pmlpp/mlpp/multi_output_layer/multi_output_layer.cpp

259 lines
8.8 KiB
C++

#include "multi_output_layer.h"
#include "../utilities/utilities.h"
int MLPPMultiOutputLayer::get_n_output() {
return _n_output;
}
void MLPPMultiOutputLayer::set_n_output(const int val) {
_n_output = val;
}
int MLPPMultiOutputLayer::get_n_hidden() {
return _n_hidden;
}
void MLPPMultiOutputLayer::set_n_hidden(const int val) {
_n_hidden = val;
}
MLPPActivation::ActivationFunction MLPPMultiOutputLayer::get_activation() {
return _activation;
}
void MLPPMultiOutputLayer::set_activation(const MLPPActivation::ActivationFunction val) {
_activation = val;
}
MLPPCost::CostTypes MLPPMultiOutputLayer::get_cost() {
return _cost;
}
void MLPPMultiOutputLayer::set_cost(const MLPPCost::CostTypes val) {
_cost = val;
}
Ref<MLPPMatrix> MLPPMultiOutputLayer::get_input() {
return _input;
}
void MLPPMultiOutputLayer::set_input(const Ref<MLPPMatrix> &val) {
_input = val;
}
Ref<MLPPMatrix> MLPPMultiOutputLayer::get_weights() {
return _weights;
}
void MLPPMultiOutputLayer::set_weights(const Ref<MLPPMatrix> &val) {
_weights = val;
}
Ref<MLPPVector> MLPPMultiOutputLayer::get_bias() {
return _bias;
}
void MLPPMultiOutputLayer::set_bias(const Ref<MLPPVector> &val) {
_bias = val;
}
Ref<MLPPMatrix> MLPPMultiOutputLayer::get_z() {
return _z;
}
void MLPPMultiOutputLayer::set_z(const Ref<MLPPMatrix> &val) {
_z = val;
}
Ref<MLPPMatrix> MLPPMultiOutputLayer::get_a() {
return _a;
}
void MLPPMultiOutputLayer::set_a(const Ref<MLPPMatrix> &val) {
_a = val;
}
Ref<MLPPVector> MLPPMultiOutputLayer::get_z_test() {
return _z_test;
}
void MLPPMultiOutputLayer::set_z_test(const Ref<MLPPVector> &val) {
_z_test = val;
}
Ref<MLPPVector> MLPPMultiOutputLayer::get_a_test() {
return _a_test;
}
void MLPPMultiOutputLayer::set_a_test(const Ref<MLPPVector> &val) {
_a_test = val;
}
Ref<MLPPMatrix> MLPPMultiOutputLayer::get_delta() {
return _delta;
}
void MLPPMultiOutputLayer::set_delta(const Ref<MLPPMatrix> &val) {
_delta = val;
}
MLPPReg::RegularizationType MLPPMultiOutputLayer::get_reg() {
return _reg;
}
void MLPPMultiOutputLayer::set_reg(const MLPPReg::RegularizationType val) {
_reg = val;
}
real_t MLPPMultiOutputLayer::get_lambda() {
return _lambda;
}
void MLPPMultiOutputLayer::set_lambda(const real_t val) {
_lambda = val;
}
real_t MLPPMultiOutputLayer::get_alpha() {
return _alpha;
}
void MLPPMultiOutputLayer::set_alpha(const real_t val) {
_alpha = val;
}
MLPPUtilities::WeightDistributionType MLPPMultiOutputLayer::get_weight_init() {
return _weight_init;
}
void MLPPMultiOutputLayer::set_weight_init(const MLPPUtilities::WeightDistributionType val) {
_weight_init = val;
}
void MLPPMultiOutputLayer::forward_pass() {
MLPPActivation avn;
_z = _input->multn(_weights)->add_vecn(_bias);
_a = avn.run_activation_norm_matrix(_activation, _z);
}
void MLPPMultiOutputLayer::test(const Ref<MLPPVector> &x) {
MLPPActivation avn;
_z_test = _weights->transposen()->mult_vec(x)->addn(_bias);
_a_test = avn.run_activation_norm_vector(_activation, _z_test);
