datasets/AVideoDataset.py [124:153]:
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    valid_indices = [i for i, val in enumerate(all_indices) if val]
    return valid_indices


def get_video_container(path_to_vid, multi_thread_decode=False, backend="pyav"):
    """
    Given the path to the video, return the pyav video container.
    Args:
        path_to_vid (str): path to the video.
        multi_thread_decode (bool): if True, perform multi-thread decoding.
        backend (str): decoder backend, options include `pyav` and
            `torchvision`, default is `pyav`.
    Returns:
        container (container): video container.
    """
    if backend == "torchvision":
        with open(path_to_vid, "rb") as fp:
            container = fp.read()
        return container
    elif backend == "pyav":
        try:
            container = av.open(path_to_vid)
        except:
            container = av.open(path_to_vid, metadata_errors="ignore")
        if multi_thread_decode:
            # Enable multiple threads for decoding.
            container.streams.video[0].thread_type = "AUTO"
        return container
    else:
        raise NotImplementedError("Unknown backend {}".format(backend))
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datasets/GDTPretrainDataset.py [95:124]:
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    valid_indices = [i for i, val in enumerate(all_indices) if val]
    return valid_indices


def get_video_container(path_to_vid, multi_thread_decode=False, backend="pyav"):
    """
    Given the path to the video, return the pyav video container.
    Args:
        path_to_vid (str): path to the video.
        multi_thread_decode (bool): if True, perform multi-thread decoding.
        backend (str): decoder backend, options include `pyav` and
            `torchvision`, default is `pyav`.
    Returns:
        container (container): video container.
    """
    if backend == "torchvision":
        with open(path_to_vid, "rb") as fp:
            container = fp.read()
        return container
    elif backend == "pyav":
        try:
            container = av.open(path_to_vid)
        except:
            container = av.open(path_to_vid, metadata_errors="ignore")
        if multi_thread_decode:
            # Enable multiple threads for decoding.
            container.streams.video[0].thread_type = "AUTO"
        return container
    else:
        raise NotImplementedError("Unknown backend {}".format(backend))
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