From 168af40fe9a3cc81c6ee16b3e81f154780c36bdb Mon Sep 17 00:00:00 2001
From: Scheaven <xuepengqiang>
Date: 星期四, 03 六月 2021 15:03:27 +0800
Subject: [PATCH] up new v4
---
lib/detecter_tools/darknet/avgpool_layer.c | 142 +++++++++++++++++++++++-----------------------
1 files changed, 71 insertions(+), 71 deletions(-)
diff --git a/lib/detecter_tools/darknet/avgpool_layer.c b/lib/detecter_tools/darknet/avgpool_layer.c
index 64567cd..2b595aa 100644
--- a/lib/detecter_tools/darknet/avgpool_layer.c
+++ b/lib/detecter_tools/darknet/avgpool_layer.c
@@ -1,71 +1,71 @@
-#include "avgpool_layer.h"
-#include "dark_cuda.h"
-#include "utils.h"
-#include <stdio.h>
-
-avgpool_layer make_avgpool_layer(int batch, int w, int h, int c)
-{
- fprintf(stderr, "avg %4d x%4d x%4d -> %4d\n", w, h, c, c);
- avgpool_layer l = { (LAYER_TYPE)0 };
- l.type = AVGPOOL;
- l.batch = batch;
- l.h = h;
- l.w = w;
- l.c = c;
- l.out_w = 1;
- l.out_h = 1;
- l.out_c = c;
- l.outputs = l.out_c;
- l.inputs = h*w*c;
- int output_size = l.outputs * batch;
- l.output = (float*)xcalloc(output_size, sizeof(float));
- l.delta = (float*)xcalloc(output_size, sizeof(float));
- l.forward = forward_avgpool_layer;
- l.backward = backward_avgpool_layer;
- #ifdef GPU
- l.forward_gpu = forward_avgpool_layer_gpu;
- l.backward_gpu = backward_avgpool_layer_gpu;
- l.output_gpu = cuda_make_array(l.output, output_size);
- l.delta_gpu = cuda_make_array(l.delta, output_size);
- #endif
- return l;
-}
-
-void resize_avgpool_layer(avgpool_layer *l, int w, int h)
-{
- l->w = w;
- l->h = h;
- l->inputs = h*w*l->c;
-}
-
-void forward_avgpool_layer(const avgpool_layer l, network_state state)
-{
- int b,i,k;
-
- for(b = 0; b < l.batch; ++b){
- for(k = 0; k < l.c; ++k){
- int out_index = k + b*l.c;
- l.output[out_index] = 0;
- for(i = 0; i < l.h*l.w; ++i){
- int in_index = i + l.h*l.w*(k + b*l.c);
- l.output[out_index] += state.input[in_index];
- }
- l.output[out_index] /= l.h*l.w;
- }
- }
-}
-
-void backward_avgpool_layer(const avgpool_layer l, network_state state)
-{
- int b,i,k;
-
- for(b = 0; b < l.batch; ++b){
- for(k = 0; k < l.c; ++k){
- int out_index = k + b*l.c;
- for(i = 0; i < l.h*l.w; ++i){
- int in_index = i + l.h*l.w*(k + b*l.c);
- state.delta[in_index] += l.delta[out_index] / (l.h*l.w);
- }
- }
- }
-}
+#include "avgpool_layer.h"
+#include "dark_cuda.h"
+#include "utils.h"
+#include <stdio.h>
+
+avgpool_layer make_avgpool_layer(int batch, int w, int h, int c)
+{
+ fprintf(stderr, "avg %4d x%4d x%4d -> %4d\n", w, h, c, c);
+ avgpool_layer l = { (LAYER_TYPE)0 };
+ l.type = AVGPOOL;
+ l.batch = batch;
+ l.h = h;
+ l.w = w;
+ l.c = c;
+ l.out_w = 1;
+ l.out_h = 1;
+ l.out_c = c;
+ l.outputs = l.out_c;
+ l.inputs = h*w*c;
+ int output_size = l.outputs * batch;
+ l.output = (float*)xcalloc(output_size, sizeof(float));
+ l.delta = (float*)xcalloc(output_size, sizeof(float));
+ l.forward = forward_avgpool_layer;
+ l.backward = backward_avgpool_layer;
+ #ifdef GPU
+ l.forward_gpu = forward_avgpool_layer_gpu;
+ l.backward_gpu = backward_avgpool_layer_gpu;
+ l.output_gpu = cuda_make_array(l.output, output_size);
+ l.delta_gpu = cuda_make_array(l.delta, output_size);
+ #endif
+ return l;
+}
+
+void resize_avgpool_layer(avgpool_layer *l, int w, int h)
+{
+ l->w = w;
+ l->h = h;
+ l->inputs = h*w*l->c;
+}
+
+void forward_avgpool_layer(const avgpool_layer l, network_state state)
+{
+ int b,i,k;
+
+ for(b = 0; b < l.batch; ++b){
+ for(k = 0; k < l.c; ++k){
+ int out_index = k + b*l.c;
+ l.output[out_index] = 0;
+ for(i = 0; i < l.h*l.w; ++i){
+ int in_index = i + l.h*l.w*(k + b*l.c);
+ l.output[out_index] += state.input[in_index];
+ }
+ l.output[out_index] /= l.h*l.w;
+ }
+ }
+}
+
+void backward_avgpool_layer(const avgpool_layer l, network_state state)
+{
+ int b,i,k;
+
+ for(b = 0; b < l.batch; ++b){
+ for(k = 0; k < l.c; ++k){
+ int out_index = k + b*l.c;
+ for(i = 0; i < l.h*l.w; ++i){
+ int in_index = i + l.h*l.w*(k + b*l.c);
+ state.delta[in_index] += l.delta[out_index] / (l.h*l.w);
+ }
+ }
+ }
+}
--
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