From d7286c273211ffeb1f56594f863d1ee9922be6d4 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Thu, 07 Nov 2013 00:09:41 +0000
Subject: [PATCH] Loading may or may not work. But probably.
---
src/convolutional_layer.c | 49 +++++++++++++++++++++++++++++--------------------
1 files changed, 29 insertions(+), 20 deletions(-)
diff --git a/src/convolutional_layer.c b/src/convolutional_layer.c
index f83622b..7478158 100644
--- a/src/convolutional_layer.c
+++ b/src/convolutional_layer.c
@@ -10,20 +10,20 @@
return (x>=0);
}
-convolutional_layer make_convolutional_layer(int h, int w, int c, int n, int size, int stride)
+convolutional_layer *make_convolutional_layer(int h, int w, int c, int n, int size, int stride)
{
int i;
- convolutional_layer layer;
- layer.n = n;
- layer.stride = stride;
- layer.kernels = calloc(n, sizeof(image));
- layer.kernel_updates = calloc(n, sizeof(image));
+ convolutional_layer *layer = calloc(1, sizeof(convolutional_layer));
+ layer->n = n;
+ layer->stride = stride;
+ layer->kernels = calloc(n, sizeof(image));
+ layer->kernel_updates = calloc(n, sizeof(image));
for(i = 0; i < n; ++i){
- layer.kernels[i] = make_random_kernel(size, c);
- layer.kernel_updates[i] = make_random_kernel(size, c);
+ layer->kernels[i] = make_random_kernel(size, c);
+ layer->kernel_updates[i] = make_random_kernel(size, c);
}
- layer.output = make_image((h-1)/stride+1, (w-1)/stride+1, n);
- layer.upsampled = make_image(h,w,n);
+ layer->output = make_image((h-1)/stride+1, (w-1)/stride+1, n);
+ layer->upsampled = make_image(h,w,n);
return layer;
}
@@ -33,12 +33,12 @@
for(i = 0; i < layer.n; ++i){
convolve(input, layer.kernels[i], layer.stride, i, layer.output);
}
- for(i = 0; i < input.h*input.w*input.c; ++i){
- input.data[i] = convolution_activation(input.data[i]);
+ for(i = 0; i < layer.output.h*layer.output.w*layer.output.c; ++i){
+ layer.output.data[i] = convolution_activation(layer.output.data[i]);
}
}
-void backpropagate_layer(image input, convolutional_layer layer)
+void backpropagate_convolutional_layer(image input, convolutional_layer layer)
{
int i;
zero_image(input);
@@ -47,7 +47,7 @@
}
}
-void backpropagate_layer_convolve(image input, convolutional_layer layer)
+void backpropagate_convolutional_layer_convolve(image input, convolutional_layer layer)
{
int i,j;
for(i = 0; i < layer.n; ++i){
@@ -67,20 +67,29 @@
}
}
-void error_convolutional_layer(image input, convolutional_layer layer)
+void learn_convolutional_layer(image input, convolutional_layer layer)
{
int i;
for(i = 0; i < layer.n; ++i){
kernel_update(input, layer.kernel_updates[i], layer.stride, i, layer.output);
}
image old_input = copy_image(input);
- zero_image(input);
- for(i = 0; i < layer.n; ++i){
- back_convolve(input, layer.kernels[i], layer.stride, i, layer.output);
- }
+ backpropagate_convolutional_layer(input, layer);
for(i = 0; i < input.h*input.w*input.c; ++i){
- input.data[i] = input.data[i]*convolution_gradient(input.data[i]);
+ input.data[i] *= convolution_gradient(old_input.data[i]);
}
free_image(old_input);
}
+void update_convolutional_layer(convolutional_layer layer, double step)
+{
+ int i,j;
+ for(i = 0; i < layer.n; ++i){
+ int pixels = layer.kernels[i].h*layer.kernels[i].w*layer.kernels[i].c;
+ for(j = 0; j < pixels; ++j){
+ layer.kernels[i].data[j] += step*layer.kernel_updates[i].data[j];
+ }
+ zero_image(layer.kernel_updates[i]);
+ }
+}
+
--
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