From 2db9fbef2bd7d35a547d0018a9850f6b249c524f Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 13 Nov 2013 18:50:38 +0000
Subject: [PATCH] Parsing, image loading, lots of stuff
---
src/network.c | 191 +++++++++++++++++++++++++++++++++++++++++++----
1 files changed, 175 insertions(+), 16 deletions(-)
diff --git a/src/network.c b/src/network.c
index e55535c..a77d607 100644
--- a/src/network.c
+++ b/src/network.c
@@ -1,48 +1,207 @@
+#include <stdio.h>
#include "network.h"
#include "image.h"
+#include "data.h"
#include "connected_layer.h"
#include "convolutional_layer.h"
#include "maxpool_layer.h"
-void run_network(image input, network net)
+network make_network(int n)
+{
+ network net;
+ net.n = n;
+ net.layers = calloc(net.n, sizeof(void *));
+ net.types = calloc(net.n, sizeof(LAYER_TYPE));
+ return net;
+}
+
+void forward_network(network net, double *input)
{
int i;
- double *input_d = 0;
for(i = 0; i < net.n; ++i){
if(net.types[i] == CONVOLUTIONAL){
convolutional_layer layer = *(convolutional_layer *)net.layers[i];
- run_convolutional_layer(input, layer);
+ forward_convolutional_layer(layer, input);
input = layer.output;
- input_d = layer.output.data;
}
else if(net.types[i] == CONNECTED){
connected_layer layer = *(connected_layer *)net.layers[i];
- run_connected_layer(input_d, layer);
- input_d = layer.output;
+ forward_connected_layer(layer, input);
+ input = layer.output;
}
else if(net.types[i] == MAXPOOL){
maxpool_layer layer = *(maxpool_layer *)net.layers[i];
- run_maxpool_layer(input, layer);
+ forward_maxpool_layer(layer, input);
input = layer.output;
- input_d = layer.output.data;
}
}
}
+void update_network(network net, double step)
+{
+ int i;
+ for(i = 0; i < net.n; ++i){
+ if(net.types[i] == CONVOLUTIONAL){
+ convolutional_layer layer = *(convolutional_layer *)net.layers[i];
+ update_convolutional_layer(layer, step);
+ }
+ else if(net.types[i] == MAXPOOL){
+ //maxpool_layer layer = *(maxpool_layer *)net.layers[i];
+ }
+ else if(net.types[i] == CONNECTED){
+ connected_layer layer = *(connected_layer *)net.layers[i];
+ update_connected_layer(layer, step, .3, 0);
+ }
+ }
+}
+
+double *get_network_output_layer(network net, int i)
+{
+ if(net.types[i] == CONVOLUTIONAL){
+ convolutional_layer layer = *(convolutional_layer *)net.layers[i];
+ return layer.output;
+ } else if(net.types[i] == MAXPOOL){
+ maxpool_layer layer = *(maxpool_layer *)net.layers[i];
+ return layer.output;
+ } else if(net.types[i] == CONNECTED){
+ connected_layer layer = *(connected_layer *)net.layers[i];
+ return layer.output;
+ }
+ return 0;
+}
+double *get_network_output(network net)
+{
+ return get_network_output_layer(net, net.n-1);
+}
+
+double *get_network_delta_layer(network net, int i)
+{
+ if(net.types[i] == CONVOLUTIONAL){
+ convolutional_layer layer = *(convolutional_layer *)net.layers[i];
+ return layer.delta;
+ } else if(net.types[i] == MAXPOOL){
+ maxpool_layer layer = *(maxpool_layer *)net.layers[i];
+ return layer.delta;
+ } else if(net.types[i] == CONNECTED){
+ connected_layer layer = *(connected_layer *)net.layers[i];
+ return layer.delta;
+ }
+ return 0;
+}
+
+double *get_network_delta(network net)
+{
+ return get_network_delta_layer(net, net.n-1);
+}
+
+void learn_network(network net, double *input)
