def _skip(x, mask):
    """
    Getting sliced (dim=0) tensor by mask. Supporting tensor and list/dict of tensors.
    """
    if isinstance(x, int):
        return x

    if x is None:
        return None

    if isinstance(x, torch.Tensor):
        if x.size(0) == mask.size(0):
            return x[mask]
        elif x.size(1) == mask.size(0):
            return x[:, mask]

    if isinstance(x, list):
        return [_skip(x_i, mask) for x_i in x]

    if isinstance(x, dict):
        return {k: _skip(v, mask) for k, v in x.items()}

    raise NotImplementedError
Getting sliced (dim=0) tensor by mask. Supporting tensor and list/dict of tensors.
fairseq/models/nat/levenshtein_utils.py