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configuration_bionexttager.py

@@ -25,12 +25,12 @@ class BioNextTaggerConfig(PretrainedConfig):
         super().__init__(**kwargs)
         
     def get_backbonemodel_config(self):
-        print("BACKend config start?", flush=True)
+        print(f"model_path {self._name_or_path}", flush=True)
         backbonemodel_cfg = AutoConfig.from_pretrained(self._name_or_path,
                                                        trust_remote_code=True)#.to_dict()
         for k in backbonemodel_cfg.to_dict():
             if hasattr(self, k):
                 setattr(backbonemodel_cfg,k, getattr(self,k))
-        print("BACKend config end?", flush=True)
+        #print("BACKend config end?", flush=True)
         return backbonemodel_cfg
         

modeling_bionexttagger.py

@@ -22,12 +22,12 @@ class BioNextTaggerModel(PreTrainedModel):
     def __init__(self, config):
         super().__init__(config)
         self.num_labels = config.num_labels
-        print("LOAD BERT?", flush=True)
+        #print("LOAD BERT?", flush=True)
         self.bert = BertModel(config.get_backbonemodel_config(), add_pooling_layer=False)
                     #AutoModel.from_pretrained(config._name_or_path, 
                     #                          config=config.get_backbonemodel_config(), 
                     #                          add_pooling_layer=False)
-        print("LOADED BERT", flush=True)
+        #print("LOADED BERT", flush=True)
         # self.vocab_size = config.vocab_size
         #classifier_dropout = (config.classifier_dropout if config.classifier_dropout is not None else config.hidden_dropout_prob)
         self.dropout = nn.Dropout(config.hidden_dropout_prob)