From 1b5afb45838e603fa6780762eb8cc59246dc2d81 Mon Sep 17 00:00:00 2001
From: IlyaOvodov <b@ovdv.ru>
Date: Tue, 08 May 2018 11:09:35 +0000
Subject: [PATCH] Output improvements for detector results: When printing detector results, output was done in random order, obfuscating results for interpreting. Now: 1. Text output includes coordinates of rects in (left,right,top,bottom in pixels) along with label and score 2. Text output is sorted by rect lefts to simplify finding appropriate rects on image 3. If several class probs are > thresh for some detection, the most probable is written first and coordinates for others are not repeated 4. Rects are imprinted in image in order by their best class prob, so most probable rects are always on top and not overlayed by less probable ones 5. Most probable label for rect is always written first Also: 6. Message about low GPU memory include required amount
---
src/rnn.c | 437 ++++++++++++++++++++++++++++++++++++++++++++++++-----
1 files changed, 391 insertions(+), 46 deletions(-)
diff --git a/src/rnn.c b/src/rnn.c
index d3e7e51..eca6f55 100644
--- a/src/rnn.c
+++ b/src/rnn.c
@@ -1,6 +1,7 @@
#include "network.h"
#include "cost_layer.h"
#include "utils.h"
+#include "blas.h"
#include "parser.h"
#ifdef OPENCV
@@ -12,16 +13,68 @@
float *y;
} float_pair;
-float_pair get_rnn_data(char *text, int len, int batch, int steps)
+int *read_tokenized_data(char *filename, size_t *read)
{
- float *x = calloc(batch * steps * 256, sizeof(float));
- float *y = calloc(batch * steps * 256, sizeof(float));
+ size_t size = 512;
+ size_t count = 0;
+ FILE *fp = fopen(filename, "r");
+ int *d = calloc(size, sizeof(int));
+ int n, one;
+ one = fscanf(fp, "%d", &n);
+ while(one == 1){
+ ++count;
+ if(count > size){
+ size = size*2;
+ d = realloc(d, size*sizeof(int));
+ }
+ d[count-1] = n;
+ one = fscanf(fp, "%d", &n);
+ }
+ fclose(fp);
+ d = realloc(d, count*sizeof(int));
+ *read = count;
+ return d;
+}
+
+char **read_tokens(char *filename, size_t *read)
+{
+ size_t size = 512;
+ size_t count = 0;
+ FILE *fp = fopen(filename, "r");
+ char **d = calloc(size, sizeof(char *));
+ char *line;
+ while((line=fgetl(fp)) != 0){
+ ++count;
+ if(count > size){
+ size = size*2;
+ d = realloc(d, size*sizeof(char *));
+ }
+ d[count-1] = line;
+ }
+ fclose(fp);
+ d = realloc(d, count*sizeof(char *));
+ *read = count;
+ return d;
+}
+
+float_pair get_rnn_token_data(int *tokens, size_t *offsets, int characters, size_t len, int batch, int steps)
+{
+ float *x = calloc(batch * steps * characters, sizeof(float));
+ float *y = calloc(batch * steps * characters, sizeof(float));
int i,j;
for(i = 0; i < batch; ++i){
- int index = rand() %(len - steps - 1);
for(j = 0; j < steps; ++j){
- x[(j*batch + i)*256 + text[index + j]] = 1;
- y[(j*batch + i)*256 + text[index + j + 1]] = 1;
+ int curr = tokens[(offsets[i])%len];
+ int next = tokens[(offsets[i] + 1)%len];
+
+ x[(j*batch + i)*characters + curr] = 1;
+ y[(j*batch + i)*characters + next] = 1;
+
+ offsets[i] = (offsets[i] + 1) % len;
+
+ if(curr >= characters || curr < 0 || next >= characters || next < 0){
+ error("Bad char");
+ }
}
}
float_pair p;
@@ -30,40 +83,102 @@
return p;
}
-void train_char_rnn(char *cfgfile, char *weightfile, char *filename)
+float_pair get_rnn_data(unsigned char *text, size_t *offsets, int characters, size_t len, int batch, int steps)
{
- FILE *fp = fopen(filename, "r");
- //FILE *fp = fopen("data/ab.txt", "r");
- //FILE *fp = fopen("data/grrm/asoiaf.txt", "r");
+ float *x = calloc(batch * steps * characters, sizeof(float));
+ float *y = calloc(batch * steps * characters, sizeof(float));
