From ae43c2bc32fbb838bfebeeaf2c2b058ccab5c83c Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@burninator.cs.washington.edu>
Date: Thu, 23 Jun 2016 05:31:14 +0000
Subject: [PATCH] hi
---
src/darknet.c | 265 +++++++++++++++++++++++++++++++++++++++++++---------
1 files changed, 219 insertions(+), 46 deletions(-)
diff --git a/src/darknet.c b/src/darknet.c
index f896efe..aee9521 100644
--- a/src/darknet.c
+++ b/src/darknet.c
@@ -5,49 +5,28 @@
#include "parser.h"
#include "utils.h"
#include "cuda.h"
+#include "blas.h"
+#include "connected_layer.h"
-#define _GNU_SOURCE
-#include <fenv.h>
+#ifdef OPENCV
+#include "opencv2/highgui/highgui_c.h"
+#endif
extern void run_imagenet(int argc, char **argv);
-extern void run_detection(int argc, char **argv);
+extern void run_yolo(int argc, char **argv);
+extern void run_coco(int argc, char **argv);
extern void run_writing(int argc, char **argv);
extern void run_captcha(int argc, char **argv);
-
-void del_arg(int argc, char **argv, int index)
-{
- int i;
- for(i = index; i < argc-1; ++i) argv[i] = argv[i+1];
- argv[i] = 0;
-}
-
-int find_arg(int argc, char* argv[], char *arg)
-{
- int i;
- for(i = 0; i < argc; ++i) {
- if(!argv[i]) continue;
- if(0==strcmp(argv[i], arg)) {
- del_arg(argc, argv, i);
- return 1;
- }
- }
- return 0;
-}
-
-int find_int_arg(int argc, char **argv, char *arg, int def)
-{
- int i;
- for(i = 0; i < argc-1; ++i){
- if(!argv[i]) continue;
- if(0==strcmp(argv[i], arg)){
- def = atoi(argv[i+1]);
- del_arg(argc, argv, i);
- del_arg(argc, argv, i);
- break;
- }
- }
- return def;
-}
+extern void run_nightmare(int argc, char **argv);
+extern void run_dice(int argc, char **argv);
+extern void run_compare(int argc, char **argv);
+extern void run_classifier(int argc, char **argv);
+extern void run_char_rnn(int argc, char **argv);
+extern void run_vid_rnn(int argc, char **argv);
+extern void run_tag(int argc, char **argv);
+extern void run_cifar(int argc, char **argv);
+extern void run_go(int argc, char **argv);
+extern void run_art(int argc, char **argv);
void change_rate(char *filename, float scale, float add)
{
@@ -63,20 +42,113 @@
fclose(fp);
}
+void average(int argc, char *argv[])
+{
+ char *cfgfile = argv[2];
+ char *outfile = argv[3];
+ gpu_index = -1;
+ network net = parse_network_cfg(cfgfile);
+ network sum = parse_network_cfg(cfgfile);
+
+ char *weightfile = argv[4];
+ load_weights(&sum, weightfile);
+
+ int i, j;
+ int n = argc - 5;
+ for(i = 0; i < n; ++i){
+ weightfile = argv[i+5];
+ load_weights(&net, weightfile);
+ for(j = 0; j < net.n; ++j){
+ layer l = net.layers[j];
+ layer out = sum.layers[j];
+ if(l.type == CONVOLUTIONAL){
+ int num = l.n*l.c*l.size*l.size;
+ axpy_cpu(l.n, 1, l.biases, 1, out.biases, 1);
+ axpy_cpu(num, 1, l.filters, 1, out.filters, 1);
+ }
+ if(l.type == CONNECTED){
+ axpy_cpu(l.outputs, 1, l.biases, 1, out.biases, 1);
+ axpy_cpu(l.outputs*l.inputs, 1, l.weights, 1, out.weights, 1);
+ }
+ }
+ }
+ n = n+1;
+ for(j = 0; j < net.n; ++j){
+ layer l = sum.layers[j];
+ if(l.type == CONVOLUTIONAL){
+ int num = l.n*l.c*l.size*l.size;
+ scal_cpu(l.n, 1./n, l.biases, 1);
+ scal_cpu(num, 1./n, l.filters, 1);
