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HolyFuckItsAlive #13

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jastornig merged 105 commits from Delta-Error-Test into main 2023-09-23 22:27:54 +02:00
Conversation 3 Commits 105 Files changed 19 +10 -13
1 changed files with 10 additions and 13 deletions
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neuronal_network.c
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@ -45,8 +45,6 @@ void randomize_network(Neural_Network* network, int scope){
matrix_randomize(network->bias_output, scope);
}
//void print_network(Neural_Network* network){};
void free_network(Neural_Network* network){
matrix_free(network->weights_1);
matrix_free(network->weights_2);
@ -226,15 +224,15 @@ void train_network(Neural_Network* network, Image *image, int label) {
Matrix* final_outputs = apply(sigmoid, final_add);
// begin backpropagation
Matrix* sigma1 = matrix_create(final_outputs->rows, 1);
matrix_fill(sigma1, 1);
Matrix* temp1 = subtract(sigma1, final_outputs);
Matrix* temp9 = matrix_create(final_outputs->rows, 1);
matrix_fill(temp9, 1);
Matrix* temp1 = subtract(temp9, final_outputs);
Matrix* temp2 = multiply(temp1, final_outputs); // * soll-ist
Matrix* temp3 = matrix_create(final_outputs->rows, final_outputs->columns);
matrix_fill(temp3, 0);
temp3->numbers[label][0] = 1;
Matrix* temp4 = subtract(temp3, final_outputs);
sigma1 = multiply(temp2, temp4);
Matrix* sigma1 = multiply(temp2, temp4);
Matrix* temp5 = transpose(h3_outputs);
Matrix* temp6 = dot(sigma1, temp5);
@ -303,13 +301,14 @@ void train_network(Neural_Network* network, Image *image, int label) {
matrix_free(temp6);
matrix_free(temp7);
matrix_free(temp8);
matrix_free(temp9);
}
Matrix * backPropagation(double learning_rate, Matrix* weights, Matrix* biases, Matrix* current_layer_activation, Matrix* previous_layer_activation, Matrix* sigma_old) {
Matrix* sigma_new = matrix_create(current_layer_activation->rows, 1);
matrix_fill(sigma_new, 1);
Matrix* temp7 = matrix_create(current_layer_activation->rows, 1);
matrix_fill(temp7, 1);
Matrix* temp1 = subtract(sigma_new, current_layer_activation);
Matrix* temp1 = subtract(temp7, current_layer_activation);
Matrix* temp2 = multiply(temp1, current_layer_activation); // *sum(delta*weights)
for(int i = 0; i < current_layer_activation->rows; i++) {
@ -319,7 +318,7 @@ Matrix * backPropagation(double learning_rate, Matrix* weights, Matrix* biases,
}
temp1->numbers[i][0] = sum;
}
sigma_new = multiply(temp2, temp1);
Matrix* sigma_new = multiply(temp2, temp1);
// new sigma done
@ -348,15 +347,13 @@ Matrix * backPropagation(double learning_rate, Matrix* weights, Matrix* biases,
matrix_free(temp4);
matrix_free(temp5);
matrix_free(temp6);
matrix_free(temp7);
matrix_free(weights_delta);
matrix_free(bias_delta);
return sigma_new;
}
//void batch_train_network(Neural_Network* network, Image** images, int size);
double sigmoid(double input) {
return 1.0 / (1 + exp(-1 * input));
}