Compute ``torch.equal`` with the optional mask parameter.

    Args:
        ignore_index (int, optional): Specifies a ``tensor`` index that is ignored.

    Returns:
        (bool) Returns ``True`` if target and prediction are equal.

def torch_equals_ignore_index(tensor, tensor_other, ignore_index=None):
    """
    Compute ``torch.equal`` with the optional mask parameter.

    Args:
        ignore_index (int, optional): Specifies a ``tensor`` index that is ignored.

    Returns:
        (bool) Returns ``True`` if target and prediction are equal.
    """
    if ignore_index is not None:
        assert tensor.size() == tensor_other.size()
        mask_arr = tensor.ne(ignore_index)
        tensor = tensor.masked_select(mask_arr)
        tensor_other = tensor_other.masked_select(mask_arr)

    return torch.equal(tensor, tensor_other)