+ int i,j;
+ for(i = 0; i < batch; ++i){
+ for(j = 0; j < steps; ++j){
+ unsigned char curr = text[(offsets[i])%len];
+ unsigned char next = text[(offsets[i] + 1)%len];
- fseek(fp, 0, SEEK_END);
- size_t size = ftell(fp);
- fseek(fp, 0, SEEK_SET);
+ x[(j*batch + i)*characters + curr] = 1;
+ y[(j*batch + i)*characters + next] = 1;
- char *text = calloc(size, sizeof(char));
- fread(text, 1, size, fp);
- fclose(fp);
+ offsets[i] = (offsets[i] + 1) % len;
+
+ if(curr > 255 || curr <= 0 || next > 255 || next <= 0){
+ /*text[(index+j+2)%len] = 0;
+ printf("%ld %d %d %d %d\n", index, j, len, (int)text[index+j], (int)text[index+j+1]);
+ printf("%s", text+index);
+ */
+ error("Bad char");
+ }
+ }
+ }
+ float_pair p;
+ p.x = x;
+ p.y = y;
+ return p;
+}
+
+void reset_rnn_state(network net, int b)
+{
+ int i;
+ for (i = 0; i < net.n; ++i) {
+ #ifdef GPU
+ layer l = net.layers[i];
+ if(l.state_gpu){
+ fill_ongpu(l.outputs, 0, l.state_gpu + l.outputs*b, 1);
+ }
+ #endif
+ }
+}
+
+void train_char_rnn(char *cfgfile, char *weightfile, char *filename, int clear, int tokenized)
+{
+ srand(time(0));
+ unsigned char *text = 0;
+ int *tokens = 0;
+ size_t size;
+ if(tokenized){
+ tokens = read_tokenized_data(filename, &size);
+ } else {
+ FILE *fp = fopen(filename, "rb");
+
+ fseek(fp, 0, SEEK_END);
+ size = ftell(fp);
+ fseek(fp, 0, SEEK_SET);
+
+ text = calloc(size+1, sizeof(char));
+ fread(text, 1, size, fp);
+ fclose(fp);
+ }
char *backup_directory = "/home/pjreddie/backup/";
- srand(time(0));
- data_seed = time(0);
char *base = basecfg(cfgfile);
- printf("%s\n", base);
+ fprintf(stderr, "%s\n", base);
float avg_loss = -1;
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
- printf("Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
+
+ int inputs = get_network_input_size(net);
+ fprintf(stderr, "Learning Rate: %g, Momentum: %g, Decay: %g\n", net.learning_rate, net.momentum, net.decay);
int batch = net.batch;
int steps = net.time_steps;
+ if(clear) *net.seen = 0;
int i = (*net.seen)/net.batch;
+ int streams = batch/steps;
+ size_t *offsets = calloc(streams, sizeof(size_t));
+ int j;
+ for(j = 0; j < streams; ++j){
+ offsets[j] = rand_size_t()%size;
+ }
+
clock_t time;
while(get_current_batch(net) < net.max_batches){
i += 1;
time=clock();
- float_pair p = get_rnn_data(text, size, batch/steps, steps);
+ float_pair p;
+ if(tokenized){
+ p = get_rnn_token_data(tokens, offsets, inputs, size, streams, steps);
+ }else{
+ p = get_rnn_data(text, offsets, inputs, size, streams, steps);
+ }
float loss = train_network_datum(net, p.x, p.y) / (batch);
free(p.x);
@@ -71,8 +186,19 @@
if (avg_loss < 0) avg_loss = loss;
avg_loss = avg_loss*.9 + loss*.1;
- printf("%d: %f, %f avg, %f rate, %lf seconds\n", i, loss, avg_loss, get_current_rate(net), sec(clock()-time));
- if(i%100==0){
+ int chars = get_current_batch(net)*batch;
+ fprintf(stderr, "%d: %f, %f avg, %f rate, %lf seconds, %f epochs\n", i, loss, avg_loss, get_current_rate(net), sec(clock()-time), (float) chars/size);
+
+ for(j = 0; j < streams; ++j){
+ //printf("%d\n", j);
+ if(rand()%10 == 0){
+ //fprintf(stderr, "Reset\n");
+ offsets[j] = rand_size_t()%size;
+ reset_rnn_state(net, j);
+ }
+ }
+
+ if(i%1000==0){
char buff[256];
sprintf(buff, "%s/%s_%d.weights", backup_directory, base, i);
save_weights(net, buff);
@@ -88,44 +214,256 @@
save_weights(net, buff);
}
-void test_char_rnn(char *cfgfile, char *weightfile, int num, char *seed, float temp, int rseed)
+void print_symbol(int n, char **tokens){
+ if(tokens){
+ printf("%s ", tokens[n]);
+ } else {
+ printf("%c", n);
