golgi

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 Go to latest Published: Jan 31, 2022 License: MIT Imports: 11 Imported by: 2

README

golgi

Golgi is a package that makes creating neural networks with Gorgonia simpler. Common neural network patterns are supported. It is best used with the qol package (gorgonia.org/qol).

High Level Goals

The high-level goals of this package is to make simple things easy, and yet not sacrificing the options for customization.

Documentation

Overview

Example 
package main

import (
	"fmt"

	. "gorgonia.org/golgi"
	"gorgonia.org/gorgonia"
	"gorgonia.org/tensor"
)

func softmax(a *gorgonia.Node) (*gorgonia.Node, error) { return gorgonia.SoftMax(a) }

func main() {
	n := 100
	of := tensor.Float64
	g := gorgonia.NewGraph()
	x := gorgonia.NewTensor(g, of, 4, gorgonia.WithName("X"), gorgonia.WithShape(n, 1, 28, 28), gorgonia.WithInit(gorgonia.GlorotU(1)))
	y := gorgonia.NewMatrix(g, of, gorgonia.WithName("Y"), gorgonia.WithShape(n, 10), gorgonia.WithInit(gorgonia.GlorotU(1)))
	nn, err := ComposeSeq(
		x,
		L(ConsReshape, ToShape(n, 784)),
		L(ConsFC, WithSize(50), WithName("l0"), AsBatched(true), WithActivation(gorgonia.Tanh), WithBias(true)),
		L(ConsDropout, WithProbability(0.5)),
		L(ConsFC, WithSize(150), WithName("l1"), AsBatched(true), WithActivation(gorgonia.Rectify)), // by default WithBias is true
		L(ConsLayerNorm, WithSize(20), WithName("Norm"), WithEps(0.001)),
		L(ConsFC, WithSize(10), WithName("l2"), AsBatched(true), WithActivation(softmax), WithBias(false)),
	)
	if err != nil {
		panic(err)
	}

	out := nn.Fwd(x)
	if err = gorgonia.CheckOne(out); err != nil {
		panic(err)
	}

	cost := gorgonia.Must(RMS(out, y))
	model := nn.Model()
	if _, err = gorgonia.Grad(cost, model...); err != nil {
		panic(err)
	}

	m := gorgonia.NewTapeMachine(g)
	if err := m.RunAll(); err != nil {
		panic(err)
	}

	fmt.Printf("Model: %v\n", model)
}

Output:

Model: [l0_W, l0_B, l1_W, l1_B, Norm_W, Norm_B, l2_W]
Example (Extension) 
package main

import (
	"fmt"

	"github.com/pkg/errors"
	. "gorgonia.org/golgi"
	G "gorgonia.org/gorgonia"
	"gorgonia.org/tensor"
)

// myLayer is a layer with additional support for transformation for shapes.
//
// One may of course do this with a ComposeSeq(Reshape, FC), but this is just for demonstration purposes
type myLayer struct {
	// name is in FC
	FC

	// BE CAREFUL WITH EMBEDDINGS

	// size is in FC and in myLayer
	size int
}

// Model, Name, Type, Shape and Describe are all from the embedded FC

func (l *myLayer) Fwd(a G.Input) G.Result {
	if err := G.CheckOne(a); err != nil {
		return G.Err(errors.Wrapf(err, "Fwd of myLayer %v", l.FC.Name()))
	}
	x := a.Node()
	xShape := x.Shape()

	switch xShape.Dims() {
	case 0, 1:
		return G.Err(errors.Errorf("Unable to handle x of %v", xShape))
	case 2:
		return l.FC.Fwd(x)
	case 3, 4:
		return G.Err(errors.Errorf("NYI"))

