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configuration.py

@@ -0,0 +1,116 @@
+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)  
+        
+