+ }
+}
+
+void test_char_rnn(char *cfgfile, char *weightfile, int num, char *seed, float temp, int rseed, char *token_file)
{
+ char **tokens = 0;
+ if(token_file){
+ size_t n;
+ tokens = read_tokens(token_file, &n);
+ }
+
srand(rseed);
char *base = basecfg(cfgfile);
- printf("%s\n", base);
+ fprintf(stderr, "%s\n", base);
network net = parse_network_cfg(cfgfile);
if(weightfile){
load_weights(&net, weightfile);
}
-
+ int inputs = get_network_input_size(net);
+
int i, j;
for(i = 0; i < net.n; ++i) net.layers[i].temperature = temp;
- char c;
+ int c = 0;
int len = strlen(seed);
- float *input = calloc(256, sizeof(float));
+ float *input = calloc(inputs, sizeof(float));
+
+ /*
+ fill_cpu(inputs, 0, input, 1);
+ for(i = 0; i < 10; ++i){
+ network_predict(net, input);
+ }
+ fill_cpu(inputs, 0, input, 1);
+ */
+
for(i = 0; i < len-1; ++i){
c = seed[i];
+ input[c] = 1;
+ network_predict(net, input);
+ input[c] = 0;
+ print_symbol(c, tokens);
+ }
+ if(len) c = seed[len-1];
+ print_symbol(c, tokens);
+ for(i = 0; i < num; ++i){
+ input[c] = 1;
+ float *out = network_predict(net, input);
+ input[c] = 0;
+ for(j = 32; j < 127; ++j){
+ //printf("%d %c %f\n",j, j, out[j]);
+ }
+ for(j = 0; j < inputs; ++j){
+ if (out[j] < .0001) out[j] = 0;
+ }
+ c = sample_array(out, inputs);
+ print_symbol(c, tokens);
+ }
+ printf("\n");
+}
+
+void test_tactic_rnn(char *cfgfile, char *weightfile, int num, float temp, int rseed, char *token_file)
+{
+ char **tokens = 0;
+ if(token_file){
+ size_t n;
+ tokens = read_tokens(token_file, &n);
+ }
+
+ srand(rseed);
+ char *base = basecfg(cfgfile);
+ fprintf(stderr, "%s\n", base);
+
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ int inputs = get_network_input_size(net);
+
+ int i, j;
+ for(i = 0; i < net.n; ++i) net.layers[i].temperature = temp;
+ int c = 0;
+ float *input = calloc(inputs, sizeof(float));
+ float *out = 0;
+
+ while((c = getc(stdin)) != EOF){
+ input[c] = 1;
+ out = network_predict(net, input);
+ input[c] = 0;
+ }
+ for(i = 0; i < num; ++i){
+ for(j = 0; j < inputs; ++j){
+ if (out[j] < .0001) out[j] = 0;
+ }
+ int next = sample_array(out, inputs);
+ if(c == '.' && next == '\n') break;
+ c = next;
+ print_symbol(c, tokens);
+
+ input[c] = 1;
+ out = network_predict(net, input);
+ input[c] = 0;
+ }
+ printf("\n");
+}
+
+void valid_tactic_rnn(char *cfgfile, char *weightfile, char *seed)
+{
+ char *base = basecfg(cfgfile);
+ fprintf(stderr, "%s\n", base);
+
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ int inputs = get_network_input_size(net);
+
+ int count = 0;
+ int words = 1;
+ int c;
+ int len = strlen(seed);
+ float *input = calloc(inputs, sizeof(float));
+ int i;
+ for(i = 0; i < len; ++i){
+ c = seed[i];
input[(int)c] = 1;
network_predict(net, input);
input[(int)c] = 0;
- printf("%c", c);
}
- c = seed[len-1];
- for(i = 0; i < num; ++i){
- printf("%c", c);
- float r = rand_uniform(0,1);
- float sum = 0;
- input[(int)c] = 1;
+ float sum = 0;
+ c = getc(stdin);
+ float log2 = log(2);
+ int in = 0;
+ while(c != EOF){
+ int next = getc(stdin);
+ if(next == EOF) break;
+ if(next < 0 || next >= 255) error("Out of range character");
+
+ input[c] = 1;
float *out = network_predict(net, input);
- input[(int)c] = 0;
- for(j = 0; j < 256; ++j){
- sum += out[j];
- if(sum > r) break;
+ input[c] = 0;
+
+ if(c == '.' && next == '\n') in = 0;
+ if(!in) {
+ if(c == '>' && next == '>'){
+ in = 1;
+ ++words;
+ }
+ c = next;
+ continue;
}
- c = j;
+ ++count;
+ sum += log(out[next])/log2;
+ c = next;
+ printf("%d %d Perplexity: %4.4f Word Perplexity: %4.4f\n", count, words, pow(2, -sum/count), pow(2, -sum/words));
