/**
* @brief Save a neural network to file
* @brief fp File pointer
* @param net Backprop neural net object
*/
int bp_save(FILE * fp, bp * net)
{
int retval,i,l;
retval = fwrite(&net->itterations, sizeof(unsigned int), 1, fp);
retval = fwrite(&net->NoOfInputs, sizeof(int), 1, fp);
retval = fwrite(&net->NoOfHiddens, sizeof(int), 1, fp);
retval = fwrite(&net->NoOfOutputs, sizeof(int), 1, fp);
retval = fwrite(&net->HiddenLayers, sizeof(int), 1, fp);
retval = fwrite(&net->learningRate, sizeof(float), 1, fp);
retval = fwrite(&net->noise, sizeof(float), 1, fp);
retval = fwrite(&net->BPerrorAverage, sizeof(float), 1, fp);
retval = fwrite(&net->DropoutPercent, sizeof(float), 1, fp);
for (l = 0; l < net->HiddenLayers; l++) {
for (i = 0; i < net->NoOfHiddens; i++) {
bp_neuron_save(fp,net->hiddens[l][i]);
}
}
for (i = 0; i < net->NoOfOutputs; i++) {
bp_neuron_save(fp,net->outputs[i]);
}
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");
}
