*`` where `T` is the length of the
    longest sequence (equal to ``lengths[0]``), ``B`` is the batch size, and
    ``*`` is any number of dimensions (including 0). If ``batch_first`` is
    ``True``, ``B x T x *`` :attr:`input` is expected.

    For unsorted sequences, use `enforce_sorted = False`. If :attr:`enforce_sorted` is
    ``True``, the sequences should be sorted by length in a decreasing order, i.e.
    ``input[:,0]`` should be the longest sequence, and ``input[:,B-1]`` the shortest
    one. `enforce_sorted = True` is only necessary for ONNX export.

    Note:
        This function accepts any input that has at least two dimensions. You
        can apply it to pack the labels, and use the output of the RNN with
        them to compute the loss directly. A Tensor can be retrieved from
        a :class:`PackedSequence` object by accessing its ``.data`` attribute.

    Args:
        input (Tensor): padded batch of variable length sequences.
        lengths (Tensor or list(int)): list of sequence lengths of each batch
            element (must be on the CPU if provided as a tensor).
        batch_first (bool, optional): if ``True``, the input is expected in ``B x T x *``
            format.
        enforce_sorted (bool, optional): if ``True``, the input is expected to
            contain sequences sorted by length in a decreasing order. If
            ``False``, the input will get sorted unconditionally. Default: ``True``.

    Returns:
        a :class:`PackedSequence` object
    zôpack_padded_sequence has been called with a Python list of sequence lengths. The tracer cannot track the data flow of Python values, and it will treat them as constants, likely rendering the trace incorrect for any other combination of lengths.rX