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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 apply_inverse(self, y):
 """ Apply the inverse of the covariance matrix to a vector or matrix Solve ``K.x = y`` for ``x`` where ``K`` is the covariance matrix of the GP with the white noise and ``yerr`` components included on the diagonal. Args: y (array[n] or array[n, nrhs]):
 The vector or matrix ``y`` described above. Returns: array[n] or array[n, nrhs]: The solution to the linear system. This will have the same shape as ``y``. Raises: ValueError: For mismatched dimensions. """

        self._recompute()
        return self.solver.solve(self._process_input(y))