}
- printf("\n");
+}
+
+void valid_char_rnn(char *cfgfile, char *weightfile, char *seed)
+{
+ char *base = basecfg(cfgfile);
+ fprintf(stderr, "%s\n", base);
+
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ int inputs = get_network_input_size(net);
+
+ int count = 0;
+ int words = 1;
+ int c;
+ int len = strlen(seed);
+ float *input = calloc(inputs, sizeof(float));
+ int i;
+ for(i = 0; i < len; ++i){
+ c = seed[i];
+ input[(int)c] = 1;
+ network_predict(net, input);
+ input[(int)c] = 0;
+ }
+ float sum = 0;
+ c = getc(stdin);
+ float log2 = log(2);
+ while(c != EOF){
+ int next = getc(stdin);
+ if(next == EOF) break;
+ if(next < 0 || next >= 255) error("Out of range character");
+ ++count;
+ if(next == ' ' || next == '\n' || next == '\t') ++words;
+ input[c] = 1;
+ float *out = network_predict(net, input);
+ input[c] = 0;
+ sum += log(out[next])/log2;
+ c = next;
+ printf("%d Perplexity: %4.4f Word Perplexity: %4.4f\n", count, pow(2, -sum/count), pow(2, -sum/words));
+ }
+}
+
+void vec_char_rnn(char *cfgfile, char *weightfile, char *seed)
+{
+ char *base = basecfg(cfgfile);
+ fprintf(stderr, "%s\n", base);
+
+ network net = parse_network_cfg(cfgfile);
+ if(weightfile){
+ load_weights(&net, weightfile);
+ }
+ int inputs = get_network_input_size(net);
+
+ int c;
+ int seed_len = strlen(seed);
+ float *input = calloc(inputs, sizeof(float));
+ int i;
+ char *line;
+ while((line=fgetl(stdin)) != 0){
+ reset_rnn_state(net, 0);
+ for(i = 0; i < seed_len; ++i){
+ c = seed[i];
+ input[(int)c] = 1;
+ network_predict(net, input);
+ input[(int)c] = 0;
+ }
+ strip(line);
+ int str_len = strlen(line);
+ for(i = 0; i < str_len; ++i){
+ c = line[i];
+ input[(int)c] = 1;
+ network_predict(net, input);
+ input[(int)c] = 0;
+ }
+ c = ' ';
+ input[(int)c] = 1;
+ network_predict(net, input);
+ input[(int)c] = 0;
+
+ layer l = net.layers[0];
+ #ifdef GPU
+ cuda_pull_array(l.output_gpu, l.output, l.outputs);
+ #endif
+ printf("%s", line);
+ for(i = 0; i < l.outputs; ++i){
+ printf(",%g", l.output[i]);
+ }
+ printf("\n");
+ }
}
void run_char_rnn(int argc, char **argv)
@@ -135,13 +473,20 @@
return;
}
char *filename = find_char_arg(argc, argv, "-file", "data/shakespeare.txt");
- char *seed = find_char_arg(argc, argv, "-seed", "\n");
- int len = find_int_arg(argc, argv, "-len", 100);
- float temp = find_float_arg(argc, argv, "-temp", 1);
+ char *seed = find_char_arg(argc, argv, "-seed", "\n\n");
+ int len = find_int_arg(argc, argv, "-len", 1000);
+ float temp = find_float_arg(argc, argv, "-temp", .7);
int rseed = find_int_arg(argc, argv, "-srand", time(0));
+ int clear = find_arg(argc, argv, "-clear");
+ int tokenized = find_arg(argc, argv, "-tokenized");
+ char *tokens = find_char_arg(argc, argv, "-tokens", 0);
char *cfg = argv[3];
char *weights = (argc > 4) ? argv[4] : 0;
- if(0==strcmp(argv[2], "train")) train_char_rnn(cfg, weights, filename);
- else if(0==strcmp(argv[2], "test")) test_char_rnn(cfg, weights, len, seed, temp, rseed);
+ if(0==strcmp(argv[2], "train")) train_char_rnn(cfg, weights, filename, clear, tokenized);
+ else if(0==strcmp(argv[2], "valid")) valid_char_rnn(cfg, weights, seed);
+ else if(0==strcmp(argv[2], "validtactic")) valid_tactic_rnn(cfg, weights, seed);
+ else if(0==strcmp(argv[2], "vec")) vec_char_rnn(cfg, weights, seed);
+ else if(0==strcmp(argv[2], "generate")) test_char_rnn(cfg, weights, len, seed, temp, rseed, tokens);
+ else if(0==strcmp(argv[2], "generatetactic")) test_tactic_rnn(cfg, weights, len, temp, rseed, tokens);
}
--
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