/**
* @brief compares two networks and returns a greater than
* zero value if they are the same
* @param net1 The first backprop neural net object
* @param net2 The second backprop neural net object
*/
int bp_compare(bp * net1, bp * net2)
{
int retval,i,l;
if (net1->NoOfInputs != net2->NoOfInputs) {
return -1;
}
if (net1->NoOfHiddens != net2->NoOfHiddens) {
return -2;
}
if (net1->NoOfOutputs != net2->NoOfOutputs) {
return -3;
}
if (net1->HiddenLayers != net2->HiddenLayers) {
return -4;
}
if (net1->learningRate != net2->learningRate) {
return -5;
}
if (net1->noise != net2->noise) {
return -6;
}
for (l = 0; l < net1->HiddenLayers; l++) {
for (i = 0; i < net1->NoOfHiddens; i++) {
retval =
bp_neuron_compare(net1->hiddens[l][i],
net2->hiddens[l][i]);
if (retval == 0) return -7;
}
}
for (i = 0; i < net1->NoOfOutputs; i++) {
retval = bp_neuron_compare(net1->outputs[i], net2->outputs[i]);
if (retval == 0) return -8;
}
if (net1->itterations != net2->itterations) {
return -9;
}
if (net1->BPerrorAverage != net2->BPerrorAverage) {
return -9;
}
if (net1->DropoutPercent!= net2->DropoutPercent) {
return -10;
}
return 1;
}
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");
}
static void test_backprop_neuron_copy()
{
bp_neuron n1, n2;
int retval, no_of_inputs=10;
unsigned int random_seed = 123;
printf("test_backprop_neuron_copy...");
bp_neuron_init(&n1, no_of_inputs, &random_seed);
bp_neuron_init(&n2, no_of_inputs, &random_seed);
bp_neuron_copy(&n1, &n2);
retval = bp_neuron_compare(&n1, &n2);
if (retval != 1) {
printf("\nretval %d\n", retval);
}
assert(retval == 1);
bp_neuron_free(&n1);
bp_neuron_free(&n2);
printf("Ok\n");
}
