From 6553b3f0e3e55fc30a99c7d4b5798aa86d18a114 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Mon, 30 Mar 2015 02:31:47 +0000
Subject: [PATCH] no comment
---
src/cost_layer.c | 49 ++++++++++++++++++++++---------------------------
1 files changed, 22 insertions(+), 27 deletions(-)
diff --git a/src/cost_layer.c b/src/cost_layer.c
index a08562b..d2c616f 100644
--- a/src/cost_layer.c
+++ b/src/cost_layer.c
@@ -10,7 +10,6 @@
COST_TYPE get_cost_type(char *s)
{
if (strcmp(s, "sse")==0) return SSE;
- if (strcmp(s, "detection")==0) return DETECTION;
fprintf(stderr, "Couldn't find activation function %s, going with SSE\n", s);
return SSE;
}
@@ -20,8 +19,6 @@
switch(a){
case SSE:
return "sse";
- case DETECTION:
- return "detection";
}
return "sse";
}
@@ -41,47 +38,45 @@
return layer;
}
-void forward_cost_layer(cost_layer layer, float *input, float *truth)
+void pull_cost_layer(cost_layer layer)
{
- if (!truth) return;
- copy_cpu(layer.batch*layer.inputs, truth, 1, layer.delta, 1);
- axpy_cpu(layer.batch*layer.inputs, -1, input, 1, layer.delta, 1);
- if(layer.type == DETECTION){
- int i;
- for(i = 0; i < layer.batch*layer.inputs; ++i){
- if((i%5) && !truth[(i/5)*5]) layer.delta[i] = 0;
- }
- }
+ cuda_pull_array(layer.delta_gpu, layer.delta, layer.batch*layer.inputs);
+}
+void push_cost_layer(cost_layer layer)
+{
+ cuda_push_array(layer.delta_gpu, layer.delta, layer.batch*layer.inputs);
+}
+
+void forward_cost_layer(cost_layer layer, network_state state)
+{
+ if (!state.truth) return;
+ copy_cpu(layer.batch*layer.inputs, state.truth, 1, layer.delta, 1);
+ axpy_cpu(layer.batch*layer.inputs, -1, state.input, 1, layer.delta, 1);
*(layer.output) = dot_cpu(layer.batch*layer.inputs, layer.delta, 1, layer.delta, 1);
//printf("cost: %f\n", *layer.output);
}
-void backward_cost_layer(const cost_layer layer, float *input, float *delta)
+void backward_cost_layer(const cost_layer layer, network_state state)
{
- copy_cpu(layer.batch*layer.inputs, layer.delta, 1, delta, 1);
+ copy_cpu(layer.batch*layer.inputs, layer.delta, 1, state.delta, 1);
}
#ifdef GPU
-void forward_cost_layer_gpu(cost_layer layer, float * input, float * truth)
+void forward_cost_layer_gpu(cost_layer layer, network_state state)
{
- if (!truth) return;
-
- copy_ongpu(layer.batch*layer.inputs, truth, 1, layer.delta_gpu, 1);
- axpy_ongpu(layer.batch*layer.inputs, -1, input, 1, layer.delta_gpu, 1);
-
- if(layer.type==DETECTION){
- mask_ongpu(layer.inputs*layer.batch, layer.delta_gpu, truth, 5);
- }
+ if (!state.truth) return;
+
+ copy_ongpu(layer.batch*layer.inputs, state.truth, 1, layer.delta_gpu, 1);
+ axpy_ongpu(layer.batch*layer.inputs, -1, state.input, 1, layer.delta_gpu, 1);
cuda_pull_array(layer.delta_gpu, layer.delta, layer.batch*layer.inputs);
*(layer.output) = dot_cpu(layer.batch*layer.inputs, layer.delta, 1, layer.delta, 1);
- //printf("cost: %f\n", *layer.output);
}
-void backward_cost_layer_gpu(const cost_layer layer, float * input, float * delta)
+void backward_cost_layer_gpu(const cost_layer layer, network_state state)
{
- copy_ongpu(layer.batch*layer.inputs, layer.delta_gpu, 1, delta, 1);
+ copy_ongpu(layer.batch*layer.inputs, layer.delta_gpu, 1, state.delta, 1);
}
#endif
--
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