	}
	panic("UNIMPLEMENTED")
}

func ConsMyLayer(x G.Input, opts ...ConsOpt) (retVal Layer, err error) {
	l := new(myLayer)
	for _, opt := range opts {
		var o Layer
		var ok bool
		if o, err = opt(l); err != nil {
			return nil, err
		}
		if l, ok = o.(*myLayer); !ok {
			return nil, errors.Errorf("Construction Option returned non *myLayer. Got %T instead", o)
		}
	}
	if err = l.Init(x.(*G.Node)); err != nil {
		return nil, err
	}
	return l, nil
}

func main() {
	of := tensor.Float64
	g := G.NewGraph()
	x := G.NewTensor(g, of, 4, G.WithName("X"), G.WithShape(100, 1, 28, 28), G.WithInit(G.GlorotU(1)))
	layer, err := ConsMyLayer(x, WithName("EXT"), WithSize(100))
	if err != nil {
		fmt.Printf("Uh oh. Error happened when constructing *myLayer: %v\n", err)
	}
	l, _ := layer.(*myLayer)
	fmt.Printf("Name:  %q\n", l.Name())
	fmt.Printf("Model: %v\n", l.Model())
	fmt.Printf("BE CAREFUL\n======\nl.size is %v. But the models shapes are correct as follows:\n", l.size)
	for _, n := range l.Model() {
		fmt.Printf("\t%v - %v\n", n.Name(), n.Shape())
	}

}

Output:

Name:  "EXT"
Model: [EXT_W, EXT_B]
BE CAREFUL
======
l.size is 0. But the models shapes are correct as follows:
	EXT_W - (1, 100)
	EXT_B - (100, 100)

Index

Examples

Constants

This section is empty.

Variables

This section is empty.

Functions

func BroadcastAdd 

func BroadcastAdd(a, b *G.Node, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastAdd performs a add. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastEq 

func BroadcastEq(a, b *G.Node, retSame bool, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastEq performs a eq. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastGt 

func BroadcastGt(a, b *G.Node, retSame bool, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastGt performs a gt. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastGte 

func BroadcastGte(a, b *G.Node, retSame bool, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastGte performs a gte. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastHadamardDiv 

func BroadcastHadamardDiv(a, b *G.Node, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastHadamardDiv performs a hadamarddiv. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastHadamardProd 

func BroadcastHadamardProd(a, b *G.Node, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastHadamardProd performs a hadamardprod. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastLt 

func BroadcastLt(a, b *G.Node, retSame bool, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastLt performs a lt. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastLte 

func BroadcastLte(a, b *G.Node, retSame bool, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastLte performs a lte. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastNe 

func BroadcastNe(a, b *G.Node, retSame bool, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastNe performs a ne. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastPow 

func BroadcastPow(a, b *G.Node, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastPow performs a pow. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func BroadcastSub 

func BroadcastSub(a, b *G.Node, leftPattern, rightPattern []byte) (*G.Node, error)

BroadcastSub performs a sub. The operation is precomposed with a broadcast such that the shapes matches before operations commence.

func ExtractMetadata 

func ExtractMetadata(opts ...ConsOpt) (retVal Metadata, unused []ConsOpt, err error)

ExtractMetadata extracts common metadata from a list of ConsOpts. It returns the metadata. Any unused ConsOpt is also returned. This allows users to selectively use the metadata and/or ConsOpt options

func GeLUFn 

func GeLUFn(a *G.Node) (*G.Node, error)

GeLUFn is an activation function. See https://arxiv.org/abs/1606.08415.

func RMS 

func RMS(yHat, y G.Input) (retVal *G.Node, err error)

RMS represents a root mean equare error The root-mean-square deviation (RMSD) or root-mean-square error (RMSE) is a frequently used measure of the differences between values (sample or population values) predicted by a model or an estimator and the values observed.

func SoftMaxFn 

func SoftMaxFn(a *G.Node) (*G.Node, error)

SoftMaxFn implements softmax without axis

Types

type Activation 

type Activation int

Activation represents the types of ActivationFunctions that Golgi understands.

