/**
* @brief Update the neural net during training
* @param net Backprop neural net object
*/
void bp_update(bp * net, int current_hidden_layer)
{
bp_dropouts(net);
bp_feed_forward(net);
bp_backprop(net, current_hidden_layer);
bp_learn(net, current_hidden_layer);
bp_clear_dropouts(net);
}
static void test_backprop()
{
bp net;
int no_of_inputs=10;
int no_of_hiddens=4;
int hidden_layers=2;
int no_of_outputs=5;
int i,l;
unsigned int random_seed = 123;
printf("test_backprop...");
bp_init(&net,
no_of_inputs, no_of_hiddens,
hidden_layers,
no_of_outputs, &random_seed);
assert((&net)->inputs!=0);
assert((&net)->hiddens!=0);
assert((&net)->outputs!=0);
/* set some inputs */
for (i = 0; i < no_of_inputs; i++) {
bp_set_input(&net, i, i/(float)no_of_inputs);
(&net)->inputs[i]->BPerror = 999;
}
for (l = 0; l < hidden_layers; l++) {
for (i = 0; i < bp_hiddens_in_layer(&net,l); i++) {
(&net)->hiddens[l][i]->BPerror = 999;
}
}
/* set some target outputs */
for (i = 0; i < no_of_outputs; i++) {
(&net)->outputs[i]->BPerror = 999;
bp_set_output(&net, i, i/(float)no_of_inputs);
}
/* feed forward */
bp_feed_forward(&net);
bp_backprop(&net,0);
/* check for non-zero backprop error values */
for (i = 0; i < no_of_inputs; i++) {
assert((&net)->inputs[i]->BPerror != 999);
}
for (l = 0; l < hidden_layers; l++) {
for (i = 0; i < bp_hiddens_in_layer(&net,l); i++) {
assert((&net)->hiddens[l][i]->BPerror != 999);
}
}
for (i = 0; i < no_of_outputs; i++) {
assert((&net)->outputs[i]->BPerror != 999);
}
bp_free(&net);
printf("Ok\n");
}
static void test_backprop_feed_forward()
{
bp net;
int no_of_inputs=10;
int no_of_hiddens=4;
int hidden_layers=2;
int no_of_outputs=5;
int i;
unsigned int random_seed = 123;
printf("test_backprop_feed_forward...");
bp_init(&net,
no_of_inputs, no_of_hiddens,
hidden_layers,
no_of_outputs, &random_seed);
assert((&net)->inputs!=0);
assert((&net)->hiddens!=0);
assert((&net)->outputs!=0);
/* set some inputs */
for (i = 0; i < no_of_inputs; i++) {
bp_set_input(&net, i, i/(float)no_of_inputs);
}
/* clear the outputs */
for (i = 0; i < no_of_outputs; i++) {
(&net)->outputs[i]->value = 999;
}
/* feed forward */
bp_feed_forward(&net);
/* check for non-zero outputs */
for (i = 0; i < no_of_outputs; i++) {
assert((&net)->outputs[i]->value != 999);
}
bp_free(&net);
printf("Ok\n");
}
static void test_backprop_training()
{
bp * net;
int no_of_inputs=2;
int no_of_hiddens=2;
int hidden_layers=1;
int no_of_outputs=1;
int itt,example;
unsigned int random_seed = 123;
float state_TRUE = 0.8f;
float state_FALSE = 0.2f;
printf("test_backprop_training...");
net = (bp*)malloc(sizeof(bp));
bp_init(net,
no_of_inputs, no_of_hiddens,
hidden_layers,
no_of_outputs, &random_seed);
assert(net->inputs!=0);
assert(net->hiddens!=0);
assert(net->outputs!=0);
/* training */
example=0;
for (itt = 0; itt < 500000; itt++, example++) {
if (example>=4) example=0;
/* select an example from the XOR truth table */
switch(example) {
case 0: {
bp_set_input(net, 0, state_FALSE);
bp_set_input(net, 1, state_FALSE);
bp_set_output(net, 0, state_FALSE);
break;
}
case 1: {
bp_set_input(net, 0, state_TRUE);
bp_set_input(net, 1, state_FALSE);
bp_set_output(net, 0, state_TRUE);
break;
}
case 2: {
bp_set_input(net, 0, state_FALSE);
bp_set_input(net, 1, state_TRUE);
bp_set_output(net, 0, state_TRUE);
break;
}
case 3: {
bp_set_input(net, 0, state_TRUE);
bp_set_input(net, 1, state_TRUE);
bp_set_output(net, 0, state_FALSE);
break;
}
}
/* train on the example */
bp_update(net,0);
}
bp_set_input(net, 0, state_FALSE);
bp_set_input(net, 1, state_FALSE);
bp_feed_forward(net);
if (bp_get_output(net, 0) >= 0.5f) {
printf("\n%.5f\n",bp_get_output(net, 0));
}
assert(bp_get_output(net, 0) < 0.5f);
bp_set_input(net, 0, state_FALSE);
bp_set_input(net, 1, state_TRUE);
bp_feed_forward(net);
if (bp_get_output(net, 0) <= 0.5f) {
printf("\n%.5f\n",bp_get_output(net, 0));
}
assert(bp_get_output(net, 0) > 0.5f);
bp_set_input(net, 0, state_TRUE);
bp_set_input(net, 1, state_FALSE);
bp_feed_forward(net);
if (bp_get_output(net, 0) <= 0.5f) {
printf("\n%.5f\n",bp_get_output(net, 0));
}
assert(bp_get_output(net, 0) > 0.5f);
bp_set_input(net, 0, state_FALSE);
bp_set_input(net, 1, state_FALSE);
bp_feed_forward(net);
if (bp_get_output(net, 0) >= 0.5f) {
printf("\n%.5f\n",bp_get_output(net, 0));
}
assert(bp_get_output(net, 0) < 0.5f);
bp_free(net);
free(net);
printf("Ok\n");
}
