| |
| """ MiniCPMV model configuration""" |
|
|
| import os |
| from typing import Union |
|
|
| from transformers.utils import logging |
| from transformers import Qwen3Config, PretrainedConfig |
| from .modeling_navit_siglip import SiglipVisionConfig |
|
|
| logger = logging.get_logger(__name__) |
|
|
|
|
| class MiniCPMVSliceConfig(PretrainedConfig): |
| model_type = "minicpmv" |
|
|
| def __init__( |
| self, |
| patch_size=14, |
| max_slice_nums=9, |
| scale_resolution=448, |
| **kwargs, |
| ): |
| super().__init__(**kwargs) |
| self.patch_size = patch_size |
| self.max_slice_nums = max_slice_nums |
| self.scale_resolution = scale_resolution |
|
|
| @classmethod |
| def from_pretrained(cls, pretrained_model_name_or_path: Union[str, os.PathLike], **kwargs) -> "PretrainedConfig": |
| cls._set_token_in_kwargs(kwargs) |
|
|
| config_dict, kwargs = cls.get_config_dict(pretrained_model_name_or_path, **kwargs) |
|
|
| if config_dict.get("model_type") == "minicpmv": |
| config_dict = config_dict["slice_config"] |
|
|
| if "model_type" in config_dict and hasattr(cls, "model_type") and config_dict["model_type"] != cls.model_type: |
| logger.warning( |
| f"You are using a model of type {config_dict['model_type']} to instantiate a model of type " |
| f"{cls.model_type}. This is not supported for all configurations of models and can yield errors." |
| ) |
|
|
| return cls.from_dict(config_dict, **kwargs) |
|
|
|
|
|
|
| class MiniCPMVConfig(Qwen3Config): |
| model_type = "minicpmv" |
| keys_to_ignore_at_inference = ["past_key_values"] |
|
|
| default_vision_config = { |
| "hidden_size": 1152, |
| "image_size": 980, |
| "intermediate_size": 4304, |
| "model_type": "siglip", |
| "num_attention_heads": 16, |
| "num_hidden_layers": 27, |
| "patch_size": 14, |
| } |
|
|
| def __init__( |
| self, |
| use_cache=True, |
| query_num=64, |
| image_size=448, |
| drop_vision_last_layer=True, |
| batch_vision_input=True, |
| slice_config=None, |
| vision_config=None, |
| use_image_id=True, |
| vision_batch_size=16, |
| batch_3d_resampler=True, |
| **kwargs, |
| ): |
| self.use_cache = use_cache |
| self.query_num = query_num |
| self.image_size = image_size |
| self.drop_vision_last_layer = drop_vision_last_layer |
| self.batch_vision_input = batch_vision_input |
| self.use_image_id = use_image_id |
| self.vision_batch_size = vision_batch_size |
| self.batch_3d_resampler = batch_3d_resampler |
|
|
| if slice_config is None: |
| self.slice_config = MiniCPMVSliceConfig(max_slice_nums=1) |
| else: |
| self.slice_config = MiniCPMVSliceConfig(**slice_config) |
| self.slice_mode = True |
|
|
| |
| if vision_config is None: |
| self.vision_config = SiglipVisionConfig(**self.default_vision_config) |
| elif isinstance(vision_config, dict): |
| self.vision_config = SiglipVisionConfig(**vision_config) |
| elif isinstance(vision_config, SiglipVisionConfig): |
| self.vision_config = vision_config |
|
|
| self.patch_size = self.vision_config.patch_size |
|
|
| super().__init__(**kwargs) |
|
|
