| """HuggingFace configs for the MiniMax VL family (M2 VL / M3 VL). |
| |
| This file is bundled into every converted HF checkpoint so that loading via |
| ``AutoConfig.from_pretrained(..., trust_remote_code=True)`` works without any |
| runtime dependency on sglang or other internal packages — only stock |
| ``transformers`` is required. |
| |
| The class definitions intentionally mirror |
| ``sglang.srt.configs.minimax_vl``; if either side changes, keep them in sync. |
| |
| The file is named ``configuration_minimax_m3_vl.py`` (matching the legacy |
| ``model_type="minimax_m3_vl"`` and the converter's ``auto_map`` entry) so |
| that ckpts produced by this converter remain loadable by older sglang versions |
| that only know the ``MiniMaxM3VL*`` names. The canonical class is |
| ``MiniMaxM3VLConfig``; ``MiniMaxM3VLConfig`` is a thin BC alias whose only |
| purpose is to be referenced from ``auto_map``. |
| """ |
|
|
| from typing import Optional |
|
|
| from transformers.configuration_utils import PretrainedConfig |
| from transformers.models.auto import CONFIG_MAPPING |
|
|
|
|
| def _coerce_sub_config( |
| sub_config: Optional[dict], default_model_type: str |
| ) -> Optional[PretrainedConfig]: |
| """Convert a config dict to a ``PretrainedConfig`` instance. |
| |
| If ``model_type`` is registered in HF ``CONFIG_MAPPING`` the corresponding |
| config class is used; otherwise we fall back to a generic |
| ``PretrainedConfig`` so all dict keys still become real attributes (M3's |
| text backbone uses ``model_type="minimax_m2"`` which is not in |
| ``CONFIG_MAPPING``). |
| """ |
| if not isinstance(sub_config, dict): |
| return sub_config |
| model_type = sub_config.get("model_type", default_model_type) |
| cls = CONFIG_MAPPING.get(model_type, PretrainedConfig) |
| return cls(**sub_config) |
|
|
|
|
| class MiniMaxVLBaseConfig(PretrainedConfig): |
| """Base config shared by every MiniMax VL variant. |
| |
| Handles vision/text sub-config coercion. Concrete subclasses only need to |
| declare a unique ``model_type`` string. |
| """ |
|
|
| def __init__( |
| self, |
| vision_config: Optional[dict] = None, |
| text_config: Optional[dict] = None, |
| image_token_index: int = 200025, |
| video_token_index: int = 200026, |
| image_seq_length: int = 576, |
| process_image_mode: str = "dynamic_res", |
| projector_hidden_act: str = "gelu", |
| multimodal_projector_bias: bool = True, |
| vision_feature_layer: int = -1, |
| vision_feature_select_strategy: str = "full", |
| img_token_compression_config: Optional[dict] = None, |
| image_grid_pinpoints: Optional[str] = None, |
| **kwargs, |
| ): |
| self.vision_config = _coerce_sub_config(vision_config, "clip_vision_model") |
| self.text_config = _coerce_sub_config(text_config, "mixtral") |
|
|
| self.image_token_index = image_token_index |
| self.video_token_index = video_token_index |
| self.image_seq_length = image_seq_length |
| self.process_image_mode = process_image_mode |
| self.projector_hidden_act = projector_hidden_act |
| self.multimodal_projector_bias = multimodal_projector_bias |
| self.vision_feature_layer = vision_feature_layer |
| self.vision_feature_select_strategy = vision_feature_select_strategy |
| self.img_token_compression_config = img_token_compression_config or {} |
| self.image_grid_pinpoints = image_grid_pinpoints |
|
|
| super().__init__(**kwargs) |
|
|
| def __post_init__(self, **kwargs): |
| super().__post_init__(**kwargs) |
| if hasattr(self, "vision_config"): |
| self.vision_config = _coerce_sub_config(self.vision_config, "clip_vision_model") |
| if hasattr(self, "text_config"): |
| self.text_config = _coerce_sub_config(self.text_config, "mixtral") |
|
|
|
|
| class MiniMaxM2VLConfig(MiniMaxVLBaseConfig): |
| """MiniMax M2 VL: vision tower + M2 (Mixtral-style MoE) text backbone.""" |
|
|
| model_type = "minimax_m2_vl" |
|
|
|
|
| class MiniMaxM3VLConfig(MiniMaxVLBaseConfig): |
| """MiniMax M3 VL: vision tower + M3 (mixed sparse/dense MoE) text backbone.""" |
|
|
| model_type = "minimax_m3_vl" |
|
|
|
|
| class MiniMaxM2MiniVLConfig(MiniMaxM2VLConfig): |
| """Legacy alias kept so old ``model_type="minimax_m2_mini_vl"`` ckpts load.""" |
|
|
| model_type = "minimax_m2_mini_vl" |
|
|
|
|
| class MiniMaxM3VLConfig(MiniMaxM3VLConfig): |
| """Legacy alias kept so old ``model_type="minimax_m3_vl"`` ckpts load.""" |
|
|
| model_type = "minimax_m3_vl" |
|
|
