def inverse_transform(self, x: Tensor) -> Tensor:
        r"""Apply the inverse transform to the whitened data.

        Args:
            x: Whitened data.

        Returns:
            Original data.

        """
        if not self.fitted:
            raise RuntimeError("Needs to be fitted first before running. Please call fit or set include_fit to True.")

        if not self.compute_inv:
            raise RuntimeError("Did not compute inverse ZCA. Please set compute_inv to True")

        if self.transform_inv is None:
            raise TypeError("The transform inverse should be a Tensor. Gotcha None.")

        mean_inv: Tensor = -self.mean_vector.mm(self.transform_matrix)

        y = linear_transform(x, self.transform_inv, mean_inv)

        return y
Apply the inverse transform to the whitened data.

        Args:
            x: Whitened data.

        Returns:
            Original data.

        
kornia/enhance/zca.py