o eiV@s:dZddlZddlmZddlmZGdddejZdS)a;This lobe enables the integration of pretrained SpeechTokenizer. Please, install speechtokenizer: pip install speechtokenizer Reference: https://arxiv.org/abs/2308.16692 Transformer from HuggingFace needs to be installed: https://huggingface.co/transformers/installation.html Author * Pooneh Mousavi 2023 N)snapshot_downloadcs@eZdZdZ d fdd Zd ddZd dd Zd d ZZS)SpeechTokenizeraThis 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. sample_rate : int (default: 16000) The audio sampling rate Example ------- >>> import torch >>> inputs = torch.rand([10, 600]) >>> model_hub = "fnlp/SpeechTokenizer" >>> save_path = "savedir" >>> model =SpeechTokenizer(model_hub, save_path) >>> tokens = model.encode(inputs) >>> tokens.shape torch.Size([8, 10, 2]) >>> wav=model.decode(tokens) >>> wav.shape torch.Size([10, 640]) >csz ddlm}||_Wn tytdwtt|ddg|d}|d}|d}|j|||_|j||_ dS) Nr)rzhPlease install the speechtokenizer module using: pip install speechtokenizer`pip install beartype==0.1.1z *config.jsonz*SpeechTokenizer.pt)repo_idallow_patterns cache_dirz'/speechtokenizer_hubert_avg/config.jsonz./speechtokenizer_hubert_avg/SpeechTokenizer.pt) speechtokenizerr ImportErrorsuper__init__rload_from_checkpointmodeleval sample_rate)selfsource save_pathrr saved_dir config_path ckpt_path __class__o/home/ubuntu/transcripts/venv/lib/python3.10/site-packages/speechbrain/lobes/models/discrete/speechtokenizer.pyr :s*        zSpeechTokenizer.__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)rwavwav_lensrrrforward\s zSpeechTokenizer.forwardcCs@t|j|d}Wd|S1swY|S)rN)torchno_gradr r unsqueeze)rrrcodesrrrrns  zSpeechTokenizer.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 decoder catsqueeze)rr#RVQ_1RVQ_supplementrrrrr%s zSpeechTokenizer.decode)r)N) __name__ __module__ __qualname____doc__r rrr% __classcell__rrrrrs( " r)r-r torch.nnnnhuggingface_hubrModulerrrrrs