Loading may or may not work. But probably.

Joseph Redmon

2013-11-07 d7286c273211ffeb1f56594f863d1ee9922be6d4

 src/connected_layer.c

@@ -4,34 +4,34 @@
#include <stdlib.h>
#include <string.h>

connected_layer make_connected_layer(int inputs, int outputs, ACTIVATOR_TYPE activator)
connected_layer *make_connected_layer(int inputs, int outputs, ACTIVATION activator)
{
    int i;
    connected_layer layer;
    layer.inputs = inputs;
    layer.outputs = outputs;
    connected_layer *layer = calloc(1, sizeof(connected_layer));
    layer->inputs = inputs;
    layer->outputs = outputs;

    layer.output = calloc(outputs, sizeof(double*));
    layer->output = calloc(outputs, sizeof(double*));

    layer.weight_updates = calloc(inputs*outputs, sizeof(double));
    layer.weights = calloc(inputs*outputs, sizeof(double));
    layer->weight_updates = calloc(inputs*outputs, sizeof(double));
    layer->weights = calloc(inputs*outputs, sizeof(double));
    for(i = 0; i < inputs*outputs; ++i)
        layer.weights[i] = .5 - (double)rand()/RAND_MAX;
        layer->weights[i] = .5 - (double)rand()/RAND_MAX;

    layer.bias_updates = calloc(outputs, sizeof(double));
    layer.biases = calloc(outputs, sizeof(double));
    layer->bias_updates = calloc(outputs, sizeof(double));
    layer->biases = calloc(outputs, sizeof(double));
    for(i = 0; i < outputs; ++i)
        layer.biases[i] = (double)rand()/RAND_MAX;
        layer->biases[i] = (double)rand()/RAND_MAX;

    if(activator == SIGMOID){
        layer.activation = sigmoid_activation;
        layer.gradient = sigmoid_gradient;
        layer->activation = sigmoid_activation;
        layer->gradient = sigmoid_gradient;
    }else if(activator == RELU){
        layer.activation = relu_activation;
        layer.gradient = relu_gradient;
        layer->activation = relu_activation;
        layer->gradient = relu_gradient;
    }else if(activator == IDENTITY){
        layer.activation = identity_activation;
        layer.gradient = identity_gradient;
        layer->activation = identity_activation;
        layer->gradient = identity_gradient;
    }

    return layer;