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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 merge_with(self, other):
 """Returns a `TensorShape` combining the information in `self` and `other`. The dimensions in `self` and `other` are merged elementwise, according to the rules defined for `Dimension.merge_with()`. Args: other: Another `TensorShape`. Returns: A `TensorShape` containing the combined information of `self` and `other`. Raises: ValueError: If `self` and `other` are not convertible. """

        other = as_shape(other)
        if self._dims is None:
            return other
        else:
            try:
                self.assert_same_rank(other)
                new_dims = []
                for i, dim in enumerate(self._dims):
                    new_dims.append(dim.merge_with(other[i]))
                return TensorShape(new_dims)
            except ValueError:
                raise ValueError("Shapes %s and %s are not convertible" % (self, other))