/**
* @brief Load a network from file
* @brief fp File pointer
* @param net Backprop neural net object
* @param random_seed Random number generator seed
*/
int bp_load(FILE * fp, bp * net,
unsigned int * random_seed)
{
int retval,i,l;
int no_of_inputs=0, no_of_hiddens=0, no_of_outputs=0;
int hidden_layers=0;
float learning_rate=0, noise=0, BPerrorAverage=0;
float DropoutPercent=0;
unsigned int itterations=0;
retval = fread(&itterations, sizeof(unsigned int), 1, fp);
retval = fread(&no_of_inputs, sizeof(int), 1, fp);
retval = fread(&no_of_hiddens, sizeof(int), 1, fp);
retval = fread(&no_of_outputs, sizeof(int), 1, fp);
retval = fread(&hidden_layers, sizeof(int), 1, fp);
retval = fread(&learning_rate, sizeof(float), 1, fp);
retval = fread(&noise, sizeof(float), 1, fp);
retval = fread(&BPerrorAverage, sizeof(float), 1, fp);
retval = fread(&DropoutPercent, sizeof(float), 1, fp);
bp_init(net, no_of_inputs, no_of_hiddens,
hidden_layers, no_of_outputs,
random_seed);
for (l = 0; l < net->HiddenLayers; l++) {
for (i = 0; i < net->NoOfHiddens; i++) {
bp_neuron_load(fp,net->hiddens[l][i]);
}
}
for (i = 0; i < net->NoOfOutputs; i++) {
bp_neuron_load(fp,net->outputs[i]);
}
net->learningRate = learning_rate;
net->noise = noise;
net->BPerrorAverage = BPerrorAverage;
net->BPerror = BPerrorAverage;
net->BPerrorTotal = BPerrorAverage;
net->itterations = itterations;
net->DropoutPercent = DropoutPercent;
return retval;
}
static void test_backprop_neuron_save_load()
{
bp_neuron n1, n2;
int no_of_inputs=10;
unsigned int random_seed = 123;
char filename[256];
FILE * fp;
printf("test_backprop_neuron_save_load...");
/* create neurons */
bp_neuron_init(&n1, no_of_inputs, &random_seed);
bp_neuron_init(&n2, no_of_inputs, &random_seed);
sprintf(filename,"%stemp_deep.dat",DEEPLEARN_TEMP_DIRECTORY);
/* save the first neuron */
fp = fopen(filename,"wb");
assert(fp!=0);
bp_neuron_save(fp, &n1);
fclose(fp);
/* load into the second neuron */
fp = fopen(filename,"rb");
assert(fp!=0);
bp_neuron_load(fp, &n2);
fclose(fp);
/* compare the two */
assert(bp_neuron_compare(&n1, &n2)==1);
/* free memory */
bp_neuron_free(&n1);
bp_neuron_free(&n2);
printf("Ok\n");
}
