i ddlmZddlmZddlmZddlmZiZ d dee efde de dejfd Z d dee efde de dejfd Z y) )Path)UnionN)base_load_model model_pathlazystrictreturnc ,td|dt||d|S)a Load and initialize a VAD/diarization 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. vad)rcategorymodel_remappingrr)rMODEL_REMAPPINGrrrkwargss h/Volumes/fast/ai/experiments/voice-extract-mac/.venv/lib/python3.12/site-packages/mlx_audio/vad/utils.py load_modelr s/  '      c t|f||d|S)a Load a VAD/diarization model from a local path or HuggingFace repository. This is the main entry point for loading VAD 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.vad import load >>> model = load("mlx-community/diar_streaming_sortformer_4spk-v2.1-fp16") >>> result = model.generate("audio.wav", verbose=True) )rr)rrs rloadr$s2 j EtF Ef EEr)FF)pathlibrtypingrmlx.nnnnmlx_audio.utilsrrstrboolModulerrrrrrs+FKc4i (,>BYY4FKFc4i F(,F>BFYYFr