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#include "nn.h"
static void fill_random_weights(double *weights, double *bias, size_t rows, size_t cols);
double * nn_layer_forward(Layer layer, double *input, size_t input_shape[2])
{
double *out = calloc(input_shape[0] * layer.neurons, sizeof(double));
if (out == NULL) {
perror("nn_layer_forward() Error");
exit(1);
}
for (size_t i = 0; i < input_shape[0]; i++) {
for (size_t j = 0; j < layer.neurons; j++) {
size_t index = layer.neurons * i + j;
out[index] = layer.bias[j];
}
}
cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasNoTrans,
input_shape[0], layer.neurons, layer.input_nodes, // m, n, k
1.0, input, input_shape[1], //alpha X
layer.weights, layer.neurons, // W
1.0, out, layer.neurons); // beta B
return out;
}
void nn_layer_init_weights(Layer layers[], size_t nmemb, size_t n_inputs)
{
int i;
size_t prev_size = n_inputs;
for (i = 0; i < nmemb; i++) {
layers[i].weights = calloc(prev_size * layers[i].neurons, sizeof(Layer));
layers[i].bias = calloc(layers[i].neurons, sizeof(Layer));
if (layers[i].weights == NULL || layers[i].bias == NULL) {
goto nn_layers_calloc_weights_error;
}
fill_random_weights(layers[i].weights, layers[i].bias, prev_size, layers[i].neurons);
layers[i].input_nodes = prev_size;
prev_size = layers[i].neurons;
}
return;
nn_layers_calloc_weights_error:
perror("nn_layers_calloc_weights() Error");
exit(1);
}
void nn_layer_free_weights(Layer *layer, size_t nmemb)
{
for (int i = 0; i < nmemb; i++) {
free(layer[i].weights);
free(layer[i].bias);
}
}
double sigmoid(double x)
{
return 1 / (1 + exp(-x));
}
double relu(double x)
{
return (x > 0) ? x : 0;
}
void fill_random_weights(double *weights, double *bias, size_t rows, size_t cols)
{
FILE *fp = fopen("/dev/random", "rb");
if (fp == NULL) goto nn_fill_random_weights_error;
size_t weights_size = rows * cols;
int64_t *random_weights = calloc(weights_size, sizeof(int64_t));
int64_t *random_bias = calloc(rows, sizeof(int64_t));
fread(random_weights, sizeof(double), weights_size, fp);
fread(random_bias, sizeof(double), rows, fp);
if (!random_weights || !random_bias) goto nn_fill_random_weights_error;
for (size_t i = 0; i < weights_size; i++) {
weights[i] = (double)random_weights[i] / (double)INT64_MAX * 2;
}
for (size_t i = 0; i < weights_size; i++) {
bias[i] = (double)random_bias[i] / (double)INT64_MAX * 2;
}
free(random_weights);
free(random_bias);
fclose(fp);
return;
nn_fill_random_weights_error:
perror("nn_fill_random_weights Error()");
exit(1);
}
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