+ }
+ if(l.type == CONNECTED){
+ scal_cpu(l.outputs, 1./n, l.biases, 1);
+ scal_cpu(l.outputs*l.inputs, 1./n, l.weights, 1);
+ }
+ }
+ save_weights(sum, outfile);
+}
+
+void operations(char *cfgfile)
+{
+ gpu_index = -1;
+ network net = parse_network_cfg(cfgfile);
+ int i;
+ long ops = 0;
+ for(i = 0; i < net.n; ++i){
+ layer l = net.layers[i];
+ if(l.type == CONVOLUTIONAL){
+ ops += 2 * l.n * l.size*l.size*l.c * l.out_h*l.out_w;
+ } else if(l.type == CONNECTED){
+ ops += 2 * l.inputs * l.outputs;
+ }
+ }
+ printf("Floating Point Operations: %ld\n", ops);
+}
+
void partial(char *cfgfile, char *weightfile, char *outfile, int max)
{
+ gpu_index = -1;
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights_upto(&net, weightfile, max);
}
+ *net.seen = 0;
+ save_weights_upto(net, outfile, max);
+}
+
+void stacked(char *cfgfile, char *weightfile, char *outfile)
+{
+ gpu_index = -1;
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
net.seen = 0;
- save_weights(net, outfile);
+ save_weights_double(net, outfile);
}
#include "convolutional_layer.h"
-void rgbgr_filters(convolutional_layer l);
+void rescale_net(char *cfgfile, char *weightfile, char *outfile)
+{
+ gpu_index = -1;
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ int i;
+ for(i = 0; i < net.n; ++i){
+ layer l = net.layers[i];
+ if(l.type == CONVOLUTIONAL){
+ rescale_filters(l, 2, -.5);
+ break;
+ }
+ }
+ save_weights(net, outfile);
+}
+
void rgbgr_net(char *cfgfile, char *weightfile, char *outfile)
{
+ gpu_index = -1;
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
@@ -92,6 +164,66 @@
save_weights(net, outfile);
}
+void normalize_net(char *cfgfile, char *weightfile, char *outfile)
+{
+ gpu_index = -1;
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ int i, j;
+ for(i = 0; i < net.n; ++i){
+ layer l = net.layers[i];
+ if(l.type == CONVOLUTIONAL){
+ net.layers[i].batch_normalize=1;
+ net.layers[i].scales = calloc(l.n, sizeof(float));
+ for(j = 0; j < l.n; ++j){
+ net.layers[i].scales[i] = 1;
+ }
+ net.layers[i].rolling_mean = calloc(l.n, sizeof(float));
+ net.layers[i].rolling_variance = calloc(l.n, sizeof(float));
+ }
+ }
+ save_weights(net, outfile);
+}
+
+void denormalize_net(char *cfgfile, char *weightfile, char *outfile)
+{
+ gpu_index = -1;
+ network net = parse_network_cfg(cfgfile);
+ if (weightfile) {
+ load_weights(&net, weightfile);
+ }
+ int i;
+ for (i = 0; i < net.n; ++i) {
+ layer l = net.layers[i];
+ if (l.type == CONVOLUTIONAL && l.batch_normalize) {
+ denormalize_convolutional_layer(l);
+ net.layers[i].batch_normalize=0;
+ }
+ if (l.type == CONNECTED && l.batch_normalize) {
+ denormalize_connected_layer(l);
+ net.layers[i].batch_normalize=0;
+ }
+ if (l.type == GRU && l.batch_normalize) {
+ denormalize_connected_layer(*l.input_z_layer);
+ denormalize_connected_layer(*l.input_r_layer);
+ denormalize_connected_layer(*l.input_h_layer);
+ denormalize_connected_layer(*l.state_z_layer);
+ denormalize_connected_layer(*l.state_r_layer);
+ denormalize_connected_layer(*l.state_h_layer);
+ l.input_z_layer->batch_normalize = 0;
+ l.input_r_layer->batch_normalize = 0;
+ l.input_h_layer->batch_normalize = 0;
