContext added in v0.6.0 

func (o TrialStateEnumOutput) ToTrialStateEnumPtrOutputWithContext(ctx context.Context) TrialStateEnumPtrOutput

type TrialStateEnumPtrInput added in v0.6.0 

type TrialStateEnumPtrInput interface {
	pulumi.Input

	ToTrialStateEnumPtrOutput() TrialStateEnumPtrOutput
	ToTrialStateEnumPtrOutputWithContext(context.Context) TrialStateEnumPtrOutput
}

func TrialStateEnumPtr added in v0.6.0 

func TrialStateEnumPtr(v string) TrialStateEnumPtrInput

type TrialStateEnumPtrOutput added in v0.6.0 

type TrialStateEnumPtrOutput struct{ *pulumi.OutputState }

func (TrialStateEnumPtrOutput) Elem added in v0.6.0 

func (o TrialStateEnumPtrOutput) Elem() TrialStateEnumOutput

func (TrialStateEnumPtrOutput) ElementType added in v0.6.0 

func (TrialStateEnumPtrOutput) ElementType() reflect.Type

func (TrialStateEnumPtrOutput) ToStringPtrOutput added in v0.6.0 

func (o TrialStateEnumPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (TrialStateEnumPtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o TrialStateEnumPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

func (TrialStateEnumPtrOutput) ToTrialStateEnumPtrOutput added in v0.6.0 

func (o TrialStateEnumPtrOutput) ToTrialStateEnumPtrOutput() TrialStateEnumPtrOutput

func (TrialStateEnumPtrOutput) ToTrialStateEnumPtrOutputWithContext added in v0.6.0 

func (o TrialStateEnumPtrOutput) ToTrialStateEnumPtrOutputWithContext(ctx context.Context) TrialStateEnumPtrOutput

