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route handles input images well....ish

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This commit is contained in:
Joseph Redmon
2015-05-11 13:46:49 -07:00
parent dc0d7bb8a8
commit 516f019ba6
31 changed files with 1250 additions and 1819 deletions
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36
src/softmax_layer.c
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@ -7,21 +7,23 @@
#include <stdio.h>
#include <assert.h>
softmax_layer *make_softmax_layer(int batch, int inputs, int groups)
softmax_layer make_softmax_layer(int batch, int inputs, int groups)
{
assert(inputs%groups == 0);
fprintf(stderr, "Softmax Layer: %d inputs\n", inputs);
softmax_layer *layer = calloc(1, sizeof(softmax_layer));
layer->batch = batch;
layer->groups = groups;
layer->inputs = inputs;
layer->output = calloc(inputs*batch, sizeof(float));
layer->delta = calloc(inputs*batch, sizeof(float));
softmax_layer l = {0};
l.type = SOFTMAX;
l.batch = batch;
l.groups = groups;
l.inputs = inputs;
l.outputs = inputs;
l.output = calloc(inputs*batch, sizeof(float));
l.delta = calloc(inputs*batch, sizeof(float));
#ifdef GPU
layer->output_gpu = cuda_make_array(layer->output, inputs*batch);
layer->delta_gpu = cuda_make_array(layer->delta, inputs*batch);
l.output_gpu = cuda_make_array(l.output, inputs*batch);
l.delta_gpu = cuda_make_array(l.delta, inputs*batch);
#endif
return layer;
return l;
}
void softmax_array(float *input, int n, float *output)
@ -42,21 +44,21 @@ void softmax_array(float *input, int n, float *output)
}
}
void forward_softmax_layer(const softmax_layer layer, network_state state)
void forward_softmax_layer(const softmax_layer l, network_state state)
{
int b;
int inputs = layer.inputs / layer.groups;
int batch = layer.batch * layer.groups;
int inputs = l.inputs / l.groups;
int batch = l.batch * l.groups;
for(b = 0; b < batch; ++b){
softmax_array(state.input+b*inputs, inputs, layer.output+b*inputs);
softmax_array(state.input+b*inputs, inputs, l.output+b*inputs);
}
}
void backward_softmax_layer(const softmax_layer layer, network_state state)
void backward_softmax_layer(const softmax_layer l, network_state state)
{
int i;
for(i = 0; i < layer.inputs*layer.batch; ++i){
state.delta[i] = layer.delta[i];
for(i = 0; i < l.inputs*l.batch; ++i){
state.delta[i] = l.delta[i];
}
}