(HJj ddlmZddlmZmZddlmZddlmZdZ dddZ ddee efd e d e d ejfd Z ddee efd e d e d ejfd Zy))Path)OptionalUnionN)base_load_modeli> ecapa_tdnn)z ecapa-tdnnr model_pathlazystrictreturnc ,td|dt||d|S)a Load and initialize a LID model from a given path. Args: model_path: The path or HuggingFace repo to load the model from. lazy: If False, evaluate model parameters immediately. strict: If True, raise an error if any weights are missing. **kwargs: Additional keyword arguments (revision, force_download). Returns: nn.Module: The loaded and initialized model. lid)rcategorymodel_remappingr r )rMODEL_REMAPPINGrr r kwargss ]/Users/ahmed/devFolder/claude-voice/.venv/lib/python3.12/site-packages/mlx_audio/lid/utils.py load_modelrs/  '      c t|f||d|S)aS Load a language identification model from a local path or HuggingFace repository. This is the main entry point for loading LID models. It automatically detects the model type and initializes the appropriate model class. Args: model_path: The local path or HuggingFace repo ID to load from. lazy: If False, evaluate model parameters immediately. strict: If True, raise an error if any weights are missing. **kwargs: Additional keyword arguments: - revision (str): HuggingFace revision/branch to use - force_download (bool): Force re-download of model files Returns: nn.Module: The loaded and initialized model. Example: >>> from mlx_audio.lid import load >>> model = load("facebook/mms-lid-256") >>> results = model.predict(audio) )r r )rrs rloadr)s2 j EtF Ef EEr)FF)pathlibrtypingrrmlx.nnnnmlx_audio.utilsr SAMPLE_RATErstrboolModulerrrrrr"s"+ FKc4i (,>BYY4FKFc4i F(,F>BFYYFr