type Version added in v0.3.0 

type Version struct {
	pulumi.CustomResourceState

	// Optional. Accelerator config for using GPUs for online prediction (beta). Only specify this field if you have specified a Compute Engine (N1) machine type in the `machineType` field. Learn more about [using GPUs for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).
	AcceleratorConfig GoogleCloudMlV1__AcceleratorConfigResponseOutput `pulumi:"acceleratorConfig"`
	// Automatically scale the number of nodes used to serve the model in response to increases and decreases in traffic. Care should be taken to ramp up traffic according to the model's ability to scale or you will start seeing increases in latency and 429 response codes.
	AutoScaling GoogleCloudMlV1__AutoScalingResponseOutput `pulumi:"autoScaling"`
	// Optional. Specifies a custom container to use for serving predictions. If you specify this field, then `machineType` is required. If you specify this field, then `deploymentUri` is optional. If you specify this field, then you must not specify `runtimeVersion`, `packageUris`, `framework`, `pythonVersion`, or `predictionClass`.
	Container GoogleCloudMlV1__ContainerSpecResponseOutput `pulumi:"container"`
	// The time the version was created.
	CreateTime pulumi.StringOutput `pulumi:"createTime"`
	// The Cloud Storage URI of a directory containing trained model artifacts to be used to create the model version. See the [guide to deploying models](/ai-platform/prediction/docs/deploying-models) for more information. The total number of files under this directory must not exceed 1000. During projects.models.versions.create, AI Platform Prediction copies all files from the specified directory to a location managed by the service. From then on, AI Platform Prediction uses these copies of the model artifacts to serve predictions, not the original files in Cloud Storage, so this location is useful only as a historical record. If you specify container, then this field is optional. Otherwise, it is required. Learn [how to use this field with a custom container](/ai-platform/prediction/docs/custom-container-requirements#artifacts).
	DeploymentUri pulumi.StringOutput `pulumi:"deploymentUri"`
	// Optional. The description specified for the version when it was created.
	Description pulumi.StringOutput `pulumi:"description"`
	// The details of a failure or a cancellation.
	ErrorMessage pulumi.StringOutput `pulumi:"errorMessage"`
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetVersion`, and systems are expected to put that etag in the request to `UpdateVersion` to ensure that their change will be applied to the model as intended.
	Etag pulumi.StringOutput `pulumi:"etag"`
	// Optional. Configures explainability features on the model's version. Some explanation features require additional metadata to be loaded as part of the model payload.
	ExplanationConfig GoogleCloudMlV1__ExplanationConfigResponseOutput `pulumi:"explanationConfig"`
	// Optional. The machine learning framework AI Platform uses to train this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, `XGBOOST`. If you do not specify a framework, AI Platform will analyze files in the deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the model to 1.4 or greater. Do **not** specify a framework if you're deploying a [custom prediction routine](/ai-platform/prediction/docs/custom-prediction-routines) or if you're using a [custom container](/ai-platform/prediction/docs/use-custom-container).
	Framework pulumi.StringOutput `pulumi:"framework"`
	// If true, this version will be used to handle prediction requests that do not specify a version. You can change the default version by calling projects.methods.versions.setDefault.
	IsDefault pulumi.BoolOutput `pulumi:"isDefault"`
	// Optional. One or more labels that you can add, to organize your model versions. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels pulumi.StringMapOutput `pulumi:"labels"`
	// The [AI Platform (Unified) `Model`](https://cloud.google.com/ai-platform-unified/docs/reference/rest/v1beta1/projects.locations.models) ID for the last [model migration](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).
	LastMigrationModelId pulumi.StringOutput `pulumi:"lastMigrationModelId"`
	// The last time this version was successfully [migrated to AI Platform (Unified)](https://cloud.google.com/ai-platform-unified/docs/start/migrating-to-ai-platform-unified).
	LastMigrationTime pulumi.StringOutput `pulumi:"lastMigrationTime"`
	// The time the version was last used for prediction.
	LastUseTime pulumi.StringOutput `pulumi:"lastUseTime"`
	// Optional. The type of machine on which to serve the model. Currently only applies to online prediction service. To learn about valid values for this field, read [Choosing a machine type for online prediction](/ai-platform/prediction/docs/machine-types-online-prediction). If this field is not specified and you are using a [regional endpoint](/ai-platform/prediction/docs/regional-endpoints), then the machine type defaults to `n1-standard-2`. If this field is not specified and you are using the global endpoint (`ml.googleapis.com`), then the machine type defaults to `mls1-c1-m2`.
	MachineType pulumi.StringOutput `pulumi:"machineType"`
	// Manually select the number of nodes to use for serving the model. You should generally use `auto_scaling` with an appropriate `min_nodes` instead, but this option is available if you want more predictable billing. Beware that latency and error rates will increase if the traffic exceeds that capability of the system to serve it based on the selected number of nodes.
	ManualScaling GoogleCloudMlV1__ManualScalingResponseOutput `pulumi:"manualScaling"`
	// The name specified for the version when it was created. The version name must be unique within the model it is created in.
	Name pulumi.StringOutput `pulumi:"name"`
	// Optional. Cloud Storage paths (`gs://…`) of packages for [custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines) or [scikit-learn pipelines with custom code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code). For a custom prediction routine, one of these packages must contain your Predictor class (see [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally, include any dependencies used by your Predictor or scikit-learn pipeline uses that are not already included in your selected [runtime version](/ml-engine/docs/tensorflow/runtime-version-list). If you specify this field, you must also set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
	PackageUris pulumi.StringArrayOutput `pulumi:"packageUris"`
	// Optional. The fully qualified name (module_name.class_name) of a class that implements the Predictor interface described in this reference field. The module containing this class should be included in a package provided to the [`packageUris` field](#Version.FIELDS.package_uris). Specify this field if and only if you are deploying a [custom prediction routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines). If you specify this field, you must set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater and you must set `machineType` to a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction). The following code sample provides the Predictor interface: class Predictor(object): """Interface for constructing custom predictors.""" def predict(self, instances, **kwargs): """Performs custom prediction. Instances are the decoded values from the request. They have already been deserialized from JSON. Args: instances: A list of prediction input instances. **kwargs: A dictionary of keyword args provided as additional fields on the predict request body. Returns: A list of outputs containing the prediction results. This list must be JSON serializable. """ raise NotImplementedError() @classmethod def from_path(cls, model_dir): """Creates an instance of Predictor using the given path. Loading of the predictor should be done in this method. Args: model_dir: The local directory that contains the exported model file along with any additional files uploaded when creating the version resource. Returns: An instance implementing this Predictor class. """ raise NotImplementedError() Learn more about [the Predictor interface and custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
	PredictionClass pulumi.StringOutput `pulumi:"predictionClass"`
	// The version of Python used in prediction. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).
	PythonVersion pulumi.StringOutput `pulumi:"pythonVersion"`
	// Optional. *Only* specify this field in a projects.models.versions.patch request. Specifying it in a projects.models.versions.create request has no effect. Configures the request-response pair logging on predictions from this Version.
	RequestLoggingConfig GoogleCloudMlV1__RequestLoggingConfigResponseOutput `pulumi:"requestLoggingConfig"`
	// Optional. Specifies paths on a custom container's HTTP server where AI Platform Prediction sends certain requests. If you specify this field, then you must also specify the `container` field. If you specify the `container` field and do not specify this field, it defaults to the following: “` json { "predict": "/v1/models/MODEL/versions/VERSION:predict", "health": "/v1/models/MODEL/versions/VERSION" }  “` See RouteMap for more details about these default values.
	Routes GoogleCloudMlV1__RouteMapResponseOutput `pulumi:"routes"`
	// The AI Platform runtime version to use for this deployment. For more information, see the [runtime version list](/ml-engine/docs/runtime-version-list) and [how to manage runtime versions](/ml-engine/docs/versioning).
	RuntimeVersion pulumi.StringOutput `pulumi:"runtimeVersion"`
	// Optional. Specifies the service account for resource access control. If you specify this field, then you must also specify either the `containerSpec` or the `predictionClass` field. Learn more about [using a custom service account](/ai-platform/prediction/docs/custom-service-account).
	ServiceAccount pulumi.StringOutput `pulumi:"serviceAccount"`
	// The state of a version.
	State pulumi.StringOutput `pulumi:"state"`
}

Creates a new version of a model from a trained TensorFlow model. If the version created in the cloud by this call is the first deployed version of the specified model, it will be made the default version of the model. When you add a version to a model that already has one or more versions, the default version does not automatically change. If you want a new version to be the default, you must call projects.models.versions.setDefault.

func GetVersion added in v0.3.0 

func GetVersion(ctx *pulumi.Context,
	name string, id pulumi.IDInput, state *VersionState, opts ...pulumi.ResourceOption) (*Version, error)

GetVersion gets an existing Version resource's state with the given name, ID, and optional state properties that are used to uniquely qualify the lookup (nil if not required).

func NewVersion added in v0.3.0 

func NewVersion(ctx *pulumi.Context,
	name string, args *VersionArgs, opts ...pulumi.ResourceOption) (*Version, error)

NewVersion registers a new resource with the given unique name, arguments, and options.

func (*Version) ElementType added in v0.3.0 

func (*Version) ElementType() reflect.Type

func (*Version) ToVersionOutput added in v0.3.0 

func (i *Version) ToVersionOutput() VersionOutput

func (*Version) ToVersionOutputWithContext added in v0.3.0 

func (i *Version) ToVersionOutputWithContext(ctx context.Context) VersionOutput

type VersionArgs added in v0.3.0 

type VersionArgs struct {
	// Optional. Accelerator config for using GPUs for online prediction (beta). Only specify this field if you have specified a Compute Engine (N1) machine type in the `machineType` field. Learn more about [using GPUs for online prediction](/ml-engine/docs/machine-types-online-prediction#gpus).
	AcceleratorConfig GoogleCloudMlV1__AcceleratorConfigPtrInput
	// Automatically scale the number of nodes used to serve the model in response to increases and decreases in traffic. Care should be taken to ramp up traffic according to the model's ability to scale or you will start seeing increases in latency and 429 response codes.
	AutoScaling GoogleCloudMlV1__AutoScalingPtrInput
	// Optional. Specifies a custom container to use for serving predictions. If you specify this field, then `machineType` is required. If you specify this field, then `deploymentUri` is optional. If you specify this field, then you must not specify `runtimeVersion`, `packageUris`, `framework`, `pythonVersion`, or `predictionClass`.
	Container GoogleCloudMlV1__ContainerSpecPtrInput
	// The Cloud Storage URI of a directory containing trained model artifacts to be used to create the model version. See the [guide to deploying models](/ai-platform/prediction/docs/deploying-models) for more information. The total number of files under this directory must not exceed 1000. During projects.models.versions.create, AI Platform Prediction copies all files from the specified directory to a location managed by the service. From then on, AI Platform Prediction uses these copies of the model artifacts to serve predictions, not the original files in Cloud Storage, so this location is useful only as a historical record. If you specify container, then this field is optional. Otherwise, it is required. Learn [how to use this field with a custom container](/ai-platform/prediction/docs/custom-container-requirements#artifacts).
	DeploymentUri pulumi.StringPtrInput
	// Optional. The description specified for the version when it was created.
	Description pulumi.StringPtrInput
	// `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a model from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform model updates in order to avoid race conditions: An `etag` is returned in the response to `GetVersion`, and systems are expected to put that etag in the request to `UpdateVersion` to ensure that their change will be applied to the model as intended.
	Etag pulumi.StringPtrInput
	// Optional. Configures explainability features on the model's version. Some explanation features require additional metadata to be loaded as part of the model payload.
	ExplanationConfig GoogleCloudMlV1__ExplanationConfigPtrInput
	// Optional. The machine learning framework AI Platform uses to train this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, `XGBOOST`. If you do not specify a framework, AI Platform will analyze files in the deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the model to 1.4 or greater. Do **not** specify a framework if you're deploying a [custom prediction routine](/ai-platform/prediction/docs/custom-prediction-routines) or if you're using a [custom container](/ai-platform/prediction/docs/use-custom-container).
	Framework VersionFrameworkPtrInput
	// Optional. One or more labels that you can add, to organize your model versions. Each label is a key-value pair, where both the key and the value are arbitrary strings that you supply. For more information, see the documentation on using labels.
	Labels pulumi.StringMapInput
	// Optional. The type of machine on which to serve the model. Currently only applies to online prediction service. To learn about valid values for this field, read [Choosing a machine type for online prediction](/ai-platform/prediction/docs/machine-types-online-prediction). If this field is not specified and you are using a [regional endpoint](/ai-platform/prediction/docs/regional-endpoints), then the machine type defaults to `n1-standard-2`. If this field is not specified and you are using the global endpoint (`ml.googleapis.com`), then the machine type defaults to `mls1-c1-m2`.
