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import logging |
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import os |
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import re |
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from typing import Optional |
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import huggingface_hub |
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import requests |
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from tqdm.auto import tqdm |
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_MODELS = ( |
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"medium" |
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) |
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def get_assets_path(): |
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"""Returns the path to the assets directory.""" |
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return os.path.join(os.path.dirname(os.path.abspath(__file__)), "assets") |
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def get_logger(): |
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"""Returns the module logger.""" |
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return logging.getLogger("faster_whisper") |
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def download_model( |
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size_or_id: str, |
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output_dir: Optional[str] = None, |
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local_files_only: bool = False, |
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cache_dir: Optional[str] = None, |
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): |
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"""Downloads a CTranslate2 Whisper model from the Hugging Face Hub. |
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The model is downloaded from https://huggingface.co/DuyTa. |
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Args: |
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size_or_id: Size of the model to download (tiny, tiny.en, base, base.en, small, small.en, |
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medium, medium.en, large-v1, or large-v2), or a CTranslate2-converted model ID |
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from the Hugging Face Hub (e.g. guillaumekln/faster-whisper-large-v2). |
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output_dir: Directory where the model should be saved. If not set, the model is saved in |
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the cache directory. |
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local_files_only: If True, avoid downloading the file and return the path to the local |
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cached file if it exists. |
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cache_dir: Path to the folder where cached files are stored. |
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Returns: |
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The path to the downloaded model. |
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Raises: |
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ValueError: if the model size is invalid. |
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""" |
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if re.match(r".*/.*", size_or_id): |
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repo_id = size_or_id |
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else: |
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if size_or_id not in _MODELS: |
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raise ValueError( |
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"Invalid model size '%s', expected one of: %s" |
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% (size_or_id, ", ".join(_MODELS)) |
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) |
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repo_id = "DuyTa/Vietnamese_ASR" |
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allow_patterns = [ |
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"config.json", |
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"model.bin", |
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"tokenizer.json", |
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"vocabulary.*", |
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] |
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kwargs = { |
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"local_files_only": local_files_only, |
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"allow_patterns": allow_patterns, |
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"tqdm_class": disabled_tqdm, |
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} |
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if output_dir is not None: |
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kwargs["local_dir"] = output_dir |
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kwargs["local_dir_use_symlinks"] = False |
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if cache_dir is not None: |
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kwargs["cache_dir"] = cache_dir |
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try: |
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return huggingface_hub.snapshot_download(repo_id, **kwargs) |
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except ( |
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huggingface_hub.utils.HfHubHTTPError, |
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requests.exceptions.ConnectionError, |
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) as exception: |
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logger = get_logger() |
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logger.warning( |
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"An error occured while synchronizing the model %s from the Hugging Face Hub:\n%s", |
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repo_id, |
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exception, |
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) |
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logger.warning( |
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"Trying to load the model directly from the local cache, if it exists." |
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) |
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kwargs["local_files_only"] = True |
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return huggingface_hub.snapshot_download(repo_id, **kwargs) |
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def format_timestamp( |
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seconds: float, |
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always_include_hours: bool = False, |
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decimal_marker: str = ".", |
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) -> str: |
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assert seconds >= 0, "non-negative timestamp expected" |
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milliseconds = round(seconds * 1000.0) |
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hours = milliseconds // 3_600_000 |
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milliseconds -= hours * 3_600_000 |
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minutes = milliseconds // 60_000 |
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milliseconds -= minutes * 60_000 |
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seconds = milliseconds // 1_000 |
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milliseconds -= seconds * 1_000 |
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hours_marker = f"{hours:02d}:" if always_include_hours or hours > 0 else "" |
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return ( |
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f"{hours_marker}{minutes:02d}:{seconds:02d}{decimal_marker}{milliseconds:03d}" |
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) |
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class disabled_tqdm(tqdm): |
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def __init__(self, *args, **kwargs): |
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kwargs["disable"] = True |
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super().__init__(*args, **kwargs) |
