@@ -41,7 +41,8 @@ std::vector<uint> trim_or_padding(const std::vector<uint>& src, uint max_len, ui
4141 std::vector<uint> res = src;
4242 if (src.size () > max_len) {
4343 res.resize (max_len);
44- } else {
44+ }
45+ else {
4546 res.resize (max_len, pad_id);
4647 }
4748 return res;
@@ -98,7 +99,7 @@ int main(int argc, char* argv[]) {
9899
99100 int opt;
100101 int epochs = 10 ;
101- int batch_size = 4 ;
102+ int batch_size = 16 ;
102103 int gpu = 1 ;
103104 int max_words_cnt = 256 ;
104105 float lr = 0 .001f ;
@@ -225,6 +226,7 @@ int main(int argc, char* argv[]) {
225226 adam.clip_grad (1 .0f );
226227 adam.step ();
227228 graph::validateAllNodesRefCnt (0 );
229+ // printAllTensors();
228230 // printAllActions();
229231 allocMemAndInitTensors ();
230232 std::cout << " Allocating memory " << std::endl
@@ -264,7 +266,8 @@ int main(int argc, char* argv[]) {
264266 auto origin_size = src_token_ids.size ();
265267 if (src_token_ids.size () < num_steps) {
266268 src_token_ids.resize (num_steps, loader.get_pad_id ());
267- } else if (src_token_ids.size () > num_steps) {
269+ }
270+ else if (src_token_ids.size () > num_steps) {
268271 src_token_ids.erase (src_token_ids.begin (), src_token_ids.end () - num_steps);
269272 }
270273 auto cur_step = origin_size - 1 ;
@@ -302,15 +305,17 @@ int main(int argc, char* argv[]) {
302305 if (cur_step >= num_steps - 1 ) {
303306 src_token_ids.push_back (max_index);
304307 src_token_ids.erase (src_token_ids.begin (), src_token_ids.end () - num_steps);
305- } else {
308+ }
309+ else {
306310 src_token_ids[++cur_step] = max_index;
307311 }
308312 }
309313 std::cout << std::endl;
310314 std::cout << " -----------------" << std::endl;
311315 ::free (res_buffer);
312316 }
313- } else {
317+ }
318+ else {
314319 init_dec_valid_lens_for_training (dec_valid_lens);
315320 signal (SIGINT, signal_callback_handler);
316321 int epoch = 0 ;
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