	MachineType pulumi.StringPtrInput
	// Manually select the number of nodes to use for serving the model. You should generally use `auto_scaling` with an appropriate `min_nodes` instead, but this option is available if you want more predictable billing. Beware that latency and error rates will increase if the traffic exceeds that capability of the system to serve it based on the selected number of nodes.
	ManualScaling GoogleCloudMlV1__ManualScalingPtrInput
	ModelId       pulumi.StringInput
	// The name specified for the version when it was created. The version name must be unique within the model it is created in.
	Name pulumi.StringPtrInput
	// Optional. Cloud Storage paths (`gs://…`) of packages for [custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines) or [scikit-learn pipelines with custom code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code). For a custom prediction routine, one of these packages must contain your Predictor class (see [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally, include any dependencies used by your Predictor or scikit-learn pipeline uses that are not already included in your selected [runtime version](/ml-engine/docs/tensorflow/runtime-version-list). If you specify this field, you must also set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
	PackageUris pulumi.StringArrayInput
	// Optional. The fully qualified name (module_name.class_name) of a class that implements the Predictor interface described in this reference field. The module containing this class should be included in a package provided to the [`packageUris` field](#Version.FIELDS.package_uris). Specify this field if and only if you are deploying a [custom prediction routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines). If you specify this field, you must set [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater and you must set `machineType` to a [legacy (MLS1) machine type](/ml-engine/docs/machine-types-online-prediction). The following code sample provides the Predictor interface: class Predictor(object): """Interface for constructing custom predictors.""" def predict(self, instances, **kwargs): """Performs custom prediction. Instances are the decoded values from the request. They have already been deserialized from JSON. Args: instances: A list of prediction input instances. **kwargs: A dictionary of keyword args provided as additional fields on the predict request body. Returns: A list of outputs containing the prediction results. This list must be JSON serializable. """ raise NotImplementedError() @classmethod def from_path(cls, model_dir): """Creates an instance of Predictor using the given path. Loading of the predictor should be done in this method. Args: model_dir: The local directory that contains the exported model file along with any additional files uploaded when creating the version resource. Returns: An instance implementing this Predictor class. """ raise NotImplementedError() Learn more about [the Predictor interface and custom prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
	PredictionClass pulumi.StringPtrInput
	Project         pulumi.StringPtrInput
	// The version of Python used in prediction. The following Python versions are available: * Python '3.7' is available when `runtime_version` is set to '1.15' or later. * Python '3.5' is available when `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7' is available when `runtime_version` is set to '1.15' or earlier. Read more about the Python versions available for [each runtime version](/ml-engine/docs/runtime-version-list).
	PythonVersion pulumi.StringInput
	// Optional. *Only* specify this field in a projects.models.versions.patch request. Specifying it in a projects.models.versions.create request has no effect. Configures the request-response pair logging on predictions from this Version.
	RequestLoggingConfig GoogleCloudMlV1__RequestLoggingConfigPtrInput
	// Optional. Specifies paths on a custom container's HTTP server where AI Platform Prediction sends certain requests. If you specify this field, then you must also specify the `container` field. If you specify the `container` field and do not specify this field, it defaults to the following: “` json { "predict": "/v1/models/MODEL/versions/VERSION:predict", "health": "/v1/models/MODEL/versions/VERSION" }  “` See RouteMap for more details about these default values.
	Routes GoogleCloudMlV1__RouteMapPtrInput
	// The AI Platform runtime version to use for this deployment. For more information, see the [runtime version list](/ml-engine/docs/runtime-version-list) and [how to manage runtime versions](/ml-engine/docs/versioning).
	RuntimeVersion pulumi.StringInput
	// Optional. Specifies the service account for resource access control. If you specify this field, then you must also specify either the `containerSpec` or the `predictionClass` field. Learn more about [using a custom service account](/ai-platform/prediction/docs/custom-service-account).
	ServiceAccount pulumi.StringPtrInput
}

