Delete configuration.py

configuration.py

@@ -1,116 +0,0 @@
-from transformers import PretrainedConfig
-from transformers import CONFIG_MAPPING
-from transformers import AutoConfig
-
-IGNORE_INDEX = -100
-IMAGE_TOKEN_INDEX = -200
-DEFAULT_IMAGE_TOKEN = "<image>"
-
-
-class TinyLlavaConfig(PretrainedConfig):
-
-    model_type = "tinyllava"
-    def __init__(
-        self,
-        llm_model_name_or_path = '',
-        tokenizer_name_or_path = None,
-        vision_model_name_or_path = '',
-        vision_model_name_or_path2 = '',
-        connector_type = None,
-        text_config=None,
-        hidden_size=2048,
-        vocab_size=32000,
-        ignore_index=-100,
-        image_token_index=32000,
-        pad_token = None,
-        pad_token_id = None,
-        tokenizer_padding_side = 'right',
-        tokenizer_model_max_length = 2048,
-        vision_config = None,
-        vision_hidden_size = None,
-        vision_feature_layer = -2,
-        vision_feature_select_strategy = 'patch',
-        image_aspect_ratio = 'square',
-        resampler_hidden_size = None,
-        num_queries = None,
-        num_resampler_layers = None,
-        use_cache = False,
-        cache_dir = None,
-        tokenizer_use_fast = False,
-        tune_type_llm = 'frozen',
-        tune_type_connector = 'frozen',
-        tune_type_vision_tower = 'frozen',
-        tune_vision_tower_from_layer = -1,
-        
-        **kwargs
-
-    ):
-        self.llm_model_name_or_path = llm_model_name_or_path
-        self.tokenizer_name_or_path = tokenizer_name_or_path or self.llm_model_name_or_path
-        self.vision_model_name_or_path = vision_model_name_or_path
-        self.vision_model_name_or_path2 = vision_model_name_or_path2
-        self.connector_type = connector_type
-        self.tune_type_llm = tune_type_llm
-        self.tune_type_connector = tune_type_connector
-        self.tune_type_vision_tower = tune_type_vision_tower
-        self.tune_vision_tower_from_layer = tune_vision_tower_from_layer
-        
-        self.ignore_index = IGNORE_INDEX
-        self.image_token_index = IMAGE_TOKEN_INDEX
-        self.pad_token = pad_token
-        self.pad_token_id = pad_token_id
-        self.tokenizer_padding_side = tokenizer_padding_side
-        self.tokenizer_model_max_length = tokenizer_model_max_length
-        self.vision_feature_layer = vision_feature_layer
-        self.vision_feature_select_strategy = vision_feature_select_strategy
-        self.image_aspect_ratio = image_aspect_ratio
-        self.resampler_hidden_size = resampler_hidden_size
-        self.num_queries = num_queries
-        self.num_resampler_layers = num_resampler_layers
-        self.use_cache = use_cache
-        self.cache_dir = cache_dir
-        self.tokenizer_use_fast = tokenizer_use_fast
-        self._load_text_config(text_config)
-        self._load_vision_config(vision_config)
-            
-        super().__init__(**kwargs)
-      
-    
-    def _load_text_config(self, text_config=None):
-        if self.llm_model_name_or_path is None or self.llm_model_name_or_path == '':
-            self.text_config = CONFIG_MAPPING['llama']()
-           
-        else:
-            self.text_config = AutoConfig.from_pretrained(self.llm_model_name_or_path, trust_remote_code=True)
-            if text_config is not None:
-                self.text_config = self.text_config.from_dict(text_config)
-                
-        self.hidden_size = getattr(self.text_config, 'hidden_size',  getattr(self.text_config, 'model_dim', None))
-        self.vocab_size = getattr(self.text_config, 'vocab_size',  None)
-    
-    
-    
-    def _load_vision_config(self, vision_config=None):
-        if self.vision_model_name_or_path is None or self.vision_model_name_or_path == '':
-            self.vision_config = CONFIG_MAPPING['clip_vision_model'](
-                intermediate_size=4096,
-                hidden_size=1024,
-                patch_size=14,
-                image_size=336,
-                num_hidden_layers=24,
-                num_attention_heads=16,
-                vocab_size=32000,
-                projection_dim=768,
-            )
-            
-        else:
-            self.vision_config = AutoConfig.from_pretrained(self.vision_model_name_or_path.split(':')[-1])
-            self.vision_config = getattr(self.vision_config, 'vision_config', self.vision_config)
-            if vision_config is not None:
-                self.vision_config = self.vision_config.from_dict(vision_config)
-                
-        self.vision_config.model_name_or_path = self.vision_model_name_or_path.split(':')[-1]
-        self.vision_config.model_name_or_path2 = self.vision_model_name_or_path2.split(':')[-1]
-        self.vision_hidden_size = getattr(self.vision_config, 'hidden_size',  None)  
-        
-