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