Documentation ¶
Overview ¶
Package tensorflow is a Go binding to TensorFlow.
The API is subject to change and may break at any time.
Index ¶
Constants ¶
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Variables ¶
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Functions ¶
This section is empty.
Types ¶
type DataType ¶
type DataType C.TF_DataType
DataType holds the type for a scalar value. E.g., one slot in a tensor. The values here are identical to corresponding values in types.proto.
type Graph ¶
type Graph struct {
// contains filtered or unexported fields
}
Graph represents a computation graph. Graphs may be shared between sessions.
type Operation ¶
type Operation struct {
// contains filtered or unexported fields
}
Operation that has been added to the graph.
type Output ¶
type Output struct { // Op is the Operation that produces this Output. Op *Operation // Index specifies the index of the output within the Operation. Index int }
Output represents one of the outputs of an operation in the graph. Has a DataType (and eventually a Shape). May be passed as an input argument to a function for adding operations to a graph, or to a Session's Run() method to fetch that output as a tensor.
type Session ¶
type Session struct {
// contains filtered or unexported fields
}
Session drives a TensorFlow graph computation.
When a Session is created with a given target, a new Session object is bound to the universe of resources specified by that target. Those resources are available to this session to perform computation described in the GraphDef. After creating the session with a graph, the caller uses the Run() API to perform the computation and potentially fetch outputs as Tensors. A Session allows concurrent calls to Run().
func NewSession ¶
func NewSession(graph *Graph, options *SessionOptions) (*Session, error)
NewSession creates a new execution session with the associated graph. options may be nil to use the default options.
func (*Session) Close ¶
Close a session. This contacts any other processes associated with this session, if applicable. Blocks until all previous calls to Run have returned.
func (*Session) Run ¶
func (s *Session) Run(inputs map[Output]*Tensor, outputs []Output, targets []*Operation) ([]*Tensor, error)
Run the graph with the associated session starting with the supplied inputs. inputs and outputs may be set to nil. Runs, but does not return Tensors for operations specified in targets.
On success, returns the Tensor outputs in the same order as supplied in the outputs argument. If outputs is set to nil, the returned Tensor outputs is empty.
type SessionOptions ¶
type SessionOptions struct { // Target indicates the TensorFlow runtime to connect to. // // If 'target' is empty or unspecified, the local TensorFlow runtime // implementation will be used. Otherwise, the TensorFlow engine // defined by 'target' will be used to perform all computations. // // "target" can be either a single entry or a comma separated list // of entries. Each entry is a resolvable address of one of the // following formats: // local // ip:port // host:port // ... other system-specific formats to identify tasks and jobs ... // // NOTE: at the moment 'local' maps to an in-process service-based // runtime. // // Upon creation, a single session affines itself to one of the // remote processes, with possible load balancing choices when the // "target" resolves to a list of possible processes. // // If the session disconnects from the remote process during its // lifetime, session calls may fail immediately. Target string }
SessionOptions contains configuration information for a session.
type Tensor ¶
type Tensor struct {
// contains filtered or unexported fields
}
Tensor holds a multi-dimensional array of elements of a single data type.
func NewTensor ¶
NewTensor converts from a Go value to a Tensor. Valid values are scalars, slices, and arrays. Every element of a slice must have the same length so that the resulting Tensor has a valid shape.
func (*Tensor) Value ¶
func (t *Tensor) Value() interface{}
Value converts the Tensor to a Go value. For now, not all Tensor types are supported, and this function may panic if it encounters an unsupported DataType.
The type of the output depends on the Tensor type and dimensions. For example: Tensor(int64, 0): int64 Tensor(float64, 3): [][][]float64