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Small improvements and fixed MLPPMLP.

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Relintai 2023-12-27 18:40:19 +01:00
parent 726d51ec58
commit dda63a53e4
1 changed files with 9 additions and 27 deletions
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36
mlpp/mlp/mlp.cpp
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@ -109,7 +109,7 @@ void MLPPMLP::gradient_descent(real_t learning_rate, int max_epoch, bool UI) {
// Calculating the weight/bias for layer 1 // Calculating the weight/bias for layer 1
Ref<MLPPMatrix> D1_1 = error->outer_product(_weights2); Ref<MLPPMatrix> D1_1 = error->outer_product(_weights2);
Ref<MLPPMatrix> D1_2 = D1_1->transposen()->hadamard_productn(avn.sigmoid_derivm(_z2)); Ref<MLPPMatrix> D1_2 = D1_1->hadamard_productn(avn.sigmoid_derivm(_z2));
Ref<MLPPMatrix> D1_3 = _input_set->transposen()->multn(D1_2); Ref<MLPPMatrix> D1_3 = _input_set->transposen()->multn(D1_2);
// weight an bias updation for layer 1 // weight an bias updation for layer 1
@ -328,7 +328,7 @@ void MLPPMLP::initialize() {
MLPPUtilities util; MLPPUtilities util;
_weights1->resize(Size2i(_k, _n_hidden)); _weights1->resize(Size2i(_n_hidden, _k));
_weights2->resize(_n_hidden); _weights2->resize(_n_hidden);
_bias1->resize(_n_hidden); _bias1->resize(_n_hidden);
@ -397,38 +397,20 @@ MLPPMLP::MLPPMLP(const Ref<MLPPMatrix> &p_input_set, const Ref<MLPPVector> &p_ou
_output_set = p_output_set; _output_set = p_output_set;
_y_hat.instance(); _y_hat.instance();
_weights1.instance();
_weights2.instance();
_z2.instance();
_a2.instance();
_bias1.instance();
_n_hidden = p_n_hidden; _n_hidden = p_n_hidden;
_n = _input_set->size().y;
_k = _input_set->size().x;
_reg = p_reg; _reg = p_reg;
_lambda = p_lambda; _lambda = p_lambda;
_alpha = p_alpha; _alpha = p_alpha;
MLPPActivation avn; _initialized = false;
_y_hat->resize(_n);
MLPPUtilities util; initialize();
_weights1.instance();
_weights1->resize(Size2i(_k, _n_hidden));
_weights2.instance();
_weights2->resize(_n_hidden);
_bias1.instance();
_bias1->resize(_n_hidden);
util.weight_initializationm(_weights1);
util.weight_initializationv(_weights2);
util.bias_initializationv(_bias1);
_bias2 = util.bias_initializationr();
_z2.instance();
_a2.instance();
_initialized = true;
} }
MLPPMLP::MLPPMLP() { MLPPMLP::MLPPMLP() {