Layer Class Reference

Represents a single layer of a neural network. More...

#include <layer.h>

Public Member Functions
	Layer (size_t inSize, size_t outSize, std::string activation, DataLocation location)
	Construct a new layer. More...
	~Layer ()
	The destructor of the layer object.
sTensor	forward (const sTensor &batch) const
	Forward one batch of data through the layer. More...
void	applyGradients (size_t batchSize, float learningRate=0.01)
	Apply the computed gradients. More...

Public Attributes
DataLocation	location
	The location of the layer. More...
size_t	outSize
	The output size of the layer. More...
size_t	inSize
	The input size to the layer. More...
std::string	activation
	The activation function. More...
sTensor	weights
	The weights of the layer. Stored as a matrix.
sTensor	biases
	The biases of the layer. Stored as a vector.

Detailed Description

Represents a single layer of a neural network.

Constructor & Destructor Documentation

Layer()

Layer::Layer	(	size_t	inSize,
		size_t	outSize,
		std::string	activation,
		DataLocation	location
	)

Construct a new layer.

Also allocates space that will be used during computation. This allows for in-place computation, which avoids allocating/freeing memory during training.

Parameters

inSize	The input size to the layer.
outSize	The output size of the layer (equal to the number of neurons).
activation	The activation function that should be used.
location	The location of the layer. See Layer::location.

Member Function Documentation

applyGradients()

void Layer::applyGradients	(	size_t	batchSize,
		float	learningRate = 0.01
	)

Apply the computed gradients.

The method should be called only when all the gradients have been computed for all the layers in the network.

Parameters

batchSize	The size of the batch.
learningRate	The learning rate of the model.

forward()

sTensor Layer::forward

(

const sTensor &

batch

)

const

Forward one batch of data through the layer.

This includes allocating space that could not be allocated in the constructor as it depends on the batch size. The additional data will only be allocated if batch size changes. This means, if all batches are of the same size, the data will not be allocated again. This is performed in the Layer::allocate() method.

Parameters

batch

The batch that should be propagated.

Member Data Documentation

activation

std::string Layer::activation

The activation function.

Pointer to the activation function object. Can be LinearActivation, ReLUActivation or SigmoidActivation.

inSize

size_t Layer::inSize

The input size to the layer.

Equal to the number of neurons in the previous layer, or the size of the input in the case of the input layer.

location

DataLocation Layer::location

The location of the layer.

Specifies the location of all the data used by the layer. See DataLocation for more info.

outSize

size_t Layer::outSize

The output size of the layer.

Equal to the number of neurons in the layer.

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The documentation for this class was generated from the following files:

• include/layer.h
• src/ann/layer.cpp