The set of arguments for constructing a Version resource.

func (VersionArgs) ElementType added in v0.3.0 

func (VersionArgs) ElementType() reflect.Type

type VersionFramework added in v0.4.0 

type VersionFramework string

Optional. The machine learning framework AI Platform uses to train this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`, `XGBOOST`. If you do not specify a framework, AI Platform will analyze files in the deployment_uri to determine a framework. If you choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the model to 1.4 or greater. Do **not** specify a framework if you're deploying a [custom prediction routine](/ai-platform/prediction/docs/custom-prediction-routines) or if you're using a [custom container](/ai-platform/prediction/docs/use-custom-container).

func (VersionFramework) ElementType added in v0.4.0 

func (VersionFramework) ElementType() reflect.Type

func (VersionFramework) ToStringOutput added in v0.4.0 

func (e VersionFramework) ToStringOutput() pulumi.StringOutput

func (VersionFramework) ToStringOutputWithContext added in v0.4.0 

func (e VersionFramework) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (VersionFramework) ToStringPtrOutput added in v0.4.0 

func (e VersionFramework) ToStringPtrOutput() pulumi.StringPtrOutput

func (VersionFramework) ToStringPtrOutputWithContext added in v0.4.0 

func (e VersionFramework) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

func (VersionFramework) ToVersionFrameworkOutput added in v0.6.0 

func (e VersionFramework) ToVersionFrameworkOutput() VersionFrameworkOutput

func (VersionFramework) ToVersionFrameworkOutputWithContext added in v0.6.0 

func (e VersionFramework) ToVersionFrameworkOutputWithContext(ctx context.Context) VersionFrameworkOutput

func (VersionFramework) ToVersionFrameworkPtrOutput added in v0.6.0 

func (e VersionFramework) ToVersionFrameworkPtrOutput() VersionFrameworkPtrOutput

func (VersionFramework) ToVersionFrameworkPtrOutputWithContext added in v0.6.0 

func (e VersionFramework) ToVersionFrameworkPtrOutputWithContext(ctx context.Context) VersionFrameworkPtrOutput

type VersionFrameworkInput added in v0.6.0 

type VersionFrameworkInput interface {
	pulumi.Input

	ToVersionFrameworkOutput() VersionFrameworkOutput
	ToVersionFrameworkOutputWithContext(context.Context) VersionFrameworkOutput
}

VersionFrameworkInput is an input type that accepts VersionFrameworkArgs and VersionFrameworkOutput values. You can construct a concrete instance of `VersionFrameworkInput` via: 

