From a360f694093f7748e3232f4ed74d40446d735fc3 Mon Sep 17 00:00:00 2001
From: Alexey <AlexeyAB@users.noreply.github.com>
Date: Wed, 01 Mar 2017 12:29:50 +0000
Subject: [PATCH] Readme.md - When should I stop training
---
src/parser.c | 106 +++++++++++++++++++++++++----------------------------
1 files changed, 50 insertions(+), 56 deletions(-)
diff --git a/src/parser.c b/src/parser.c
index 09eef42..3f39a13 100644
--- a/src/parser.c
+++ b/src/parser.c
@@ -2,32 +2,32 @@
#include <string.h>
#include <stdlib.h>
-#include "blas.h"
-#include "parser.h"
-#include "assert.h"
-#include "activations.h"
-#include "crop_layer.h"
-#include "cost_layer.h"
-#include "convolutional_layer.h"
#include "activation_layer.h"
-#include "normalization_layer.h"
-#include "batchnorm_layer.h"
-#include "connected_layer.h"
-#include "rnn_layer.h"
-#include "gru_layer.h"
-#include "crnn_layer.h"
-#include "maxpool_layer.h"
-#include "reorg_layer.h"
-#include "softmax_layer.h"
-#include "dropout_layer.h"
-#include "detection_layer.h"
-#include "region_layer.h"
+#include "activations.h"
+#include "assert.h"
#include "avgpool_layer.h"
+#include "batchnorm_layer.h"
+#include "blas.h"
+#include "connected_layer.h"
+#include "convolutional_layer.h"
+#include "cost_layer.h"
+#include "crnn_layer.h"
+#include "crop_layer.h"
+#include "detection_layer.h"
+#include "dropout_layer.h"
+#include "gru_layer.h"
+#include "list.h"
#include "local_layer.h"
+#include "maxpool_layer.h"
+#include "normalization_layer.h"
+#include "option_list.h"
+#include "parser.h"
+#include "region_layer.h"
+#include "reorg_layer.h"
+#include "rnn_layer.h"
#include "route_layer.h"
#include "shortcut_layer.h"
-#include "list.h"
-#include "option_list.h"
+#include "softmax_layer.h"
#include "utils.h"
typedef struct{
@@ -232,30 +232,12 @@
return layer;
}
-int *read_map(char *filename)
-{
- int n = 0;
- int *map = 0;
- char *str;
- FILE *file = fopen(filename, "r");
- if(!file) file_error(filename);
- while((str=fgetl(file))){
- ++n;
- map = realloc(map, n*sizeof(int));
- map[n-1] = atoi(str);
- }
- return map;
-}
-
layer parse_region(list *options, size_params params)
{
int coords = option_find_int(options, "coords", 4);
int classes = option_find_int(options, "classes", 20);
int num = option_find_int(options, "num", 1);
- params.w = option_find_int(options, "side", params.w);
- params.h = option_find_int(options, "side", params.h);
-
layer l = make_region_layer(params.batch, params.w, params.h, num, classes, coords);
assert(l.outputs == params.inputs);
@@ -267,6 +249,11 @@
l.jitter = option_find_float(options, "jitter", .2);
l.rescore = option_find_int_quiet(options, "rescore",0);
+ l.thresh = option_find_float(options, "thresh", .5);
+ l.classfix = option_find_int_quiet(options, "classfix", 0);
+ l.absolute = option_find_int_quiet(options, "absolute", 0);
+ l.random = option_find_int_quiet(options, "random", 0);
+
l.coord_scale = option_find_float(options, "coord_scale", 1);
l.object_scale = option_find_float(options, "object_scale", 1);
l.noobject_scale = option_find_float(options, "noobject_scale", 1);
@@ -355,6 +342,7 @@
layer parse_reorg(list *options, size_params params)
{
int stride = option_find_int(options, "stride",1);
+ int reverse = option_find_int_quiet(options, "reverse",0);
int batch,h,w,c;
h = params.h;
@@ -363,7 +351,7 @@
batch=params.batch;
if(!(h && w && c)) error("Layer before reorg layer must output image.");
- layer layer = make_reorg_layer(batch,w,h,c,stride);
+ layer layer = make_reorg_layer(batch,w,h,c,stride,reverse);
return layer;
}
@@ -619,9 +607,10 @@
n = n->next;
int count = 0;
free_section(s);
+ fprintf(stderr, "layer filters size input output\n");
while(n){
params.index = count;
- fprintf(stderr, "%d: ", count);
+ fprintf(stderr, "%5d ", count);
s = (section *)n->val;
options = s->options;
layer l = {0};
@@ -837,7 +826,7 @@
}
#endif
fprintf(stderr, "Saving weights to %s\n", filename);
- FILE *fp = fopen(filename, "w");
+ FILE *fp = fopen(filename, "wb");
if(!fp) file_error(filename);
int major = 0;
@@ -977,23 +966,28 @@
//return;
}
int num = l.n*l.c*l.size*l.size;
- if(0){
- fread(l.biases + ((l.n != 1374)?0:5), sizeof(float), l.n, fp);
- if (l.batch_normalize && (!l.dontloadscales)){
- fread(l.scales + ((l.n != 1374)?0:5), sizeof(float), l.n, fp);
- fread(l.rolling_mean + ((l.n != 1374)?0:5), sizeof(float), l.n, fp);
- fread(l.rolling_variance + ((l.n != 1374)?0:5), sizeof(float), l.n, fp);
+ fread(l.biases, sizeof(float), l.n, fp);
+ if (l.batch_normalize && (!l.dontloadscales)){
+ fread(l.scales, sizeof(float), l.n, fp);
+ fread(l.rolling_mean, sizeof(float), l.n, fp);
+ fread(l.rolling_variance, sizeof(float), l.n, fp);
+ if(0){
+ int i;
+ for(i = 0; i < l.n; ++i){
+ printf("%g, ", l.rolling_mean[i]);
+ }
+ printf("\n");
+ for(i = 0; i < l.n; ++i){
+ printf("%g, ", l.rolling_variance[i]);
+ }
+ printf("\n");
}
- fread(l.weights + ((l.n != 1374)?0:5*l.c*l.size*l.size), sizeof(float), num, fp);
- }else{
- fread(l.biases, sizeof(float), l.n, fp);
- if (l.batch_normalize && (!l.dontloadscales)){
- fread(l.scales, sizeof(float), l.n, fp);
- fread(l.rolling_mean, sizeof(float), l.n, fp);
- fread(l.rolling_variance, sizeof(float), l.n, fp);
+ if(0){
+ fill_cpu(l.n, 0, l.rolling_mean, 1);
+ fill_cpu(l.n, 0, l.rolling_variance, 1);
}
- fread(l.weights, sizeof(float), num, fp);
}
+ fread(l.weights, sizeof(float), num, fp);
if(l.adam){
fread(l.m, sizeof(float), num, fp);
fread(l.v, sizeof(float), num, fp);
--
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