diff options
Diffstat (limited to 'src/nn.c')
| -rw-r--r-- | src/nn.c | 34 |
1 files changed, 17 insertions, 17 deletions
@@ -88,8 +88,11 @@ void nn_network_train( for (size_t l = 0; l < network_size; l++) { outs[l] = calloc(samples * network[l].neurons, sizeof(double)); zouts[l] = calloc(samples * network[l].neurons, sizeof(double)); - weights[l] = calloc(network[l].input_nodes * network[l].neurons, sizeof(double)); - biases[l] = calloc(network[l].neurons, sizeof(double)); + weights[l] = malloc(network[l].input_nodes * network[l].neurons * sizeof(double)); + biases[l] = malloc(network[l].neurons * sizeof(double)); + + memcpy(weights[l], network[l].weights, sizeof(double) * network[l].input_nodes * network[l].neurons); + memcpy(biases[l], network[l].bias, sizeof(double) * network[l].neurons); } for (size_t epoch = 0; epoch < epochs; epoch++) { @@ -175,11 +178,12 @@ void nn_backward( memmove(delta_next, delta, weights_shape[1] * sizeof(double)); } - for (size_t l = 0; l < network_size; l++) { - size_t weights_shape[2] = {network[l].input_nodes, network[l].neurons}; - memmove(network[l].weights, weights[l], weights_shape[0] * weights_shape[1] * sizeof(double)); - memmove(network[l].bias, bias[l], weights_shape[1] * sizeof(double)); - } + } + + for (size_t l = 0; l < network_size; l++) { + size_t weights_shape[2] = {network[l].input_nodes, network[l].neurons}; + memcpy(network[l].weights, weights[l], weights_shape[0] * weights_shape[1] * sizeof(double)); + memcpy(network[l].bias, bias[l], weights_shape[1] * sizeof(double)); } free(dcost_outs); @@ -192,20 +196,16 @@ nn_backward_error: } void nn_layer_backward( - double *weights, double *bias, size_t weigths_shape[2], + double *weights, double *bias, size_t weights_shape[2], double *delta, double *out_prev, Layer layer, double alpha) { - for (size_t i = 0; i < weigths_shape[0]; i++) { - for (size_t j = 0; j < weigths_shape[1]; j++) { - size_t index = weigths_shape[1] * i + j; - double dcost_w = delta[j] * out_prev[i]; - weights[index] = layer.weights[index] - alpha * dcost_w; - } - } + // W_next = W - alpha * out_prev @ delta.T + cblas_dger(CblasRowMajor, weights_shape[0], weights_shape[1], -alpha, + out_prev, 1, delta, 1, weights, weights_shape[1]); - for (size_t j = 0; j < weigths_shape[1]; j++) - bias[j] = layer.bias[j] - alpha * delta[j]; + for (size_t j = 0; j < weights_shape[1]; j++) + bias[j] = bias[j] - alpha * delta[j]; } void nn_layer_hidden_delta( |