common/sampler.py [70:82]:
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    def __init__(self, video_clips, max_clips_per_video):
        if not isinstance(video_clips, torchvision.datasets.video_utils.VideoClips):
            raise TypeError("Expected video_clips to be an instance of VideoClips, "
                            "got {}".format(type(video_clips)))
        self.video_clips = video_clips
        self.max_clips_per_video = max_clips_per_video

    def __iter__(self):
        idxs = []
        s = 0
        # select at most max_clips_per_video for each video, uniformly spaced
        for c in self.video_clips.clips:
            length = len(c)
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common/sampler.py [102:114]:
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    def __init__(self, video_clips, max_clips_per_video):
        if not isinstance(video_clips, torchvision.datasets.video_utils.VideoClips):
            raise TypeError("Expected video_clips to be an instance of VideoClips, "
                            "got {}".format(type(video_clips)))
        self.video_clips = video_clips
        self.max_clips_per_video = max_clips_per_video

    def __iter__(self):
        idxs = []
        s = 0
        # select at most max_clips_per_video for each video, randomly
        for c in self.video_clips.clips:
            length = len(c)
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