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This commit is contained in:
Joseph Redmon
2016-10-21 13:16:43 -07:00
parent ae53edc6a4
commit d8adaf8ea6
17 changed files with 287 additions and 127 deletions
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85
src/softmax_layer.c
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@ -32,31 +32,25 @@ softmax_layer make_softmax_layer(int batch, int inputs, int groups)
return l;
}
void softmax_array(float *input, int n, float temp, float *output)
{
int i;
float sum = 0;
float largest = -FLT_MAX;
for(i = 0; i < n; ++i){
if(input[i] > largest) largest = input[i];
}
for(i = 0; i < n; ++i){
sum += exp(input[i]/temp-largest/temp);
}
if(sum) sum = largest/temp+log(sum);
else sum = largest-100;
for(i = 0; i < n; ++i){
output[i] = exp(input[i]/temp-sum);
}
}
void forward_softmax_layer(const softmax_layer l, network_state state)
{
int b;
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, l.temperature, l.output+b*inputs);
if(l.softmax_tree){
for(b = 0; b < batch; ++b){
int i;
int count = 0;
for(i = 0; i < l.softmax_tree->groups; ++i){
int group_size = l.softmax_tree->group_size[i];
softmax(state.input+b*inputs + count, group_size, l.temperature, l.output+b*inputs + count);
count += group_size;
}
}
} else {
for(b = 0; b < batch; ++b){
softmax(state.input+b*inputs, inputs, l.temperature, l.output+b*inputs);
}
}
}
@ -68,3 +62,54 @@ void backward_softmax_layer(const softmax_layer l, network_state state)
}
}
#ifdef GPU
void pull_softmax_layer_output(const softmax_layer layer)
{
cuda_pull_array(layer.output_gpu, layer.output, layer.inputs*layer.batch);
}
void forward_softmax_layer_gpu(const softmax_layer l, network_state state)
{
int inputs = l.inputs / l.groups;
int batch = l.batch * l.groups;
int b;
if(l.softmax_tree){
if(0){
float *buff = calloc(inputs * batch, sizeof(float));
cuda_pull_array(state.input, buff, batch * inputs);
state.input = buff;
forward_softmax_layer(l, state);
cuda_push_array(l.output_gpu, l.output, batch*inputs);
free(buff);
} else {
int i;
const int nstreams = 32;
cudaStream_t streams[nstreams];
for (i = 0; i < nstreams; ++i) {
cudaStreamCreate(&streams[i]);
}
for (b = 0; b < batch; ++b) {
int i;
int count = 0;
for (i = 0; i < l.softmax_tree->groups; ++i) {
int group_size = l.softmax_tree->group_size[i];
softmax_gpu(state.input+b*inputs + count, group_size, 1, l.temperature, l.output_gpu+b*inputs + count, streams[(b*l.softmax_tree->groups + i) % nstreams]);
count += group_size;
}
}
for(i = 0; i < nstreams; ++i){
cudaStreamDestroy(streams[i]);
}
}
} else {
softmax_gpu(state.input, inputs, batch, l.temperature, l.output_gpu, 0);
}
}
void backward_softmax_layer_gpu(const softmax_layer layer, network_state state)
{
axpy_ongpu(layer.batch*layer.inputs, 1, layer.delta_gpu, 1, state.delta, 1);
}
#endif