fix bugs

.gitignore

@@ -12,6 +12,7 @@ state_dict/bert_seq2seq_save
 # Distribution / packaging
 .Python
 build/
+./test.py
 nouse/*
 develop-eggs/
 dist/

bert_seq2seq/gpt2_generate_model.py

@@ -42,6 +42,29 @@ def sample_generate(self, text, input_max_length=256, out_max_length=200, top_k=
 
         return self.tokenizer.decode(np.array(output_ids))
 
+    def sample_generate_once(self, text, input_max_length=256, out_max_length=200, top_k=30, top_p=0.0, sep="。"):
+
+        token_ids, _ = self.tokenizer.encode(text, max_length=input_max_length)
+        # 不加任何的开始符号和结束符号，就是输入一句话。
+        token_ids = torch.tensor(token_ids, device=self.device, dtype=torch.long)[1:-1].view(1, -1)
+
+
+        output_ids = []
+        sep_id = self.word2ix[sep] # 句号结尾
+        with torch.no_grad(): 
+            for step in range(out_max_length):
+                _, scores = self.model(token_ids)
+                logit_score = torch.log_softmax(scores[:, -1], dim=-1).squeeze(0)
+                logit_score[self.word2ix["[UNK]"]] = -float('Inf')
+                filtered_logits = top_k_top_p_filtering(logit_score, top_k=top_k, top_p=top_p)
+                next_token = torch.multinomial(F.softmax(filtered_logits, dim=-1), num_samples=1)
+                if sep_id == next_token.item():
+                    break
+                output_ids.append(next_token.item())
+                token_ids = torch.cat((token_ids, next_token.long().unsqueeze(0)), dim=1)
+
+        return self.tokenizer.decode(np.array(output_ids))
+
     def sample_generate_english(self, text, input_max_length=256, out_max_length=200, top_k=30, top_p=0.0, add_eos=False):
 
         token_ids = self.tokenizer.encode(text, max_length=input_max_length, truncation=True)