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""" MiniCPMV model configuration""" |
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import os |
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from typing import Union |
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from transformers import PretrainedConfig, Qwen2Config |
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from transformers.utils import logging |
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from .modeling_navit_siglip import SiglipVisionConfig |
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logger = logging.get_logger(__name__) |
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class MiniCPMVSliceConfig(PretrainedConfig): |
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model_type = "minicpmv" |
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def __init__( |
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self, |
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patch_size=14, |
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max_slice_nums=9, |
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scale_resolution=448, |
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**kwargs, |
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): |
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super().__init__(**kwargs) |
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self.patch_size = patch_size |
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self.max_slice_nums = max_slice_nums |
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self.scale_resolution = scale_resolution |
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@classmethod |
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def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike], **kwargs) -> "PretrainedConfig": |
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cls._set_token_in_kwargs(kwargs) |
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config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs) |
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if config_dict.get("model_type") == "minicpmv": |
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config_dict = config_dict["slice_config"] |
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if "model_type" in config_dict and hasattr(cls, "model_type") and config_dict["model_type"] != cls.model_type: |
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logger.warning( |
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f"You are using a model of type {config_dict['model_type']} to instantiate a model of type " |
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f"{cls.model_type}. This is not supported for all configurations of models and can yield errors." |
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) |
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return cls.from_dict(config_dict, **kwargs) |
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class MiniCPMVConfig(Qwen2Config): |
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model_type = "minicpmv" |
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keys_to_ignore_at_inference = ["past_key_values"] |
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default_vision_config = { |
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"hidden_size": 1152, |
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"image_size": 980, |
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"intermediate_size": 4304, |
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"model_type": "siglip", |
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"num_attention_heads": 16, |
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"num_hidden_layers": 27, |
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"patch_size": 14, |
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} |
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def __init__( |
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self, |
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use_cache=True, |
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query_num=64, |
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image_size=448, |
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drop_vision_last_layer=True, |
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batch_vision_input=True, |
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slice_config=None, |
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vision_config=None, |
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use_image_id=True, |
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vision_batch_size=16, |
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**kwargs, |
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): |
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self.use_cache = use_cache |
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self.query_num = query_num |
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self.image_size = image_size |
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self.drop_vision_last_layer = drop_vision_last_layer |
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self.batch_vision_input = batch_vision_input |
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self.use_image_id = use_image_id |
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self.vision_batch_size = vision_batch_size |
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if slice_config is None: |
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self.slice_config = MiniCPMVSliceConfig(max_slice_nums=1) |
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else: |
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self.slice_config = MiniCPMVSliceConfig(**slice_config) |
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self.slice_mode = True |
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if vision_config is None: |
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self.vision_config = SiglipVisionConfig(**self.default_vision_config) |
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logger.info("vision_config is None, using default vision config") |
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elif isinstance(vision_config, dict): |
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self.vision_config = SiglipVisionConfig(**vision_config) |
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elif isinstance(vision_config, SiglipVisionConfig): |
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self.vision_config = vision_config |
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self.patch_size = self.vision_config.patch_size |
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super().__init__(**kwargs) |
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