From eb98da5000f4d347ee8563467dffa4541e7faa7a Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Tue, 11 Aug 2015 06:22:54 +0000
Subject: [PATCH] Merge branch 'master' of github.com:pjreddie/darknet
---
src/convolutional_layer.c | 48 +++++++++++++++++++++++++++++++++++++++---------
1 files changed, 39 insertions(+), 9 deletions(-)
diff --git a/src/convolutional_layer.c b/src/convolutional_layer.c
index b6437d4..7dcf5a4 100644
--- a/src/convolutional_layer.c
+++ b/src/convolutional_layer.c
@@ -61,7 +61,8 @@
l.biases = calloc(n, sizeof(float));
l.bias_updates = calloc(n, sizeof(float));
- float scale = 1./sqrt(size*size*c);
+ //float scale = 1./sqrt(size*size*c);
+ float scale = sqrt(2./(size*size*c));
for(i = 0; i < c*n*size*size; ++i) l.filters[i] = 2*scale*rand_uniform() - scale;
for(i = 0; i < n; ++i){
l.biases[i] = scale;
@@ -96,12 +97,18 @@
return l;
}
-void resize_convolutional_layer(convolutional_layer *l, int h, int w)
+void resize_convolutional_layer(convolutional_layer *l, int w, int h)
{
- l->h = h;
l->w = w;
- int out_h = convolutional_out_height(*l);
+ l->h = h;
int out_w = convolutional_out_width(*l);
+ int out_h = convolutional_out_height(*l);
+
+ l->out_w = out_w;
+ l->out_h = out_h;
+
+ l->outputs = l->out_h * l->out_w * l->out_c;
+ l->inputs = l->w * l->h * l->c;
l->col_image = realloc(l->col_image,
out_h*out_w*l->size*l->size*l->c*sizeof(float));
@@ -115,9 +122,9 @@
cuda_free(l->delta_gpu);
cuda_free(l->output_gpu);
- l->col_image_gpu = cuda_make_array(l->col_image, out_h*out_w*l->size*l->size*l->c);
- l->delta_gpu = cuda_make_array(l->delta, l->batch*out_h*out_w*l->n);
- l->output_gpu = cuda_make_array(l->output, l->batch*out_h*out_w*l->n);
+ l->col_image_gpu = cuda_make_array(0, out_h*out_w*l->size*l->size*l->c);
+ l->delta_gpu = cuda_make_array(0, l->batch*out_h*out_w*l->n);
+ l->output_gpu = cuda_make_array(0, l->batch*out_h*out_w*l->n);
#endif
}
@@ -181,8 +188,6 @@
gradient_array(l.output, m*k*l.batch, l.activation, l.delta);
backward_bias(l.bias_updates, l.delta, l.batch, l.n, k);
- if(state.delta) memset(state.delta, 0, l.batch*l.h*l.w*l.c*sizeof(float));
-
for(i = 0; i < l.batch; ++i){
float *a = l.delta + i*m*k;
float *b = l.col_image;
@@ -226,12 +231,37 @@
return float_to_image(w,h,c,l.filters+i*h*w*c);
}
+void rgbgr_filters(convolutional_layer l)
+{
+ int i;
+ for(i = 0; i < l.n; ++i){
+ image im = get_convolutional_filter(l, i);
+ if (im.c == 3) {
+ rgbgr_image(im);
+ }
+ }
+}
+
+void rescale_filters(convolutional_layer l, float scale, float trans)
+{
+ int i;
+ for(i = 0; i < l.n; ++i){
+ image im = get_convolutional_filter(l, i);
+ if (im.c == 3) {
+ scale_image(im, scale);
+ float sum = sum_array(im.data, im.w*im.h*im.c);
+ l.biases[i] += sum*trans;
+ }
+ }
+}
+
image *get_filters(convolutional_layer l)
{
image *filters = calloc(l.n, sizeof(image));
int i;
for(i = 0; i < l.n; ++i){
filters[i] = copy_image(get_convolutional_filter(l, i));
+ normalize_image(filters[i]);
}
return filters;
}
--
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