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/dropout_layer.c | 176 +++++++++++++++++++++++++++++-----------------------------
1 files changed, 88 insertions(+), 88 deletions(-)
diff --git a/lib/detecter_tools/darknet/dropout_layer.c b/lib/detecter_tools/darknet/dropout_layer.c
index b941d31..3cc73ed 100644
--- a/lib/detecter_tools/darknet/dropout_layer.c
+++ b/lib/detecter_tools/darknet/dropout_layer.c
@@ -1,88 +1,88 @@
-#include "dropout_layer.h"
-#include "utils.h"
-#include "dark_cuda.h"
-#include <stdlib.h>
-#include <stdio.h>
-
-dropout_layer make_dropout_layer(int batch, int inputs, float probability, int dropblock, float dropblock_size_rel, int dropblock_size_abs, int w, int h, int c)
-{
- dropout_layer l = { (LAYER_TYPE)0 };
- l.type = DROPOUT;
- l.probability = probability;
- l.dropblock = dropblock;
- l.dropblock_size_rel = dropblock_size_rel;
- l.dropblock_size_abs = dropblock_size_abs;
- if (l.dropblock) {
- l.out_w = l.w = w;
- l.out_h = l.h = h;
- l.out_c = l.c = c;
-
- if (l.w <= 0 || l.h <= 0 || l.c <= 0) {
- printf(" Error: DropBlock - there must be positive values for: l.w=%d, l.h=%d, l.c=%d \n", l.w, l.h, l.c);
- exit(0);
- }
- }
- l.inputs = inputs;
- l.outputs = inputs;
- l.batch = batch;
- l.rand = (float*)xcalloc(inputs * batch, sizeof(float));
- l.scale = 1./(1.0 - probability);
- l.forward = forward_dropout_layer;
- l.backward = backward_dropout_layer;
-#ifdef GPU
- l.forward_gpu = forward_dropout_layer_gpu;
- l.backward_gpu = backward_dropout_layer_gpu;
- l.rand_gpu = cuda_make_array(l.rand, inputs*batch);
- if (l.dropblock) {
- l.drop_blocks_scale = cuda_make_array_pinned(l.rand, l.batch);
- l.drop_blocks_scale_gpu = cuda_make_array(l.rand, l.batch);
- }
-#endif
- if (l.dropblock) {
- if(l.dropblock_size_abs) fprintf(stderr, "dropblock p = %.3f l.dropblock_size_abs = %d %4d -> %4d\n", probability, l.dropblock_size_abs, inputs, inputs);
- else fprintf(stderr, "dropblock p = %.3f l.dropblock_size_rel = %.2f %4d -> %4d\n", probability, l.dropblock_size_rel, inputs, inputs);
- }
- else fprintf(stderr, "dropout p = %.3f %4d -> %4d\n", probability, inputs, inputs);
- return l;
-}
-
-void resize_dropout_layer(dropout_layer *l, int inputs)
-{
- l->inputs = l->outputs = inputs;
- l->rand = (float*)xrealloc(l->rand, l->inputs * l->batch * sizeof(float));
-#ifdef GPU
- cuda_free(l->rand_gpu);
- l->rand_gpu = cuda_make_array(l->rand, l->inputs*l->batch);
-
- if (l->dropblock) {
- cudaFreeHost(l->drop_blocks_scale);
- l->drop_blocks_scale = cuda_make_array_pinned(l->rand, l->batch);
-
- cuda_free(l->drop_blocks_scale_gpu);
- l->drop_blocks_scale_gpu = cuda_make_array(l->rand, l->batch);
- }
-#endif
-}
-
-void forward_dropout_layer(dropout_layer l, network_state state)
-{
- int i;
- if (!state.train) return;
- for(i = 0; i < l.batch * l.inputs; ++i){
- float r = rand_uniform(0, 1);
- l.rand[i] = r;
- if(r < l.probability) state.input[i] = 0;
- else state.input[i] *= l.scale;
- }
-}
-
-void backward_dropout_layer(dropout_layer l, network_state state)
-{