The Activation type is useful as it allows the models to be serialized (you cannot serialize ActivationFunction). Use ActivationMap() to get the relevant ActivationFunction. 

const (
	Identity Activation = iota
	Sigmoid
	Tanh
	ReLU
	GeLU
	LeakyReLU
	ELU
	Cube
	SoftMax
)

type ActivationFunction 

type ActivationFunction func(*G.Node) (*G.Node, error)

ActivationFunction represents an activation function Note: This may become an interface once we've worked through all the linter errors

func ActivationMap 

func ActivationMap(a Activation) ActivationFunction

ActivationMap is a map from Activation to ActivationFunction. The mapping function is finite. If an invalid Activation is passed in, nil will be returned.

type ByNamer 

type ByNamer interface {
	ByName(name string) Term
}

ByNamer is any type that allows a name to be found and returned.

If a name is not found, `nil` is to be returned

type Composition 

type Composition struct {
	// contains filtered or unexported fields
}

Composition (∘) represents a composition of functions.

The semantics of ∘(a, b)(x) is b(a(x)).

func Compose 

func Compose(a, b Term) (retVal *Composition)

Compose creates a composition of terms.

func ComposeSeq 

func ComposeSeq(layers ...Term) (retVal *Composition, err error)

ComposeSeq creates a composition with the inputs written in left to right order

The equivalent in F# is |>. The equivalent in Haskell is (flip (.))

func (*Composition) ByName 

func (l *Composition) ByName(name string) Term

ByName returns a Term by name

func (*Composition) Describe 

func (l *Composition) Describe()

Describe will describe a composition

func (*Composition) FLOPs 

func (l *Composition) FLOPs() (retVal int)

func (*Composition) Fwd 

func (l *Composition) Fwd(a G.Input) (output G.Result)

Fwd runs the equation forwards

func (*Composition) Graph 

func (l *Composition) Graph() *G.ExprGraph

func (*Composition) Model 

func (l *Composition) Model() (retVal G.Nodes)

Model will return the gorgonia.Nodes associated with this composition

func (*Composition) Name 

func (l *Composition) Name() string

Name will return the name of the composition

func (*Composition) Runners 

func (l *Composition) Runners() []Runner

type ConsOpt 

type ConsOpt func(Layer) (Layer, error)

ConsOpt is a construction option for layers

func AsBatched 

func AsBatched(batched bool) ConsOpt

AsBatched defines a layer that performs batched operation or not. By default most layers in this package are batched.

func AsRunner 

func AsRunner() ConsOpt

func ComputeFLOPs 

func ComputeFLOPs(toCompute bool) ConsOpt

ComputeFLOPs tells the layer to also compute FLOPS as the input is forwarded through it.

func Of 

func Of(dt tensor.Dtype) ConsOpt

Of sets the type of the internal tensor

func ToShape 

func ToShape(shp ...int) ConsOpt

ToShape is a ConsOpt for Reshape only.

func WithActivation 

func WithActivation(act ActivationFunction) ConsOpt

WithActivation sets the activation function of a layer

func WithBatchSize 

func WithBatchSize(bs int) ConsOpt

WithBatchSize creates a layer with a given batch size.

func WithBias 

func WithBias(withbias bool) ConsOpt

WithBias defines a layer with or without a bias

func WithClasses 

func WithClasses(classes int) ConsOpt

WithClasses is a construction option that specifies how many classes are there in the embedding layer.

func WithConst 

func WithConst(c *G.Node) ConsOpt

WithConst is a construction option for the skip Layer

func WithDilation 

func WithDilation(s []int) ConsOpt

WithDilation sets the dilation for convolution layers

func WithEps 

func WithEps(eps float64) ConsOpt

WithEps is a ConsOpt for constructing Layer Norms only.

func WithKernelShape 

func WithKernelShape(s tensor.Shape) ConsOpt

WithKernelShape sets the kernel shape for convolution layers (Conv, MaxPool)

func WithName 

func WithName(name string) ConsOpt

WithName creates a layer that is named.

