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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 zero(self):
 """Function mapping anything to zero."""

        # Since `FunctionSpace.lincomb` may be slow, we implement this
        # function directly.
        # The unused **kwargs are needed to support combination with
        # functions that take parameters.
        def zero_vec(x, out=None, **kwargs):
            """Zero function, vectorized."""
            if is_valid_input_meshgrid(x, self.domain.ndim):
                scalar_out_shape = out_shape_from_meshgrid(x)
            elif is_valid_input_array(x, self.domain.ndim):
                scalar_out_shape = out_shape_from_array(x)
            else:
                raise TypeError('invalid input type')

            # For tensor-valued functions
            out_shape = self.out_shape + scalar_out_shape

            if out is None:
                return np.zeros(out_shape, dtype=self.scalar_out_dtype)
            else:
                # Need to go through an array to fill with the correct
                # zero value for all dtypes
                fill_value = np.zeros(1, dtype=self.scalar_out_dtype)[0]
                out.fill(fill_value)

        return self.element_type(self, zero_vec)