}
MLPPMultiOutputLayer::MLPPMultiOutputLayer(int n_output, int p_n_hidden, MLPPActivation::ActivationFunction p_activation, MLPPCost::CostTypes cost, Ref<MLPPMatrix> p_input, MLPPUtilities::WeightDistributionType p_weight_init, MLPPReg::RegularizationType p_reg, real_t p_lambda, real_t p_alpha) {
_n_output = n_output;
_n_hidden = p_n_hidden;
_activation = p_activation;
_cost = cost;
_input = p_input;
// Regularization Params
_reg = p_reg;
_lambda = p_lambda; /* Regularization Parameter */
_alpha = p_alpha; /* This is the controlling param for Elastic Net*/
_weight_init = p_weight_init;
_z.instance();
_a.instance();
_z_test.instance();
_a_test.instance();
_delta.instance();
_weights.instance();
_bias.instance();
_weights->resize(Size2i(_n_output, _n_hidden));
_bias->resize(_n_output);
MLPPUtilities utils;
utils.weight_initializationm(_weights, _weight_init);
utils.bias_initializationv(_bias);
}
MLPPMultiOutputLayer::MLPPMultiOutputLayer() {
_n_hidden = 0;
_activation = MLPPActivation::ACTIVATION_FUNCTION_LINEAR;
// Regularization Params
//reg = 0;
_lambda = 0; /* Regularization Parameter */
_alpha = 0; /* This is the controlling param for Elastic Net*/
_weight_init = MLPPUtilities::WEIGHT_DISTRIBUTION_TYPE_DEFAULT;
_z.instance();
_a.instance();
_z_test.instance();
_a_test.instance();
_delta.instance();
_weights.instance();
_bias.instance();
}
MLPPMultiOutputLayer::~MLPPMultiOutputLayer() {
}
void MLPPMultiOutputLayer::_bind_methods() {
ClassDB::bind_method(D_METHOD("get_n_output"), &MLPPMultiOutputLayer::get_n_output);
ClassDB::bind_method(D_METHOD("set_n_output", "val"), &MLPPMultiOutputLayer::set_n_output);
ADD_PROPERTY(PropertyInfo(Variant::INT, "n_output"), "set_n_output", "get_n_output");
ClassDB::bind_method(D_METHOD("get_n_hidden"), &MLPPMultiOutputLayer::get_n_hidden);
ClassDB::bind_method(D_METHOD("set_n_hidden", "val"), &MLPPMultiOutputLayer::set_n_hidden);
ADD_PROPERTY(PropertyInfo(Variant::INT, "n_hidden"), "set_n_hidden", "get_n_hidden");
ClassDB::bind_method(D_METHOD("get_activation"), &MLPPMultiOutputLayer::get_activation);
ClassDB::bind_method(D_METHOD("set_activation", "val"), &MLPPMultiOutputLayer::set_activation);
ADD_PROPERTY(PropertyInfo(Variant::INT, "activation"), "set_activation", "get_activation");
ClassDB::bind_method(D_METHOD("get_cost"), &MLPPMultiOutputLayer::get_cost);
ClassDB::bind_method(D_METHOD("set_cost", "val"), &MLPPMultiOutputLayer::set_cost);
ADD_PROPERTY(PropertyInfo(Variant::INT, "cost"), "set_cost", "get_cost");
ClassDB::bind_method(D_METHOD("get_input"), &MLPPMultiOutputLayer::get_input);
ClassDB::bind_method(D_METHOD("set_input", "val"), &MLPPMultiOutputLayer::set_input);
ADD_PROPERTY(PropertyInfo(Variant::OBJECT, "input", PROPERTY_HINT_RESOURCE_TYPE, "MLPPMatrix"), "set_input", "get_input");
ClassDB::bind_method(D_METHOD("get_weights"), &MLPPMultiOutputLayer::get_weights);
ClassDB::bind_method(D_METHOD("set_weights", "val"), &MLPPMultiOutputLayer::set_weights);