If the layer is unnameable (i.e. trivial layers), then there is no effect.

func WithOneHotInput 

func WithOneHotInput() ConsOpt

WithOneHotInput is a construction option for a *Embedding that specifiess the behaviour to accept one-hot-vector/matrix as input.

func WithPad 

func WithPad(p []int) ConsOpt

WithPad sets the pad for convolution layers (Conv, MaxPool)

func WithProbability 

func WithProbability(prob float64) ConsOpt

WithProbability is a ConsOpt for Dropout only.

func WithSize 

func WithSize(size ...int) ConsOpt

WithSize automatically creates a layer of the given sizes.

func WithStride 

func WithStride(s []int) ConsOpt

WithStride sets the stride for convolution layers (Conv, MaxPool)

func WithWB 

func WithWB(w, b *G.Node) ConsOpt

WithWB is a FC specific construction option used to initialize a FC.

func WithWeights 

func WithWeights(w *G.Node) ConsOpt

WithWeights constructs a layer with the given weights.

type Conv 

type Conv struct {
	// contains filtered or unexported fields
}

Conv represents a convolution layer

func NewConv 

func NewConv(opts ...ConsOpt) (*Conv, error)

func (*Conv) Describe 

func (l *Conv) Describe()

Describe will describe a convolution layer

func (*Conv) FLOPs 

func (l *Conv) FLOPs() int

func (*Conv) Fwd 

func (l *Conv) Fwd(x gorgonia.Input) gorgonia.Result

Fwd runs the equation forwards

func (*Conv) Init 

func (l *Conv) Init(xs ...*gorgonia.Node) (err error)

Init will initialize the fully connected layer

func (*Conv) Model 

func (l *Conv) Model() gorgonia.Nodes

Model will return the gorgonia.Nodes associated with this convolution layer

func (*Conv) Name 

func (l *Conv) Name() string

Name will return the name of the convolution layer

func (*Conv) SetActivationFn 

func (l *Conv) SetActivationFn(act ActivationFunction) error

SetActivationFn sets the activation function of the layer

func (*Conv) SetDropout 

func (l *Conv) SetDropout(d float64) error

SetDropout sets the dropout of the layer

func (*Conv) SetName 

func (l *Conv) SetName(n string) error

SetName sets the name of the layer

func (*Conv) SetSize 

func (l *Conv) SetSize(s ...int) error

SetSize sets the size of the layer

func (*Conv) Shape 

func (l *Conv) Shape() tensor.Shape

Shape will return the tensor.Shape of the convolution layer

func (*Conv) Type 

func (l *Conv) Type() hm.Type

Type will return the hm.Type of the convolution layer

type Data 

type Data interface {
	Make(g *G.ExprGraph, name string) (Layer, error)
}

Data represents a layer's data. It is able to reconstruct a Layer and populating it.

type Embedding 

type Embedding struct {
	// contains filtered or unexported fields
}

Embedding is a layer that represents an embedding layer.

An embedding layer is essentially a matrix of the shape (classes, dimensions). While the Embedding layer can be done by means of using FC, this provides some ease of use.

Specifically the Embedding layer supports forwarding of an input that is a slice of classes.

Let us look at a word-based example, consider the vocab size to be the number of classes. The classical word embedding then is simply a (vocab, dims) matrix. Let's set the dims to be 50. For simplicity, let's set the vocab to 10. So that the embedding matrix W is a (10, 50) matrix. 

W := ⸢w1_1  ...  w1_50⸣
             ⋮
     ⸤w10_1 ... w10_50⸥

To select a word vector, we simply slice the matrix. For example, to get the vector of word ID 2, we slice W[2]. This gives us a 50-dimension vector: 

W[2] = [w2_1 ... w2_50]

We can equally do this by multiplying the matrix with a one-hot vector. A vector O given as 

O := [0 0 1 0 0 0 0 0 0 0]

when multiplied against W, will yield the same result as W[2].

The usual way of selecting from a embedding matrix with a one-hot vector is quite cumbersome. This struct makes it easy.

