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mlpack/src/mlpack/methods/ann/layer/base_layer.hpp
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/**
* @file base_layer.hpp
* @author Marcus Edel
*
* Definition of the BaseLayer class, which attaches various functions to the
* embedding layer.
*
* mlpack is free software; you may redistribute it and/or modify it under the
* terms of the 3-clause BSD license. You should have received a copy of the
* 3-clause BSD license along with mlpack. If not, see
* http://www.opensource.org/licenses/BSD-3-Clause for more information.
*/
#ifndef MLPACK_METHODS_ANN_LAYER_BASE_LAYER_HPP
#define MLPACK_METHODS_ANN_LAYER_BASE_LAYER_HPP
#include <mlpack/prereqs.hpp>
#include <mlpack/methods/ann/activation_functions/logistic_function.hpp>
#include <mlpack/methods/ann/activation_functions/identity_function.hpp>
#include <mlpack/methods/ann/activation_functions/rectifier_function.hpp>
#include <mlpack/methods/ann/activation_functions/tanh_function.hpp>
#include <mlpack/methods/ann/activation_functions/softplus_function.hpp>
#include <mlpack/methods/ann/activation_functions/hard_sigmoid_function.hpp>
#include <mlpack/methods/ann/activation_functions/swish_function.hpp>
#include <mlpack/methods/ann/activation_functions/mish_function.hpp>
#include <mlpack/methods/ann/activation_functions/lisht_function.hpp>
#include <mlpack/methods/ann/activation_functions/gelu_function.hpp>
namespace mlpack {
namespace ann /** Artificial Neural Network. */ {
/**
* Implementation of the base layer. The base layer works as a metaclass which
* attaches various functions to the embedding layer.
*
* A few convenience typedefs are given:
*
* - SigmoidLayer
* - IdentityLayer
* - ReLULayer
* - TanHLayer
*
* @tparam ActivationFunction Activation function used for the embedding layer.
* @tparam InputDataType Type of the input data (arma::colvec, arma::mat,
* arma::sp_mat or arma::cube).
* @tparam OutputDataType Type of the output data (arma::colvec, arma::mat,
* arma::sp_mat or arma::cube).
*/
template <
class ActivationFunction = LogisticFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
class BaseLayer
{
public:
/**
* Create the BaseLayer object.
*/
BaseLayer()
{
// Nothing to do here.
}
/**
* Ordinary feed forward pass of a neural network, evaluating the function
* f(x) by propagating the activity forward through f.
*
* @param input Input data used for evaluating the specified function.
* @param output Resulting output activation.
*/
template<typename InputType, typename OutputType>
void Forward(const InputType&& input, OutputType&& output)
{
ActivationFunction::Fn(input, output);
}
/**
* Ordinary feed backward pass of a neural network, calculating the function
* f(x) by propagating x backwards trough f. Using the results from the feed
* forward pass.
*
* @param input The propagated input activation.
* @param gy The backpropagated error.
* @param g The calculated gradient.
*/
template<typename eT>
void Backward(const arma::Mat<eT>&& input,
arma::Mat<eT>&& gy,
arma::Mat<eT>&& g)
{
arma::Mat<eT> derivative;
ActivationFunction::Deriv(input, derivative);
g = gy % derivative;
}
//! Get the output parameter.
OutputDataType const& OutputParameter() const { return outputParameter; }
//! Modify the output parameter.
OutputDataType& OutputParameter() { return outputParameter; }
//! Get the delta.
OutputDataType const& Delta() const { return delta; }
//! Modify the delta.
OutputDataType& Delta() { return delta; }
/**
* Serialize the layer.
*/
template<typename Archive>
void serialize(Archive& /* ar */, const unsigned int /* version */)
{
/* Nothing to do here */
}
private:
//! Locally-stored delta object.
OutputDataType delta;
//! Locally-stored output parameter object.
OutputDataType outputParameter;
}; // class BaseLayer
// Convenience typedefs.
/**
* Standard Sigmoid-Layer using the logistic activation function.
*/
template <
class ActivationFunction = LogisticFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using SigmoidLayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
/**
* Standard Identity-Layer using the identity activation function.
*/
template <
class ActivationFunction = IdentityFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using IdentityLayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
/**
* Standard rectified linear unit non-linearity layer.
*/
template <
class ActivationFunction = RectifierFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using ReLULayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
/**
* Standard hyperbolic tangent layer.
*/
template <
class ActivationFunction = TanhFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using TanHLayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
/**
* Standard Softplus-Layer using the Softplus activation function.
*/
template <
class ActivationFunction = SoftplusFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using SoftPlusLayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
/**
* Standard HardSigmoid-Layer using the HardSigmoid activation function.
*/
template <
class ActivationFunction = HardSigmoidFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using HardSigmoidLayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
/**
* Standard Swish-Layer using the Swish activation function.
*/
template <
class ActivationFunction = SwishFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using SwishFunctionLayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
/**
* Standard Mish-Layer using the Mish activation function.
*/
template <
class ActivationFunction = MishFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using MishFunctionLayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
/**
* Standard LiSHT-Layer using the LiSHT activation function.
*/
template <
class ActivationFunction = LiSHTFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using LiSHTFunctionLayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
/**
* Standard GELU-Layer using the GELU activation function.
*/
template <
class ActivationFunction = GELUFunction,
typename InputDataType = arma::mat,
typename OutputDataType = arma::mat
>
using GELUFunctionLayer = BaseLayer<
ActivationFunction, InputDataType, OutputDataType>;
} // namespace ann
} // namespace mlpack
#endif