From 564877ad6a3f53d3d866b0015237d07f4af2eaa2 Mon Sep 17 00:00:00 2001
From: vinjn <vinjn.z@gmail.com>
Date: Sat, 07 Jul 2018 04:30:45 +0000
Subject: [PATCH] cuda.h - converts tab to space
---
src/softmax_layer.c | 63 ++++++++++++-------------------
1 files changed, 24 insertions(+), 39 deletions(-)
diff --git a/src/softmax_layer.c b/src/softmax_layer.c
index 2a34cae..27f73fd 100644
--- a/src/softmax_layer.c
+++ b/src/softmax_layer.c
@@ -10,7 +10,7 @@
softmax_layer make_softmax_layer(int batch, int inputs, int groups)
{
assert(inputs%groups == 0);
- fprintf(stderr, "Softmax Layer: %d inputs\n", inputs);
+ fprintf(stderr, "softmax %4d\n", inputs);
softmax_layer l = {0};
l.type = SOFTMAX;
l.batch = batch;
@@ -32,24 +32,30 @@
return l;
}
+void softmax_tree(float *input, int batch, int inputs, float temp, tree *hierarchy, float *output)
+{
+ int b;
+ for(b = 0; b < batch; ++b){
+ int i;
+ int count = 0;
+ for(i = 0; i < hierarchy->groups; ++i){
+ int group_size = hierarchy->group_size[i];
+ softmax(input+b*inputs + count, group_size, temp, output+b*inputs + count, 1);
+ count += group_size;
+ }
+ }
+}
+
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;
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;
- }
- }
+ softmax_tree(state.input, batch, inputs, l.temperature, l.softmax_tree, l.output);
} else {
for(b = 0; b < batch; ++b){
- softmax(state.input+b*inputs, inputs, l.temperature, l.output+b*inputs);
+ softmax(state.input+b*inputs, inputs, l.temperature, l.output+b*inputs, 1);
}
}
}
@@ -73,37 +79,16 @@
{
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]);
- }
+ 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+count, group_size, inputs, batch, l.temperature, l.output_gpu + count);
+ count += group_size;
}
} else {
- softmax_gpu(state.input, inputs, batch, l.temperature, l.output_gpu, 0);
+ softmax_gpu(state.input, inputs, inputs, batch, l.temperature, l.output_gpu);
}
}
--
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