ADD_PROPERTY(PropertyInfo(Variant::OBJECT, "weights", PROPERTY_HINT_RESOURCE_TYPE, "MLPPMatrix"), "set_weights", "get_weights");
ClassDB::bind_method(D_METHOD("get_bias"), &MLPPMultiOutputLayer::get_bias);
ClassDB::bind_method(D_METHOD("set_bias", "val"), &MLPPMultiOutputLayer::set_bias);
ADD_PROPERTY(PropertyInfo(Variant::OBJECT, "bias", PROPERTY_HINT_RESOURCE_TYPE, "MLPPVector"), "set_bias", "get_bias");
ClassDB::bind_method(D_METHOD("get_z"), &MLPPMultiOutputLayer::get_z);
ClassDB::bind_method(D_METHOD("set_z", "val"), &MLPPMultiOutputLayer::set_z);
ADD_PROPERTY(PropertyInfo(Variant::OBJECT, "z", PROPERTY_HINT_RESOURCE_TYPE, "MLPPMatrix"), "set_z", "get_z");
ClassDB::bind_method(D_METHOD("get_a"), &MLPPMultiOutputLayer::get_a);
ClassDB::bind_method(D_METHOD("set_a", "val"), &MLPPMultiOutputLayer::set_a);
ADD_PROPERTY(PropertyInfo(Variant::OBJECT, "a", PROPERTY_HINT_RESOURCE_TYPE, "MLPPMatrix"), "set_a", "get_a");
ClassDB::bind_method(D_METHOD("get_z_test"), &MLPPMultiOutputLayer::get_z_test);
ClassDB::bind_method(D_METHOD("set_z_test", "val"), &MLPPMultiOutputLayer::set_z_test);
ADD_PROPERTY(PropertyInfo(Variant::OBJECT, "z_test", PROPERTY_HINT_RESOURCE_TYPE, "MLPPVector"), "set_z_test", "get_z_test");
ClassDB::bind_method(D_METHOD("get_a_test"), &MLPPMultiOutputLayer::get_a_test);
ClassDB::bind_method(D_METHOD("set_a_test", "val"), &MLPPMultiOutputLayer::set_a_test);
ADD_PROPERTY(PropertyInfo(Variant::OBJECT, "a_test", PROPERTY_HINT_RESOURCE_TYPE, "MLPPVector"), "set_a_test", "get_a_test");
ClassDB::bind_method(D_METHOD("get_delta"), &MLPPMultiOutputLayer::get_delta);
ClassDB::bind_method(D_METHOD("set_delta", "val"), &MLPPMultiOutputLayer::set_delta);
ADD_PROPERTY(PropertyInfo(Variant::OBJECT, "delta", PROPERTY_HINT_RESOURCE_TYPE, "MLPPMatrix"), "set_delta", "get_delta");
ClassDB::bind_method(D_METHOD("get_reg"), &MLPPMultiOutputLayer::get_reg);
ClassDB::bind_method(D_METHOD("set_reg", "val"), &MLPPMultiOutputLayer::set_reg);
ADD_PROPERTY(PropertyInfo(Variant::INT, "reg"), "set_reg", "get_reg");
ClassDB::bind_method(D_METHOD("get_lambda"), &MLPPMultiOutputLayer::get_lambda);
ClassDB::bind_method(D_METHOD("set_lambda", "val"), &MLPPMultiOutputLayer::set_lambda);
ADD_PROPERTY(PropertyInfo(Variant::REAL, "lambda"), "set_lambda", "get_lambda");
ClassDB::bind_method(D_METHOD("get_alpha"), &MLPPMultiOutputLayer::get_alpha);
ClassDB::bind_method(D_METHOD("set_alpha", "val"), &MLPPMultiOutputLayer::set_alpha);
ADD_PROPERTY(PropertyInfo(Variant::REAL, "alpha"), "set_alpha", "get_alpha");
ClassDB::bind_method(D_METHOD("get_weight_init"), &MLPPMultiOutputLayer::get_weight_init);
ClassDB::bind_method(D_METHOD("set_weight_init", "val"), &MLPPMultiOutputLayer::set_weight_init);
ADD_PROPERTY(PropertyInfo(Variant::INT, "set_weight_init"), "set_weight_init", "get_weight_init");
ClassDB::bind_method(D_METHOD("forward_pass"), &MLPPMultiOutputLayer::forward_pass);
ClassDB::bind_method(D_METHOD("test", "x"), &MLPPMultiOutputLayer::test);
}