You can pass in a *tensor.Dense of qol.Class: 

wv := tensor.New(tensor.WithBacking([]qol.Class{4, 10, 0, 0, 0, 0, 0, 0,0,0}))
words := gorgonia.NewVector(g, gorgonia.WithShape(10), gorgonia.WithValue(wv))
layer.Fwd(words)

The Embedding layer's Fwd function will automatically transform a slice of classes into a one-hot matrix to be multiplied with.

func NewEmbedding 

func NewEmbedding(opts ...ConsOpt) *Embedding

NewEmbedding creates a new embedding layer.

func (*Embedding) Describe 

func (l *Embedding) Describe()

func (*Embedding) Fwd 

func (l *Embedding) Fwd(a G.Input) G.Result

func (*Embedding) Graph 

func (l *Embedding) Graph() *G.ExprGraph

Graph returns the underlying computation graph. Embedding implements Grapher.

func (*Embedding) Init 

func (l *Embedding) Init(xs ...*G.Node) (err error)

Init initializes the embedding layer.

func (*Embedding) IsInitialized 

func (l *Embedding) IsInitialized() bool

func (*Embedding) Model 

func (l *Embedding) Model() G.Nodes

Model returns the gorgonia.Nodes associated with the embedding layer.

func (*Embedding) Name 

func (l *Embedding) Name() string

func (*Embedding) Run 

func (l *Embedding) Run(input G.Input) (err error)

Run is a function that sets the internal one hot vector/matrix

func (*Embedding) Runners 

func (l *Embedding) Runners() []Runner

Runners returns the embedding itself

type Env 

type Env struct {
	// contains filtered or unexported fields
}

Env is a linked list representing an environment. Within the documentation, an environment is written as such: 

e := (x ↦ X)

`x` is the name while `X` is the *gorgonia.Node

A longer environment may look like this: 

e2 := (x ↦ X :: y ↦ Y)
                ^

Here, e2 is pointing to the *Env that contains (y ↦ Y).

When talking about Envs in general, it will often be written as a meta variable σ.

func NewEnv 

func NewEnv(name string, node *G.Node) *Env

NewEnv creates a new Env.

func (*Env) ByName 

func (e *Env) ByName(name string) (*G.Node, *Env)

ByName returns the first node that matches the given name. It also returns the parent

For example, if we have an Env as follows: 

e := (x ↦ X1 :: w ↦ W :: x ↦ X2)
                         ^

The caret indicates the pointer of *Env. Now, if e.ByName("x") is called, then the result returned will be X2 and (x ↦ X1 :: w ↦ W)

func (*Env) Extend 

func (e *Env) Extend(name string, node *G.Node) *Env

Extend allows users to extend the environment.

Given an environment as follows: 

e := (x ↦ X)

if `e.Extend(y, Y)` is called, the following is returned 

e2 := (x ↦ X :: y ↦ Y)
                ^

The pointer will be pointing to the *Env starting at y

func (*Env) HintedModel 

func (e *Env) HintedModel(hint int) G.Nodes

HintedModel will return the gorgonia.Nodes hinted associated with this environment

func (*Env) Model 

func (e *Env) Model() G.Nodes

Model will return the gorgonia.Nodes associated with this environment

func (*Env) Name 

func (e *Env) Name() string

Name will return the name of the composition

type FC 

type FC struct {
	// contains filtered or unexported fields
}

FC represents a fully connected layer

If batched is set to true, then the first dimension is assumed to be the batch dimension

func MakeFC 

func MakeFC(w, b *G.Node, act ActivationFunction, name string, batched bool) FC

MakeFC creates a FC with the given parameters

func NewFC 

func NewFC(opts ...ConsOpt) *FC

NewFC is the usual way to create a FC

func (*FC) ByName 

func (l *FC) ByName(name string) Term

ByName returns a Term by name

func (*FC) Describe 

func (l *FC) Describe()

