# -------------------------------------------------------- # InternVL # Copyright (c) 2024 OpenGVLab # Licensed under The MIT License [see LICENSE for details] # -------------------------------------------------------- import copy from transformers import AutoConfig, LlamaConfig from transformers.configuration_utils import PretrainedConfig from transformers.utils import logging from transformers.models.auto import CONFIG_MAPPING from .configuration_intern_vit import InternVisionConfig from .configuration_yuan import YuanConfig logger = logging.get_logger(__name__) class YuanVLChatConfig(PretrainedConfig): model_type = 'yuanvl' is_composition = True sub_configs = {"llm_config": YuanConfig, "vision_config": InternVisionConfig} # 声明子配置类型 def __init__( self, vision_config=None, llm_config=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, tie_word_embeddings=False, ps_version='v1', min_dynamic_patch=1, max_dynamic_patch=6, img_context_token_id=77188,** kwargs): # 初始化视觉子配置(确保为InternVisionConfig实例) if vision_config is None: # 输入为None时,直接实例化InternVisionConfig(而非字典) self.vision_config = InternVisionConfig(architectures=['InternVisionModel']) logger.info('vision_config is None. Initializing InternVisionConfig with default values.') elif isinstance(vision_config, dict): # 输入为字典时,用from_dict实例化 self.vision_config = InternVisionConfig.from_dict(vision_config) else: # 输入已为实例时直接使用 self.vision_config = vision_config # 初始化LLM子配置(确保为YuanConfig实例) if llm_config is None: # 输入为None时,直接实例化YuanConfig(而非字典) self.llm_config = YuanConfig(architectures=['YuanForCausalLM']) self.llm_config.tie_word_embeddings = tie_word_embeddings # 显式设置属性 logger.info('llm_config is None. Initializing YuanConfig with default values.') elif isinstance(llm_config, dict): # 输入为字典时,用from_dict实例化 self.llm_config = YuanConfig.from_dict(llm_config) self.llm_config.tie_word_embeddings = tie_word_embeddings else: # 输入已为实例时直接使用,并同步tie_word_embeddings self.llm_config = llm_config self.llm_config.tie_word_embeddings = tie_word_embeddings # 其他属性初始化 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 self.min_dynamic_patch = min_dynamic_patch self.max_dynamic_patch = max_dynamic_patch self.img_context_token_id = img_context_token_id self.tie_word_embeddings = self.llm_config.tie_word_embeddings # 同步LLM的配置 # 日志输出 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}') super().__init__(**kwargs) @classmethod def from_sub_model_configs( cls, vision_config: InternVisionConfig, llm_config: YuanConfig, **kwargs, ): r""" Instantiate a [`YuanVLChatConfig`] (or a derived class) from bark sub-models configuration. Returns: [``YuanVLChatConfig``]: An instance of a configuration object """ return cls( vision_config=vision_config.to_dict(), llm_config=llm_config.to_dict(), **kwargs, ) 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