Update modeling_deepseekocr.py

modeling_deepseekocr.py

@@ -353,6 +353,7 @@ class DeepseekOCRConfig(DeepseekV2Config):
 
 class DeepseekOCRModel(DeepseekV2Model):
     config_class = DeepseekOCRConfig
+    verbose = True
 
     def __init__(self, config: DeepseekV2Config):
         super(DeepseekOCRModel, self).__init__(config)
@@ -383,7 +384,6 @@ class DeepseekOCRModel(DeepseekV2Model):
         images_seq_mask: Optional[torch.FloatTensor] = None,
         images_spatial_crop: Optional[torch.FloatTensor] = None,
         return_dict: Optional[bool] = None,
-        verbose: Optional[bool] = None,
     ) -> Union[Tuple, BaseModelOutputWithPast]:
 
 
@@ -433,7 +433,7 @@ class DeepseekOCRModel(DeepseekV2Model):
                         global_features = torch.cat((global_features_2[:, 1:], global_features_1.flatten(2).permute(0, 2, 1)), dim=-1) 
                         global_features = self.projector(global_features)
 
-                        if verbose:
+                        if self.verbose:
                             print('=====================')
                             print('BASE: ', global_features.shape)
                             print('PATCHES: ', local_features.shape)
@@ -478,7 +478,7 @@ class DeepseekOCRModel(DeepseekV2Model):
                         global_features = torch.cat((global_features_2[:, 1:], global_features_1.flatten(2).permute(0, 2, 1)), dim=-1) 
                         global_features = self.projector(global_features)
 
-                        if verbose:
+                        if self.verbose:
                             print('=====================')
                             print('BASE: ', global_features.shape)
                             print('NO PATCHES')
@@ -706,6 +706,7 @@ class DeepseekOCRForCausalLM(DeepseekV2ForCausalLM):
 
     def infer(self, tokenizer, prompt='', image_file='', output_path = '', base_size=1024, image_size=640, crop_mode=True, test_compress=False, save_results=False, eval_mode=False, streamer=None, verbose=True):
         self.disable_torch_init()
+        self.model.verbose = verbose
 
         if len(output_path) > 0 :
             os.makedirs(output_path, exist_ok=True)
@@ -930,8 +931,7 @@ class DeepseekOCRForCausalLM(DeepseekV2ForCausalLM):
                         streamer=streamer,
                         max_new_tokens=8192,
                         no_repeat_ngram_size = 20,
-                        use_cache = True,
-                        verbose = verbose
+                        use_cache = True
                         )
 
         else:
@@ -948,8 +948,7 @@ class DeepseekOCRForCausalLM(DeepseekV2ForCausalLM):
                         eos_token_id=tokenizer.eos_token_id,
                         max_new_tokens=8192,
                         no_repeat_ngram_size = 35,
-                        use_cache = True,
-                        verbose = verbose
+                        use_cache = True
                         )