Describe will describe a fully connected layer

func (*FC) FLOPs 

func (l *FC) FLOPs() int

func (*FC) Fwd 

func (l *FC) Fwd(a G.Input) G.Result

Fwd runs the equation forwards

func (*FC) Graph 

func (l *FC) Graph() *G.ExprGraph

func (*FC) Init 

func (l *FC) Init(xs ...*G.Node) (err error)

Init will initialize the fully connected layer

func (*FC) IsInitialized 

func (l *FC) IsInitialized() bool

IsInitialized returns true if it has been initialized. This allows lazy initialization to be supported

func (*FC) Model 

func (l *FC) Model() G.Nodes

Model will return the gorgonia.Nodes associated with this fully connected layer

func (*FC) Name 

func (l *FC) Name() string

Name will return the name of the fully connected layer

func (*FC) SetAct 

func (l *FC) SetAct(act ActivationFunction) error

SetAct will set an activiation function of a fully connected layer

func (*FC) SetComputeFLOPs 

func (l *FC) SetComputeFLOPs(toCompute bool) error

SetComputeFLOPs will set the `computeFLOPs` param. If true then the FLOPs will be computed when the input is forwarded.

func (*FC) SetName 

func (l *FC) SetName(a string) error

SetName will set the name of a fully connected layer

func (*FC) SetSize 

func (l *FC) SetSize(a int) error

SetSize will set the size of a fully connected layer

func (*FC) Shape 

func (l *FC) Shape() tensor.Shape

Shape will return the tensor.Shape of the fully connected layer

func (*FC) Type 

func (l *FC) Type() hm.Type

Type will return the hm.Type of the fully connected layer

type Grapher 

type Grapher interface {
	Graph() *G.ExprGraph
}

Grapher is any type that can return the underlying computational graph

type I 

type I struct{}

func (I) Name 

func (i I) Name() string

type Join 

type Join struct {
	Composition
	// contains filtered or unexported fields
}

Join joins are generalized compositions.

func Add 

func Add(a, b Term) *Join

Add adds the results of two layers/terms.

func HadamardProd 

func HadamardProd(a, b Term) *Join

HadamardProd performs a elementwise multiplicatoin on the results of two layers/terms.

func (*Join) Fwd 

func (l *Join) Fwd(a G.Input) (output G.Result)

Fwd runs the equation forwards.

type LSTM 

type LSTM struct {
	// contains filtered or unexported fields
}

LSTM represents an LSTM RNN

func FromLSTMData 

func FromLSTMData(g *G.ExprGraph, layer *LSTMData, name string) *LSTM

FromLSTMData will initialize a new LSTM model

func (*LSTM) Describe 

func (l *LSTM) Describe()

Describe will describe a LSTM

func (*LSTM) Fwd 

func (l *LSTM) Fwd(x G.Input) G.Result

Fwd runs the equation forwards.

While a *LSTM can take any gorgonia.Input as an input, it returns a gorgonia.Result, of which the concrete type is a lstimIO.

The lstmIO type is not exported. Instead, to query the *Node of the gorgonia.Input or gorgonia.Result, use the Nodes() method.

The Result will always be organized as such: [previousHidden, previousCell]

e.g. 

out := lstm.Fwd(x)
outNodes := out.Nodes()
prevHidden := outNodes[0]
prevCell := outNodes[1]

func (*LSTM) Init 

func (l *LSTM) Init(xs ...*G.Node) (err error)

Init will initialize the fully connected layer

func (*LSTM) Model 

func (l *LSTM) Model() G.Nodes

Model will return the gorgonia.Nodes associated with this LSTM

func (*LSTM) Name 

func (l *LSTM) Name() string

Name will return the name of the LSTM

func (*LSTM) SetName 

func (l *LSTM) SetName(a string) error

SetName will set the name of a fully connected layer

func (*LSTM) Shape 

func (l *LSTM) Shape() tensor.Shape

Shape will return the tensor.Shape of the LSTM

func (*LSTM) Type 

func (l *LSTM) Type() hm.Type

Type will return the hm.Type of the LSTM

type LSTMData 

type LSTMData struct {
	// contains filtered or unexported fields
}

LSTMData represents a basic LSTM layer

func (*LSTMData) Make 

func (l *LSTMData) Make(g *G.ExprGraph, name string) (Layer, error)

type Layer 

type Layer interface {
	// σ - The weights are the "free variables" of a function
	Model() G.Nodes