+ l.state_z_layer->batch_normalize = 0;
+ l.state_r_layer->batch_normalize = 0;
+ l.state_h_layer->batch_normalize = 0;
+ net.layers[i].batch_normalize=0;
+ }
+ }
+ save_weights(net, outfile);
+}
+
void visualize(char *cfgfile, char *weightfile)
{
network net = parse_network_cfg(cfgfile);
@@ -99,9 +231,9 @@
load_weights(&net, weightfile);
}
visualize_network(net);
- #ifdef OPENCV
+#ifdef OPENCV
cvWaitKey(0);
- #endif
+#endif
}
int main(int argc, char **argv)
@@ -114,32 +246,73 @@
return 0;
}
gpu_index = find_int_arg(argc, argv, "-i", 0);
- if(find_arg(argc, argv, "-nogpu")) gpu_index = -1;
+ if(find_arg(argc, argv, "-nogpu")) {
+ gpu_index = -1;
+ }
#ifndef GPU
gpu_index = -1;
#else
if(gpu_index >= 0){
- cudaSetDevice(gpu_index);
+ cudaError_t status = cudaSetDevice(gpu_index);
+ check_error(status);
}
#endif
if(0==strcmp(argv[1], "imagenet")){
run_imagenet(argc, argv);
- } else if (0 == strcmp(argv[1], "detection")){
- run_detection(argc, argv);
+ } else if (0 == strcmp(argv[1], "average")){
+ average(argc, argv);
+ } else if (0 == strcmp(argv[1], "yolo")){
+ run_yolo(argc, argv);
+ } else if (0 == strcmp(argv[1], "cifar")){
+ run_cifar(argc, argv);
+ } else if (0 == strcmp(argv[1], "go")){
+ run_go(argc, argv);
+ } else if (0 == strcmp(argv[1], "rnn")){
+ run_char_rnn(argc, argv);
+ } else if (0 == strcmp(argv[1], "vid")){
+ run_vid_rnn(argc, argv);
+ } else if (0 == strcmp(argv[1], "coco")){
+ run_coco(argc, argv);
+ } else if (0 == strcmp(argv[1], "classifier")){
+ run_classifier(argc, argv);
+ } else if (0 == strcmp(argv[1], "art")){
+ run_art(argc, argv);
+ } else if (0 == strcmp(argv[1], "tag")){
+ run_tag(argc, argv);
+ } else if (0 == strcmp(argv[1], "compare")){
+ run_compare(argc, argv);
+ } else if (0 == strcmp(argv[1], "dice")){
+ run_dice(argc, argv);
} else if (0 == strcmp(argv[1], "writing")){
run_writing(argc, argv);
+ } else if (0 == strcmp(argv[1], "3d")){
+ composite_3d(argv[2], argv[3], argv[4]);
} else if (0 == strcmp(argv[1], "test")){
test_resize(argv[2]);
} else if (0 == strcmp(argv[1], "captcha")){
run_captcha(argc, argv);
+ } else if (0 == strcmp(argv[1], "nightmare")){
+ run_nightmare(argc, argv);
} else if (0 == strcmp(argv[1], "change")){
change_rate(argv[2], atof(argv[3]), (argc > 4) ? atof(argv[4]) : 0);
} else if (0 == strcmp(argv[1], "rgbgr")){
rgbgr_net(argv[2], argv[3], argv[4]);
+ } else if (0 == strcmp(argv[1], "denormalize")){
+ denormalize_net(argv[2], argv[3], argv[4]);
+ } else if (0 == strcmp(argv[1], "normalize")){
+ normalize_net(argv[2], argv[3], argv[4]);
+ } else if (0 == strcmp(argv[1], "rescale")){
+ rescale_net(argv[2], argv[3], argv[4]);
+ } else if (0 == strcmp(argv[1], "ops")){
+ operations(argv[2]);
} else if (0 == strcmp(argv[1], "partial")){
partial(argv[2], argv[3], argv[4], atoi(argv[5]));
+ } else if (0 == strcmp(argv[1], "average")){
+ average(argc, argv);
+ } else if (0 == strcmp(argv[1], "stacked")){
+ stacked(argv[2], argv[3], argv[4]);
} else if (0 == strcmp(argv[1], "visualize")){
visualize(argv[2], (argc > 3) ? argv[3] : 0);
} else if (0 == strcmp(argv[1], "imtest")){
--
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