+{
+ int i;
+ double *prev_input;
+ double *prev_delta;
+ for(i = net.n-1; i >= 0; --i){
+ if(i == 0){
+ prev_input = input;
+ prev_delta = 0;
+ }else{
+ prev_input = get_network_output_layer(net, i-1);
+ prev_delta = get_network_delta_layer(net, i-1);
+ }
+ if(net.types[i] == CONVOLUTIONAL){
+ convolutional_layer layer = *(convolutional_layer *)net.layers[i];
+ learn_convolutional_layer(layer, prev_input);
+ if(i != 0) backward_convolutional_layer(layer, prev_input, prev_delta);
+ }
+ else if(net.types[i] == MAXPOOL){
+ //maxpool_layer layer = *(maxpool_layer *)net.layers[i];
+ }
+ else if(net.types[i] == CONNECTED){
+ connected_layer layer = *(connected_layer *)net.layers[i];
+ learn_connected_layer(layer, prev_input);
+ if(i != 0) backward_connected_layer(layer, prev_input, prev_delta);
+ }
+ }
+}
+
+void train_network_batch(network net, batch b)
+{
+ int i,j;
+ int k = get_network_output_size(net);
+ int correct = 0;
+ for(i = 0; i < b.n; ++i){
+ forward_network(net, b.images[i].data);
+ image o = get_network_image(net);
+ double *output = get_network_output(net);
+ double *delta = get_network_delta(net);
+ for(j = 0; j < k; ++j){
+ //printf("%f %f\n", b.truth[i][j], output[j]);
+ delta[j] = b.truth[i][j]-output[j];
+ if(fabs(delta[j]) < .5) ++correct;
+ //printf("%f\n", output[j]);
+ }
+ learn_network(net, b.images[i].data);
+ update_network(net, .00001);
+ }
+ printf("Accuracy: %f\n", (double)correct/b.n);
+}
+
+int get_network_output_size_layer(network net, int i)
+{
+ if(net.types[i] == CONVOLUTIONAL){
+ convolutional_layer layer = *(convolutional_layer *)net.layers[i];
+ image output = get_convolutional_image(layer);
+ return output.h*output.w*output.c;
+ }
+ else if(net.types[i] == MAXPOOL){
+ maxpool_layer layer = *(maxpool_layer *)net.layers[i];
+ image output = get_maxpool_image(layer);
+ return output.h*output.w*output.c;
+ }
+ else if(net.types[i] == CONNECTED){
+ connected_layer layer = *(connected_layer *)net.layers[i];
+ return layer.outputs;
+ }
+ return 0;
+}
+
+int get_network_output_size(network net)
+{
+ int i = net.n-1;
+ return get_network_output_size_layer(net, i);
+}
+
+image get_network_image_layer(network net, int i)
+{
+ if(net.types[i] == CONVOLUTIONAL){
+ convolutional_layer layer = *(convolutional_layer *)net.layers[i];
+ return get_convolutional_image(layer);
+ }
+ else if(net.types[i] == MAXPOOL){
+ maxpool_layer layer = *(maxpool_layer *)net.layers[i];
+ return get_maxpool_image(layer);
+ }
+ return make_image(0,0,0);
+}
+
image get_network_image(network net)
{
int i;
for(i = net.n-1; i >= 0; --i){
- if(net.types[i] == CONVOLUTIONAL){
- convolutional_layer layer = *(convolutional_layer *)net.layers[i];
- return layer.output;
- }
- else if(net.types[i] == MAXPOOL){
- maxpool_layer layer = *(maxpool_layer *)net.layers[i];
- return layer.output;
- }
+ image m = get_network_image_layer(net, i);
+ if(m.h != 0) return m;
}
return make_image(1,1,1);
}
+void visualize_network(network net)
+{
+ int i;
+ for(i = 0; i < 1; ++i){
+ if(net.types[i] == CONVOLUTIONAL){
+ convolutional_layer layer = *(convolutional_layer *)net.layers[i];
+ visualize_convolutional_layer(layer);
+ }
+ }
+}
+
--
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