	// Fwd represents the forward application of inputs
	// x.t
	Fwd(x G.Input) G.Result

	Term

	// Describe returns the protobuf definition of a Layer that conforms to the ONNX standard
	Describe() // some protobuf things TODO
}

Layer represents a neural network layer. λ

func ConsConv 

func ConsConv(in gorgonia.Input, opts ...ConsOpt) (retVal Layer, err error)

ConsConv is a Conv construction function. It takes a gorgonia.Input that has a *gorgonia.Node. Defaults: 

activation function: Rectify
kernel shape: (5,5)
pad: (1,1)
stride: (1,1)
dilation: (1,1)

func ConsDropout 

func ConsDropout(_ G.Input, opts ...ConsOpt) (l Layer, err error)

ConsDropout creates a dropout layer. It ignores the `x` input

func ConsEmbedding 

func ConsEmbedding(in G.Input, opts ...ConsOpt) (retVal Layer, err error)

ConsEmbedding is a construction function to construct a *Embedding. This is typically used in a L() construction manner.

func ConsFC 

func ConsFC(in G.Input, opts ...ConsOpt) (retVal Layer, err error)

ConsFC is a FC construction function. It takes a gorgonia.Input that has a *gorgonia.Node.

func ConsLSTM 

func ConsLSTM(in G.Input, opts ...ConsOpt) (retVal Layer, err error)

ConsLSTM is a LSTM construction function. It takes a gorgonia.Input that has a *gorgonia.Node.

func ConsLayerNorm 

func ConsLayerNorm(in G.Input, opts ...ConsOpt) (retVal Layer, err error)

ConsLayerNorm is a construction function for a layer normalization layer. `in` has to be at least a *gorgonia.Node

func ConsMaxPool 

func ConsMaxPool(in gorgonia.Input, opts ...ConsOpt) (retVal Layer, err error)

ConsMaxPool is a MaxPool construction function. It takes a gorgonia.Input that has a *gorgonia.Node. Defaults: 

kernel shape: (2,2)
pad: (0,0)
stride: (2,2)

func ConsReshape 

func ConsReshape(_ G.Input, opts ...ConsOpt) (l Layer, err error)

ConsReshape is a construction function for a reshaping layer. It ignores the `x` input.

func ConsSkip 

func ConsSkip(_ G.Input, opts ...ConsOpt) (retVal Layer, err error)

func MakeLayerNorm 

func MakeLayerNorm(opts ...ConsOpt) Layer

func NewLayerNorm 

func NewLayerNorm(opts ...ConsOpt) Layer

NewLayerNorm creates a layer-normalization layer. It does not initialize the layer.

func Redefine 

func Redefine(l Layer, opts ...ConsOpt) (retVal Layer, err error)

Redefine redefines a layer with the given construction options. This is useful for re-initializing layers

type LayerCons 

type LayerCons func(input G.Input, opts ...ConsOpt) (Layer, error)

LayerCons makes a layer

type MaxPool 

type MaxPool struct {
	// contains filtered or unexported fields
}

MaxPool represents a MaxPoololution layer

func NewMaxPool 

func NewMaxPool(opts ...ConsOpt) (*MaxPool, error)

func (*MaxPool) Describe 

func (l *MaxPool) Describe()

Describe will describe a MaxPoololution layer

func (*MaxPool) FLOPs 

func (l *MaxPool) FLOPs() int

func (*MaxPool) Fwd 

func (l *MaxPool) Fwd(x gorgonia.Input) gorgonia.Result

Fwd runs the equation forwards

func (*MaxPool) Init 

func (l *MaxPool) Init(xs ...*gorgonia.Node) (err error)