VersionFrameworkArgs{...}

type VersionFrameworkOutput added in v0.6.0 

type VersionFrameworkOutput struct{ *pulumi.OutputState }

func (VersionFrameworkOutput) ElementType added in v0.6.0 

func (VersionFrameworkOutput) ElementType() reflect.Type

func (VersionFrameworkOutput) ToStringOutput added in v0.6.0 

func (o VersionFrameworkOutput) ToStringOutput() pulumi.StringOutput

func (VersionFrameworkOutput) ToStringOutputWithContext added in v0.6.0 

func (o VersionFrameworkOutput) ToStringOutputWithContext(ctx context.Context) pulumi.StringOutput

func (VersionFrameworkOutput) ToStringPtrOutput added in v0.6.0 

func (o VersionFrameworkOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (VersionFrameworkOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o VersionFrameworkOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

func (VersionFrameworkOutput) ToVersionFrameworkOutput added in v0.6.0 

func (o VersionFrameworkOutput) ToVersionFrameworkOutput() VersionFrameworkOutput

func (VersionFrameworkOutput) ToVersionFrameworkOutputWithContext added in v0.6.0 

func (o VersionFrameworkOutput) ToVersionFrameworkOutputWithContext(ctx context.Context) VersionFrameworkOutput

func (VersionFrameworkOutput) ToVersionFrameworkPtrOutput added in v0.6.0 

func (o VersionFrameworkOutput) ToVersionFrameworkPtrOutput() VersionFrameworkPtrOutput

func (VersionFrameworkOutput) ToVersionFrameworkPtrOutputWithContext added in v0.6.0 

func (o VersionFrameworkOutput) ToVersionFrameworkPtrOutputWithContext(ctx context.Context) VersionFrameworkPtrOutput

type VersionFrameworkPtrInput added in v0.6.0 

type VersionFrameworkPtrInput interface {
	pulumi.Input

	ToVersionFrameworkPtrOutput() VersionFrameworkPtrOutput
	ToVersionFrameworkPtrOutputWithContext(context.Context) VersionFrameworkPtrOutput
}

func VersionFrameworkPtr added in v0.6.0 

func VersionFrameworkPtr(v string) VersionFrameworkPtrInput

type VersionFrameworkPtrOutput added in v0.6.0 

type VersionFrameworkPtrOutput struct{ *pulumi.OutputState }

func (VersionFrameworkPtrOutput) Elem added in v0.6.0 

func (o VersionFrameworkPtrOutput) Elem() VersionFrameworkOutput

func (VersionFrameworkPtrOutput) ElementType added in v0.6.0 

func (VersionFrameworkPtrOutput) ElementType() reflect.Type

func (VersionFrameworkPtrOutput) ToStringPtrOutput added in v0.6.0 

func (o VersionFrameworkPtrOutput) ToStringPtrOutput() pulumi.StringPtrOutput

func (VersionFrameworkPtrOutput) ToStringPtrOutputWithContext added in v0.6.0 

func (o VersionFrameworkPtrOutput) ToStringPtrOutputWithContext(ctx context.Context) pulumi.StringPtrOutput

func (VersionFrameworkPtrOutput) ToVersionFrameworkPtrOutput added in v0.6.0 

func (o VersionFrameworkPtrOutput) ToVersionFrameworkPtrOutput() VersionFrameworkPtrOutput

func (VersionFrameworkPtrOutput) ToVersionFrameworkPtrOutputWithContext added in v0.6.0 

func (o VersionFrameworkPtrOutput) ToVersionFrameworkPtrOutputWithContext(ctx context.Context) VersionFrameworkPtrOutput

type VersionInput added in v0.3.0 

type VersionInput interface {
	pulumi.Input

	ToVersionOutput() VersionOutput
	ToVersionOutputWithContext(ctx context.Context) VersionOutput
}

type VersionOutput added in v0.3.0 

type VersionOutput struct{ *pulumi.OutputState }

func (VersionOutput) ElementType added in v0.3.0 

func (VersionOutput) ElementType() reflect.Type

func (VersionOutput) ToVersionOutput added in v0.3.0 

func (o VersionOutput) ToVersionOutput() VersionOutput

func (VersionOutput) ToVersionOutputWithContext added in v0.3.0 

func (o VersionOutput) ToVersionOutputWithContext(ctx context.Context) VersionOutput

type VersionState added in v0.3.0 

type VersionState struct {
}

func (VersionState) ElementType added in v0.3.0 

func (VersionState) ElementType() reflect.Type

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