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So there WAS this huge bug. Gone now

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This commit is contained in:
Joseph Redmon
2014-05-09 15:14:52 -07:00
parent 5ef74c2031
commit cd8d53df21
22 changed files with 769 additions and 193 deletions
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38
src/connected_layer.c
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@ -7,7 +7,7 @@
#include <stdlib.h>
#include <string.h>
connected_layer *make_connected_layer(int batch, int inputs, int outputs, ACTIVATION activation)
connected_layer *make_connected_layer(int batch, int inputs, int outputs, float dropout, ACTIVATION activation)
{
fprintf(stderr, "Connected Layer: %d inputs, %d outputs\n", inputs, outputs);
int i;
@ -15,6 +15,7 @@ connected_layer *make_connected_layer(int batch, int inputs, int outputs, ACTIVA
layer->inputs = inputs;
layer->outputs = outputs;
layer->batch=batch;
layer->dropout = dropout;
layer->output = calloc(batch*outputs, sizeof(float*));
layer->delta = calloc(batch*outputs, sizeof(float*));
@ -54,9 +55,9 @@ void update_connected_layer(connected_layer layer, float step, float momentum, f
memset(layer.weight_updates, 0, layer.outputs*layer.inputs*sizeof(float));
}
void forward_connected_layer(connected_layer layer, float *input)
void forward_connected_layer(connected_layer layer, float *input, int train)
{
int i;
if(!train) layer.dropout = 0;
memcpy(layer.output, layer.biases, layer.outputs*sizeof(float));
int m = layer.batch;
int k = layer.inputs;
@ -65,17 +66,15 @@ void forward_connected_layer(connected_layer layer, float *input)
float *b = layer.weights;
float *c = layer.output;
gemm(0,0,m,n,k,1,a,k,b,n,1,c,n);
for(i = 0; i < layer.outputs*layer.batch; ++i){
layer.output[i] = activate(layer.output[i], layer.activation);
}
activate_array(layer.output, layer.outputs*layer.batch, layer.activation, layer.dropout);
}
void learn_connected_layer(connected_layer layer, float *input)
void backward_connected_layer(connected_layer layer, float *input, float *delta)
{
int i;
for(i = 0; i < layer.outputs*layer.batch; ++i){
layer.delta[i] *= gradient(layer.output[i], layer.activation);
layer.bias_updates[i%layer.batch] += layer.delta[i]/layer.batch;
layer.bias_updates[i%layer.batch] += layer.delta[i];
}
int m = layer.inputs;
int k = layer.batch;
@ -84,18 +83,15 @@ void learn_connected_layer(connected_layer layer, float *input)
float *b = layer.delta;
float *c = layer.weight_updates;
gemm(0,0,m,n,k,1,a,k,b,n,1,c,n);
}
void backward_connected_layer(connected_layer layer, float *input, float *delta)
{
int m = layer.inputs;
int k = layer.outputs;
int n = layer.batch;
float *a = layer.weights;
float *b = layer.delta;
float *c = delta;
gemm(0,0,m,n,k,1,a,k,b,n,0,c,n);
m = layer.inputs;
k = layer.outputs;
n = layer.batch;
a = layer.weights;
b = layer.delta;
c = delta;
if(c) gemm(0,0,m,n,k,1,a,k,b,n,0,c,n);
}