Init will initialize the fully connected layer

func (*MaxPool) Model 

func (l *MaxPool) Model() gorgonia.Nodes

Model will return the gorgonia.Nodes associated with this MaxPoololution layer

func (*MaxPool) Name 

func (l *MaxPool) Name() string

Name will return the name of the MaxPoololution layer

func (*MaxPool) SetComputeFLOPs 

func (l *MaxPool) SetComputeFLOPs(toCompute bool) error

func (*MaxPool) SetDropout 

func (l *MaxPool) SetDropout(d float64) error

SetDropout sets the dropout of the layer

func (*MaxPool) SetName 

func (l *MaxPool) SetName(n string) error

SetName sets the name of the layer

func (*MaxPool) SetSize 

func (l *MaxPool) SetSize(s int) error

SetSize sets the size of the layer

func (*MaxPool) Type 

func (l *MaxPool) Type() hm.Type

Type will return the hm.Type of the MaxPoololution layer

type Metadata 

type Metadata struct {
	Size int

	ActivationFn ActivationFunction
	// contains filtered or unexported fields
}

Metadata is not a real Layer. Its main aims is to extract metadata such as name or size from ConsOpts. This is useful in cases where the metadata needs to be composed as well. Note that the fields may end up being all empty.

func (*Metadata) Describe 

func (m *Metadata) Describe()

Describe will describe a metadata

func (*Metadata) Fwd 

func (m *Metadata) Fwd(x G.Input) G.Result

Fwd runs the equation forwards

func (*Metadata) Model 

func (m *Metadata) Model() G.Nodes

Model will return the gorgonia.Nodes associated with this metadata

func (*Metadata) Name 

func (m *Metadata) Name() string

Name returns the name. Conveniently, this makes *Metadata fulfil the Layer interface, so we may use it to extract the desired metadata. Unfortunately this also means that the name is not an exported field. A little inconsistency there.

func (*Metadata) PassThru 

func (m *Metadata) PassThru()

PassThru represents a passthru function

func (*Metadata) SetActivationFn 

func (m *Metadata) SetActivationFn(act ActivationFunction) error

SetActivationFn allows the metadata to store activation function.

func (*Metadata) SetName 

func (m *Metadata) SetName(name string) error

SetName allows for names to be set by a ConsOpt

func (*Metadata) SetSize 

func (m *Metadata) SetSize(size int) error

SetSize allows for the metadata struct to be filled by a ConsOpt

func (*Metadata) Shape 

func (m *Metadata) Shape() tensor.Shape

Shape will return the tensor.Shape of the metadata

func (*Metadata) Type 

func (m *Metadata) Type() hm.Type

Type will return the hm.Type of the metadata

type Name 

type Name string

Name is a variable by name

func (Name) Name 

func (n Name) Name() string

Name will return itself as a string

type Pass 

type Pass interface {
	PassThru()
}

Pass represents layers that are pass-thru - layers that have external effects that do not affect the expression graph.

type ReshapeFn 

type ReshapeFn func(s tensor.Shape) tensor.Shape

ReshapeFn defines a function to reshape a tensor

type Runner 

type Runner interface {
	Run(a G.Input) error

	// Runners should return themselves
	Runnerser
}

Runner is a kind of layer that requires outside-the-graph manipulation.

type Runnerser 

type Runnerser interface {
	Runners() []Runner
}

Runnerser is any kind of layer that gets a slice of Runners.

For simplicity, all Runners should implement Runnerser

type Term 

type Term interface {
	Name() string
}

Term represents a term that can be used in Golgi

func Apply 

func Apply(a, b Term) (Term, error)

Apply will apply two terms and return the resulting term Apply(a, b) has the semantics of a(b).

func L 

func L(cons LayerCons, opts ...ConsOpt) Term

L is a thunk of creation function

func Trace 

func Trace(name, format, errFormat string, logger *log.Logger) Term

Trace creates a layer for debugging composed layers

The format string adds four things: "%s %v (%p) %v" - name (of trace), x, x, x.Shape()

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