o pi@sFdZddlZddlmZddlmZddlmZGdddejZ dS)aThis lobe enables the integration of pretrained SpeechTokenizer. Please, install speechtokenizer: pip install speechtokenizer Reference: https://arxiv.org/abs/2308.16692 Reference: https://arxiv.org/abs/1904.05862 Reference: https://arxiv.org/abs/2110.13900 Transformer from HuggingFace needs to be installed: https://huggingface.co/transformers/installation.html Author * Pooneh Mousavi 2023 N)snapshot_download)SpeechTokenizercs<eZdZdZfddZd ddZd ddZd d ZZS) SpeechTokenizer_interfaceaThis lobe enables the integration of HuggingFace and SpeechBrain pretrained SpeechTokenizer. Please, install speechtokenizer: pip install speechtokenizer Source paper: https://arxiv.org/abs/2308.16692 The model can be used as a fixed Discrete feature extractor or can be finetuned. It will download automatically the model from HuggingFace or use a local path. Arguments --------- source : str HuggingFace hub name: e.g "fnlp/SpeechTokenizer" save_path : str Path (dir) of the downloaded model. Example ------- >>> import torch >>> inputs = torch.rand([10, 600]) >>> model_hub = "fnlp/SpeechTokenizer" >>> save_path = "savedir" >>> model =SpeechTokenizer_interface(model_hub, save_path) # doctest: +SKIP >>> tokens = model(inputs) # doctest: +SKIP >>> print(tokens.shape) # doctest: +SKIP torch.Size([8, 10, 2]) >>> wav=model.decode(tokens) >>> print(wav.shape) torch.Size([10, 640]) csLtt|ddg|d}|d}|d}t|||_|jdS)Nz *config.jsonz*SpeechTokenizer.pt)repo_idallow_patterns cache_dirz'/speechtokenizer_hubert_avg/config.jsonz./speechtokenizer_hubert_avg/SpeechTokenizer.pt)super__init__rrload_from_checkpointmodeleval)selfsource save_path saved_dir config_path ckpt_path __class__y/home/ubuntu/SoloSpeech/.venv/lib/python3.10/site-packages/speechbrain/lobes/models/discrete/speechtokenizer_interface.pyr ;s   z"SpeechTokenizer_interface.__init__NcCs |||S)Takes an input waveform and return its corresponding wav2vec encoding. Arguments --------- wav : torch.Tensor (signal) A batch of audio signals to transform to features. wav_lens : torch.Tensor The relative length of the wav given in SpeechBrain format. Returns ------- tokens : torch.Tensor A (N_q, Batch x Seq) tensor of audio tokens )encode)r wavwav_lensrrrforwardOs z!SpeechTokenizer_interface.forwardcCs@t|j|d}Wd|S1swY|S)rN)torchno_gradr r unsqueeze)r rrcodesrrrras  z SpeechTokenizer_interface.encodecCsX|ddddddf}|ddddddf}|jtj||gdd}|dS)aBTakes an input waveform and return its corresponding wav2vec encoding. Arguments --------- codes : torch.Tensor A (N_q, Batch x Seq) tensor of audio tokens Returns ------- wav : torch.Tensor (signal) A batch of reconstructed audio signals. Nrr)axis)r decodercatsqueeze)r r RVQ_1RVQ_supplementrrrrr"ws z SpeechTokenizer_interface.decode)N) __name__ __module__ __qualname____doc__r rrr" __classcell__rrrrrs  "  r) r*rtorch.nnnnhuggingface_hubrspeechtokenizerrModulerrrrrs