~VjiS ddlZddlmZddlmZmZmZddlZddlm Z ddl m Z ddl m Z ddlmZddlmZd Zd Zd Zd gd gd dgdZdedeededeeeeffdZGdde ZdS)N)Path)ListTupleUnion)Tensor)Dataset)download_url_to_file)_get_librispeech_metadata) _extract_tarlibrispeech_finetuningzIhttps://dl.fbaipublicfiles.com/librilight/data/librispeech_finetuning.tgz@5d1efdc777b548194d7e09ba89126e2188026df9fd57aa57eb14408d2b2342afz1h/0z1h/*9h)10min1h10hpathfolders _ext_audioreturnctg}|D]7}fd|d|D}|d|Dz }8|d|S)aGet the file names and the corresponding file paths without `speaker_id` and `chapter_id` directories. The format of path is like: {root}/{_ARCHIVE_NAME}/1h/[0-5]/[clean, other] or {root}/{_ARCHIVE_NAME}/9h/[clean, other] Args: path (Path): Root path to the dataset. folders (List[str]): Folders that contain the desired audio files. _ext_audio (str): Extension of audio files. Returns: List[Tuple[str, str]]: List of tuples where the first element is the relative path to the audio file. The format of relative path is like: 1h/[0-5]/[clean, other] or 9h/[clean, other] The second element is the file name without audio extension. c:g|]}|S) relative_to).0prs `/root/voice-cloning/.venv/lib/python3.11/site-packages/torchaudio/datasets/librilight_limited.py z&_get_fileids_paths..*s%YYYt$$YYYz/*/*/*/*crg|]4}t|jjjt|jf5Sr)strparentstem)rrs rrz&_get_fileids_paths..+s4RRRqQX_344c!&kkBRRRrc$|d|dzS)Nrr)xs rz$_get_fileids_paths..,s1Q4!A$;r)key)rglobsort)rrr files_pathsfolderpathss` r_get_fileids_pathsr-s( ::DKSSYYYYdii68W8W:8W8W.X.XYYYRRERRRR ../// rc |eZdZdZdZdZ ddeeefdede d d fd Z d e d e e e ee e e ffd Zd e fdZd S)LibriLightLimitedaSubset of Libri-light :cite:`librilight` dataset, which was used in HuBERT :cite:`hsu2021hubert` for supervised fine-tuning. Args: root (str or Path): Path to the directory where the dataset is found or downloaded. subset (str, optional): The subset to use. Options: [``"10min"``, ``"1h"``, ``"10h"``] (Default: ``"10min"``). download (bool, optional): Whether to download the dataset if it is not found at root path. (default: ``False``). z .trans.txtz.flacrFrootsubsetdownloadrNc|tvr,tdtd|t|}tj|}tj|t|_tj|td}tj |js[|stdtj |stt|tt|t!|j||j|_dS)Nz`subset` must be one of z . Found: z.tgzz9Dataset not found. Please use `download=True` to download) hash_prefix) _SUBSET_MAP ValueErrorkeysosfspathrjoin _ARCHIVE_NAME_pathisdir RuntimeErrorisfiler _URL _CHECKSUMr r-r_fileids_paths)selfr0r1r2rarchives r__init__zLibriLightLimited.__init__?s  $ $] 8H8H8J8J]]U[]]^^ ^f%yW\\$ 66 ',,t %;%;%;<<w}}TZ(( " `"#^___7>>'** K$T7 JJJJ  ! ! !0WdoVVrnc|j|\}}t||j||j|j}t jtj |j|d\}}|f|ddzS)aLoad the n-th sample from the dataset. Args: n (int): The index of the sample to be loaded Returns: Tuple of the following items; Tensor: Waveform int: Sample rate str: Transcript int: Speaker ID int: Chapter ID int: Utterance ID rr$N) rBr r<r_ext_txt torchaudioloadr8rr:)rCrF file_pathfileidmetadatawaveform_s r __getitem__zLibriLightLimited.__getitem__Tsq*!/2 6,VTZDO]a]jkk obgll4:x{&K&KLL !{Xabb\))rc*t|jS)N)lenrB)rCs r__len__zLibriLightLimited.__len__ns4&'''r)rF)__name__ __module__ __qualname____doc__rHrrr rboolrEintrrrPrSrrrr/r/0s  HJ  WWCIWW W  WWWW**S*U63S#s+J%K****4(((((((rr/)r8pathlibrtypingrrrrItorchrtorch.utils.datartorchaudio._internalr torchaudio.datasets.librispeechr torchaudio.datasets.utilsr r;r@rAr5r r-r/rrrrasF %%%%%%%%%%$$$$$$555555EEEEEE222222) R N &$HH TDI34PUVY[^V^P_K`:?(?(?(?(?(?(?(?(?(?(r