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NIGHTMARE!!!!

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This commit is contained in:
Joseph Redmon
2015-07-08 00:36:43 -07:00
parent d1d56a2a72
commit a08ef29e08
24 changed files with 456 additions and 96 deletions
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50
src/network.c
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@ -132,10 +132,11 @@ void backward_network(network net, network_state state)
{
int i;
float *original_input = state.input;
float *original_delta = state.delta;
for(i = net.n-1; i >= 0; --i){
if(i == 0){
state.input = original_input;
state.delta = 0;
state.delta = original_delta;
}else{
layer prev = net.layers[i-1];
state.input = prev.output;
@ -171,6 +172,7 @@ float train_network_datum(network net, float *x, float *y)
#endif
network_state state;
state.input = x;
state.delta = 0;
state.truth = y;
state.train = 1;
forward_network(net, state);
@ -224,6 +226,7 @@ float train_network_batch(network net, data d, int n)
int i,j;
network_state state;
state.train = 1;
state.delta = 0;
float sum = 0;
int batch = 2;
for(i = 0; i < n; ++i){
@ -249,43 +252,30 @@ void set_batch_network(network *net, int b)
}
}
/*
int resize_network(network net, int h, int w, int c)
int resize_network(network *net, int w, int h)
{
fprintf(stderr, "Might be broken, careful!!");
int i;
for (i = 0; i < net.n; ++i){
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer *layer = (convolutional_layer *)net.layers[i];
resize_convolutional_layer(layer, h, w);
image output = get_convolutional_image(*layer);
h = output.h;
w = output.w;
c = output.c;
} else if(net.types[i] == DECONVOLUTIONAL){
deconvolutional_layer *layer = (deconvolutional_layer *)net.layers[i];
resize_deconvolutional_layer(layer, h, w);
image output = get_deconvolutional_image(*layer);
h = output.h;
w = output.w;
c = output.c;
}else if(net.types[i] == MAXPOOL){
maxpool_layer *layer = (maxpool_layer *)net.layers[i];
resize_maxpool_layer(layer, h, w);
image output = get_maxpool_image(*layer);
h = output.h;
w = output.w;
c = output.c;
}else if(net.types[i] == DROPOUT){
dropout_layer *layer = (dropout_layer *)net.layers[i];
resize_dropout_layer(layer, h*w*c);
//if(w == net->w && h == net->h) return 0;
net->w = w;
net->h = h;
//fprintf(stderr, "Resizing to %d x %d...", w, h);
//fflush(stderr);
for (i = 0; i < net->n; ++i){
layer l = net->layers[i];
if(l.type == CONVOLUTIONAL){
resize_convolutional_layer(&l, w, h);
}else if(l.type == MAXPOOL){
resize_maxpool_layer(&l, w, h);
}else{
error("Cannot resize this type of layer");
}
net->layers[i] = l;
w = l.out_w;
h = l.out_h;
}
//fprintf(stderr, " Done!\n");
return 0;
}
*/
int get_network_output_size(network net)
{