From c123f320fcc2212f1d3b59a4d3d2ae6be71cf1e6 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Sun, 04 Mar 2018 20:41:23 +0000
Subject: [PATCH] Show avg-loss chart during Training, if compiled with OpenCV. Use -dont_show to disable.
---
src/rnn.c | 398 +++++++++++++++++++++++++++++++++++++++++++++++++-------
1 files changed, 348 insertions(+), 50 deletions(-)
diff --git a/src/rnn.c b/src/rnn.c
index 43cac5a..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
@@ -12,29 +13,66 @@
float *y;
} float_pair;
-float_pair get_rnn_data(unsigned char *text, int characters, int len, int batch, int steps)
+int *read_tokenized_data(char *filename, size_t *read)
+{
+ 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);
- /*
- int done = 1;
- while(!done){
- index = rand() %(len - steps - 1);
- while(index < len-steps-1 && text[index++] != '\n');
- if (index < len-steps-1) done = 1;
- }
- */
for(j = 0; j < steps; ++j){
- x[(j*batch + i)*characters + text[index + j]] = 1;
- y[(j*batch + i)*characters + text[index + j + 1]] = 1;
+ int curr = tokens[(offsets[i])%len];
+ int next = tokens[(offsets[i] + 1)%len];
- if(text[index+j] > 255 || text[index+j] <= 0 || text[index+j+1] > 255 || text[index+j+1] <= 0){
- text[index+j+2] = 0;
- printf("%d %d %d %d %d\n", index, j, len, (int)text[index+j], (int)text[index+j+1]);
- printf("%s", text+index);
+ 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");
}
}
@@ -45,21 +83,70 @@
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, "rb");
+ 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;
- unsigned char *text = calloc(size+1, 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);
fprintf(stderr, "%s\n", base);
float avg_loss = -1;
@@ -67,17 +154,31 @@
if(weightfile){
load_weights(&net, weightfile);
}
+
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, inputs, 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);
@@ -85,8 +186,19 @@
if (avg_loss < 0) avg_loss = loss;
avg_loss = avg_loss*.9 + loss*.1;
- fprintf(stderr, "%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);
@@ -102,8 +214,22 @@
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);
fprintf(stderr, "%s\n", base);
@@ -116,34 +242,89 @@
int i, j;
for(i = 0; i < net.n; ++i) net.layers[i].temperature = temp;
- unsigned char c;
+ int c = 0;
int len = strlen(seed);
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[(int)c] = 1;
+ input[c] = 1;
network_predict(net, input);
- input[(int)c] = 0;
- printf("%c", c);
+ input[c] = 0;
+ print_symbol(c, tokens);
}
- c = seed[len-1];
+ if(len) c = seed[len-1];
+ print_symbol(c, tokens);
for(i = 0; i < num; ++i){
- printf("%c", c);
- float r = rand_uniform(0,1);
- float sum = 0;
- input[(int)c] = 1;
+ input[c] = 1;
float *out = network_predict(net, input);
- input[(int)c] = 0;
- for(j = 0; j < inputs; ++j){
- sum += out[j];
- if(sum > r) break;
+ input[c] = 0;
+ for(j = 32; j < 127; ++j){
+ //printf("%d %c %f\n",j, j, out[j]);
}
- c = 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 valid_char_rnn(char *cfgfile, char *weightfile)
+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);
@@ -155,24 +336,135 @@
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);
+ 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[c] = 0;
+
+ if(c == '.' && next == '\n') in = 0;
+ if(!in) {
+ if(c == '>' && next == '>'){
+ in = 1;
+ ++words;
+ }
+ c = next;
+ continue;
+ }
+ ++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));
+ }
+}
+
+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));
}
- printf("Perplexity: %f\n", pow(2, -sum/count));
}
+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)
{
@@ -181,14 +473,20 @@
return;
}
char *filename = find_char_arg(argc, argv, "-file", "data/shakespeare.txt");
- char *seed = find_char_arg(argc, argv, "-seed", "\n");
+ 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], "valid")) valid_char_rnn(cfg, weights);
- 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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