Upload configuration_internvl_chat.py with huggingface_hub

configuration_internvl_chat.py

@@ -0,0 +1,115 @@
+# --------------------------------------------------------
+# InternVL
+# Copyright (c) 2024 OpenGVLab
+# Licensed under The MIT License [see NOTICE for details]
+# --------------------------------------------------------
+
+import copy
+from typing import Dict, Any, Optional
+
+from transformers.configuration_utils import PretrainedConfig
+from transformers.utils import logging
+
+from .configuration_intern_vit import InternVisionConfig
+
+logger = logging.get_logger(__name__)
+
+
+class InternVLChatConfig(PretrainedConfig):
+    model_type = 'internvl_chat'
+    is_composition = True
+
+    def __init__(
+        self,
+        vision_config: Optional[Dict[str, Any]] = None,
+        llm_config: Optional[Dict[str, Any]] = None,
+        use_backbone_lora=0,
+        use_llm_lora=0,
+        select_layer=-1,
+        force_image_size=None,
+        downsample_ratio=0.5,
+        template=None,
+        dynamic_image_size=False,
+        use_thumbnail=False,
+        ps_version="v1",
+        min_dynamic_patch=1,
+        max_dynamic_patch=6,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+
+        if vision_config is None:
+            vision_config = {'architectures': ['InternVisionModel']}
+            logger.info('vision_config is None. Initializing the InternVisionConfig with default values.')
+
+        if llm_config is None:
+            llm_config = {'architectures': ['Qwen2ForCausalLM']}
+            logger.info('llm_config is None. Initializing the LlamaConfig config with default values (`LlamaConfig`).')
+        assert 'architectures' in llm_config, "Should specify architecture in llm_config"
+
+        if isinstance(vision_config, dict):
+            self.vision_config = InternVisionConfig(**vision_config)
+        else:
+            self.vision_config = vision_config
+
+        if isinstance(llm_config, dict):
+            architecture: str = llm_config['architectures'][0]
+            if architecture == 'LlamaForCausalLM':
+                from transformers import LlamaConfig
+                self.llm_config = LlamaConfig(**llm_config)
+            elif architecture == 'Qwen2ForCausalLM':
+                from transformers import Qwen2Config
+                self.llm_config = Qwen2Config(**llm_config)
+            elif architecture == 'Qwen3MoeForCausalLM':
+                from transformers import Qwen3MoeConfig
+                self.llm_config = Qwen3MoeConfig(**llm_config)
+            elif architecture == 'Qwen3ForCausalLM':
+                from transformers import Qwen3Config
+                self.llm_config = Qwen3Config(**llm_config)
+            else:
+                raise ValueError('Unsupported architecture: {}'.format(architecture))
+        else:
+            self.llm_config = llm_config
+
+        self.use_backbone_lora = use_backbone_lora
+        self.use_llm_lora = use_llm_lora
+        self.select_layer = select_layer
+        self.force_image_size = force_image_size
+        self.downsample_ratio = downsample_ratio
+        self.template = template
+        self.dynamic_image_size = dynamic_image_size
+        self.use_thumbnail = use_thumbnail
+        self.ps_version = ps_version  # pixel shuffle version
+        self.min_dynamic_patch = min_dynamic_patch
+        self.max_dynamic_patch = max_dynamic_patch
+        self.tie_word_embeddings = self.llm_config.tie_word_embeddings
+
+        logger.info(f'vision_select_layer: {self.select_layer}')
+        logger.info(f'ps_version: {self.ps_version}')
+        logger.info(f'min_dynamic_patch: {self.min_dynamic_patch}')
+        logger.info(f'max_dynamic_patch: {self.max_dynamic_patch}')
+
+    def to_dict(self):
+        """
+        Serializes this instance to a Python dictionary. Override the default [`~PretrainedConfig.to_dict`].
+
+        Returns:
+            `Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
+        """
+        output = copy.deepcopy(self.__dict__)
+        output['vision_config'] = self.vision_config.to_dict()
+        output['llm_config'] = self.llm_config.to_dict()
+        output['model_type'] = self.__class__.model_type
+        output['use_backbone_lora'] = self.use_backbone_lora
+        output['use_llm_lora'] = self.use_llm_lora
+        output['select_layer'] = self.select_layer
+        output['force_image_size'] = self.force_image_size
+        output['downsample_ratio'] = self.downsample_ratio
+        output['template'] = self.template
+        output['dynamic_image_size'] = self.dynamic_image_size
+        output['use_thumbnail'] = self.use_thumbnail
+        output['ps_version'] = self.ps_version
+        output['min_dynamic_patch'] = self.min_dynamic_patch
+        output['max_dynamic_patch'] = self.max_dynamic_patch
+
+        return output