update for inf

fastNLP/modules/generator/seq2seq_generator.py

@@ -280,7 +280,6 @@ def _beam_search_generate(decoder: Seq2SeqDecoder, tokens=None, state=None, max_
         scores = F.log_softmax(scores, dim=-1)  # (batch_size, vocab_size)
         # 得到(batch_size, num_beams), (batch_size, num_beams)
         next_scores, next_tokens = torch.topk(scores, num_beams, dim=1, largest=True, sorted=True)
-    # TODO 这里需要考虑如果在第一个位置就结束的情况
 
     # 根据index来做顺序的调转
     indices = torch.arange(batch_size, dtype=torch.long).to(device)
@@ -329,7 +328,7 @@ def _beam_search_generate(decoder: Seq2SeqDecoder, tokens=None, state=None, max_
             max_len_eos_mask = max_lengths.eq(cur_len+1)
             eos_scores = scores[:, _eos_token_id]
             # 如果已经达到最大长度，就把eos的分数加大
-            scores[:, _eos_token_id] = torch.where(max_len_eos_mask, eos_scores+float('inf'), eos_scores)
+            scores[:, _eos_token_id] = torch.where(max_len_eos_mask, eos_scores+1e12, eos_scores)
 
         if do_sample:
             if temperature > 0 and temperature != 1: