Format model of qwen.

qwen/modeling_qwen.py

@@ -38,6 +38,7 @@ from qwen_generation_utils import (
 )
 
 import sys
+
 sys.path.append("..")
 from tools import show
 
@@ -144,7 +145,6 @@ class QWenAttention(nn.Module):
         else:
             attention_mask = causal_mask
 
-
         # qk = query @ key.transpose(-2, -1)
         # qk = qk[0]
         # show.DumpTensorToImage(qk,"q_matmul_k_layer_"+str(self.index)+".png")
@@ -441,12 +441,7 @@ class QWenLMHeadModel(QWenPreTrainedModel):
         if max_window_size is None:
             max_window_size = generation_config.max_window_size
         raw_text, context_tokens = make_context(
-            tokenizer,
-            query,
-            query_assistant,
-            history=history,
-            system=system,
-            max_window_size=max_window_size
+            tokenizer, query, query_assistant, history=history, system=system, max_window_size=max_window_size
         )
 
         stop_words_ids.extend([[tokenizer.im_end_id], [tokenizer.im_start_id]])
@@ -469,13 +464,12 @@ class QWenLMHeadModel(QWenPreTrainedModel):
     def generate(
         self,
         inputs: Optional[torch.Tensor] = None,
-        stop_words_ids = [],
+        stop_words_ids=[],
         prefix_allowed_tokens_fn: Optional[Callable[[int, torch.Tensor], List[int]]] = None,
         **kwargs,
     ) -> Union[GenerateOutput, torch.LongTensor]:
         generation_config = self.generation_config
 
-
         # 1. Handle `generation_config` and kwargs that might update it, and validate the `.generate()` call
         self._validate_model_class()
 
@@ -486,7 +480,6 @@ class QWenLMHeadModel(QWenPreTrainedModel):
 
         # 2. Set generation parameters if not already defined
 
-
         if generation_config.pad_token_id is None and generation_config.eos_token_id is not None:
             if model_kwargs.get("attention_mask", None) is None:
                 logger.warning(
@@ -524,7 +517,6 @@ class QWenLMHeadModel(QWenPreTrainedModel):
         generation_config.max_length = generation_config.max_new_tokens + input_ids_length
         self._validate_generated_length(generation_config, input_ids_length, has_default_max_length)
 
-
         stop_words_logits_processor = StopWordsLogitsProcessor(
             stop_words_ids=stop_words_ids,
             eos_token_id=generation_config.eos_token_id,
@@ -541,7 +533,6 @@ class QWenLMHeadModel(QWenPreTrainedModel):
             negative_prompt_attention_mask=None,
         )
 
-
         # 12. expand input_ids with `num_return_sequences` additional sequences per batch
         input_ids, model_kwargs = self._expand_inputs_for_generation(
             input_ids=input_ids,
@@ -552,9 +543,9 @@ class QWenLMHeadModel(QWenPreTrainedModel):
 
         # 13. run sample
 
-        pad_token_id=generation_config.pad_token_id
-        eos_token_id_tensor=torch.tensor([generation_config.eos_token_id]).to(input_ids.device)
-        
+        pad_token_id = generation_config.pad_token_id
+        eos_token_id_tensor = torch.tensor([generation_config.eos_token_id]).to(input_ids.device)
+
         # init values
         stopping_criteria = self._get_stopping_criteria(
             generation_config=generation_config, stopping_criteria=StoppingCriteriaList()