- int i;
- if(!state.delta) return;
- for(i = 0; i < l.batch * l.inputs; ++i){
- float r = l.rand[i];
- if(r < l.probability) state.delta[i] = 0;
- else state.delta[i] *= l.scale;
- }
-}
+#include "dropout_layer.h"
+#include "utils.h"
+#include "dark_cuda.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+dropout_layer make_dropout_layer(int batch, int inputs, float probability, int dropblock, float dropblock_size_rel, int dropblock_size_abs, int w, int h, int c)
+{
+ dropout_layer l = { (LAYER_TYPE)0 };
+ l.type = DROPOUT;
+ l.probability = probability;
+ l.dropblock = dropblock;
+ l.dropblock_size_rel = dropblock_size_rel;
+ l.dropblock_size_abs = dropblock_size_abs;
+ if (l.dropblock) {
+ l.out_w = l.w = w;
+ l.out_h = l.h = h;
+ l.out_c = l.c = c;
+
+ if (l.w <= 0 || l.h <= 0 || l.c <= 0) {
+ printf(" Error: DropBlock - there must be positive values for: l.w=%d, l.h=%d, l.c=%d \n", l.w, l.h, l.c);
+ exit(0);
+ }
+ }
+ l.inputs = inputs;
+ l.outputs = inputs;
+ l.batch = batch;
+ l.rand = (float*)xcalloc(inputs * batch, sizeof(float));
+ l.scale = 1./(1.0 - probability);
+ l.forward = forward_dropout_layer;
+ l.backward = backward_dropout_layer;
+#ifdef GPU
+ l.forward_gpu = forward_dropout_layer_gpu;
+ l.backward_gpu = backward_dropout_layer_gpu;
+ l.rand_gpu = cuda_make_array(l.rand, inputs*batch);
+ if (l.dropblock) {
+ l.drop_blocks_scale = cuda_make_array_pinned(l.rand, l.batch);
+ l.drop_blocks_scale_gpu = cuda_make_array(l.rand, l.batch);
+ }
+#endif
+ if (l.dropblock) {
+ if(l.dropblock_size_abs) fprintf(stderr, "dropblock p = %.3f l.dropblock_size_abs = %d %4d -> %4d\n", probability, l.dropblock_size_abs, inputs, inputs);
+ else fprintf(stderr, "dropblock p = %.3f l.dropblock_size_rel = %.2f %4d -> %4d\n", probability, l.dropblock_size_rel, inputs, inputs);
+ }
+ else fprintf(stderr, "dropout p = %.3f %4d -> %4d\n", probability, inputs, inputs);
+ return l;
+}
+
+void resize_dropout_layer(dropout_layer *l, int inputs)
+{
+ l->inputs = l->outputs = inputs;
+ l->rand = (float*)xrealloc(l->rand, l->inputs * l->batch * sizeof(float));
+#ifdef GPU
+ cuda_free(l->rand_gpu);
+ l->rand_gpu = cuda_make_array(l->rand, l->inputs*l->batch);
+
+ if (l->dropblock) {
+ cudaFreeHost(l->drop_blocks_scale);
+ l->drop_blocks_scale = cuda_make_array_pinned(l->rand, l->batch);
+
+ cuda_free(l->drop_blocks_scale_gpu);
+ l->drop_blocks_scale_gpu = cuda_make_array(l->rand, l->batch);
+ }
+#endif
+}
+
+void forward_dropout_layer(dropout_layer l, network_state state)
+{
+ int i;
+ if (!state.train) return;
+ for(i = 0; i < l.batch * l.inputs; ++i){
+ float r = rand_uniform(0, 1);
+ l.rand[i] = r;
+ if(r < l.probability) state.input[i] = 0;
+ else state.input[i] *= l.scale;
+ }
+}
+
+void backward_dropout_layer(dropout_layer l, network_state state)
+{
+ int i;
+ if(!state.delta) return;
+ for(i = 0; i < l.batch * l.inputs; ++i){
+ float r = l.rand[i];
+ if(r < l.probability) state.delta[i] = 0;
+ else state.delta[i] *= l.scale;
+ }
+}
--
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