def normalize(clip, mean, std, inplace=False):
    """
    Args:
        clip (torch.tensor): Video clip to be normalized. Size is (T, C, H, W)
        mean (tuple): pixel RGB mean. Size is (3)
        std (tuple): pixel standard deviation. Size is (3)
    Returns:
        normalized clip (torch.tensor): Size is (T, C, H, W)
    """
    if not _is_tensor_video_clip(clip):
        raise ValueError("clip should be a 4D torch.tensor")
    if not inplace:
        clip = clip.clone()
    mean = torch.as_tensor(mean, dtype=clip.dtype, device=clip.device)
    # print(mean)
    std = torch.as_tensor(std, dtype=clip.dtype, device=clip.device)
    clip.sub_(mean[:, None, None, None]).div_(std[:, None, None, None])
    return clip
Args:
clip (torch.tensor): Video clip to be normalized. Size is (T, C, H, W)
mean (tuple): pixel RGB mean. Size is (3)
std (tuple): pixel standard deviation. Size is (3)
Returns:
normalized clip (torch.tensor): Size is (T, C, H, W)
opensora/dataset/transform.py