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140 lines
5.0 KiB
C++
140 lines
5.0 KiB
C++
//
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// MultiOutputLayer.cpp
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//
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// Created by Marc Melikyan on 11/4/20.
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//
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#include "multi_output_layer_old.h"
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#include "../lin_alg/lin_alg_old.h"
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#include "../utilities/utilities.h"
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#include <iostream>
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#include <random>
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MLPPOldMultiOutputLayer::MLPPOldMultiOutputLayer(int p_n_output, int p_n_hidden, std::string p_activation, std::string p_cost, std::vector<std::vector<real_t>> p_input, std::string p_weightInit, std::string p_reg, real_t p_lambda, real_t p_alpha) {
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n_output = p_n_output;
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n_hidden = p_n_hidden;
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activation = p_activation;
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cost = p_cost;
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input = p_input;
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weightInit = p_weightInit;
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reg = p_reg;
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lambda = p_lambda;
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alpha = p_alpha;
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weights = MLPPUtilities::weightInitialization(n_hidden, n_output, weightInit);
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bias = MLPPUtilities::biasInitialization(n_output);
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activation_map["Linear"] = &MLPPActivationOld::linear;
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activationTest_map["Linear"] = &MLPPActivationOld::linear;
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activation_map["Sigmoid"] = &MLPPActivationOld::sigmoid;
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activationTest_map["Sigmoid"] = &MLPPActivationOld::sigmoid;
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activation_map["Softmax"] = &MLPPActivationOld::softmax;
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activationTest_map["Softmax"] = &MLPPActivationOld::softmax;
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activation_map["Swish"] = &MLPPActivationOld::swish;
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activationTest_map["Swish"] = &MLPPActivationOld::swish;
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activation_map["Mish"] = &MLPPActivationOld::mish;
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activationTest_map["Mish"] = &MLPPActivationOld::mish;
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activation_map["SinC"] = &MLPPActivationOld::sinc;
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activationTest_map["SinC"] = &MLPPActivationOld::sinc;
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activation_map["Softplus"] = &MLPPActivationOld::softplus;
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activationTest_map["Softplus"] = &MLPPActivationOld::softplus;
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activation_map["Softsign"] = &MLPPActivationOld::softsign;
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activationTest_map["Softsign"] = &MLPPActivationOld::softsign;
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activation_map["CLogLog"] = &MLPPActivationOld::cloglog;
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activationTest_map["CLogLog"] = &MLPPActivationOld::cloglog;
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activation_map["Logit"] = &MLPPActivationOld::logit;
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activationTest_map["Logit"] = &MLPPActivationOld::logit;
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activation_map["GaussianCDF"] = &MLPPActivationOld::gaussianCDF;
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activationTest_map["GaussianCDF"] = &MLPPActivationOld::gaussianCDF;
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activation_map["RELU"] = &MLPPActivationOld::RELU;
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activationTest_map["RELU"] = &MLPPActivationOld::RELU;
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activation_map["GELU"] = &MLPPActivationOld::GELU;
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activationTest_map["GELU"] = &MLPPActivationOld::GELU;
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activation_map["Sign"] = &MLPPActivationOld::sign;
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activationTest_map["Sign"] = &MLPPActivationOld::sign;
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activation_map["UnitStep"] = &MLPPActivationOld::unitStep;
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activationTest_map["UnitStep"] = &MLPPActivationOld::unitStep;
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activation_map["Sinh"] = &MLPPActivationOld::sinh;
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activationTest_map["Sinh"] = &MLPPActivationOld::sinh;
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activation_map["Cosh"] = &MLPPActivationOld::cosh;
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activationTest_map["Cosh"] = &MLPPActivationOld::cosh;
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activation_map["Tanh"] = &MLPPActivationOld::tanh;
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activationTest_map["Tanh"] = &MLPPActivationOld::tanh;
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activation_map["Csch"] = &MLPPActivationOld::csch;
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activationTest_map["Csch"] = &MLPPActivationOld::csch;
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activation_map["Sech"] = &MLPPActivationOld::sech;
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activationTest_map["Sech"] = &MLPPActivationOld::sech;
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activation_map["Coth"] = &MLPPActivationOld::coth;
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activationTest_map["Coth"] = &MLPPActivationOld::coth;
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activation_map["Arsinh"] = &MLPPActivationOld::arsinh;
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activationTest_map["Arsinh"] = &MLPPActivationOld::arsinh;
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activation_map["Arcosh"] = &MLPPActivationOld::arcosh;
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activationTest_map["Arcosh"] = &MLPPActivationOld::arcosh;
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activation_map["Artanh"] = &MLPPActivationOld::artanh;
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activationTest_map["Artanh"] = &MLPPActivationOld::artanh;
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activation_map["Arcsch"] = &MLPPActivationOld::arcsch;
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activationTest_map["Arcsch"] = &MLPPActivationOld::arcsch;
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activation_map["Arsech"] = &MLPPActivationOld::arsech;
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activationTest_map["Arsech"] = &MLPPActivationOld::arsech;
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activation_map["Arcoth"] = &MLPPActivationOld::arcoth;
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activationTest_map["Arcoth"] = &MLPPActivationOld::arcoth;
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costDeriv_map["MSE"] = &MLPPCostOld::MSEDeriv;
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cost_map["MSE"] = &MLPPCostOld::MSE;
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costDeriv_map["RMSE"] = &MLPPCostOld::RMSEDeriv;
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cost_map["RMSE"] = &MLPPCostOld::RMSE;
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costDeriv_map["MAE"] = &MLPPCostOld::MAEDeriv;
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cost_map["MAE"] = &MLPPCostOld::MAE;
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costDeriv_map["MBE"] = &MLPPCostOld::MBEDeriv;
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cost_map["MBE"] = &MLPPCostOld::MBE;
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costDeriv_map["LogLoss"] = &MLPPCostOld::LogLossDeriv;
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cost_map["LogLoss"] = &MLPPCostOld::LogLoss;
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costDeriv_map["CrossEntropy"] = &MLPPCostOld::CrossEntropyDeriv;
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cost_map["CrossEntropy"] = &MLPPCostOld::CrossEntropy;
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costDeriv_map["HingeLoss"] = &MLPPCostOld::HingeLossDeriv;
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cost_map["HingeLoss"] = &MLPPCostOld::HingeLoss;
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costDeriv_map["WassersteinLoss"] = &MLPPCostOld::HingeLossDeriv;
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cost_map["WassersteinLoss"] = &MLPPCostOld::HingeLoss;
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}
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void MLPPOldMultiOutputLayer::forwardPass() {
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MLPPLinAlgOld alg;
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MLPPActivationOld avn;
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z = alg.mat_vec_add(alg.matmult(input, weights), bias);
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a = (avn.*activation_map[activation])(z, false);
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}
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void MLPPOldMultiOutputLayer::Test(std::vector<real_t> x) {
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MLPPLinAlgOld alg;
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MLPPActivationOld avn;
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z_test = alg.addition(alg.mat_vec_mult(alg.transpose(weights), x), bias);
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a_test = (avn.*activationTest_map[activation])(z_test, false);
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}
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