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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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)