101 lines
3.2 KiB
Python
101 lines
3.2 KiB
Python
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# coding=utf-8
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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.utils import logging
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from transformers import Qwen2Config, PretrainedConfig
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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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# same as HuggingFaceM4/siglip-so400m-14-980-flash-attn2-navit add tgt_sizes
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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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