def _compare(self, b, n, k, m, dtype, adjoint_a, adjoint_b):
    np.random.seed(42)
    x = np.random.normal(0, 1, ((b * n) * k)).astype(dtype).reshape([b, n, k])
    if (dtype in (np.complex64, np.complex128)):
        x.imag = np.random.normal(0, 1, ((b * n) * k)).astype(dtype).reshape([b, n, k])
    y = np.random.normal(0, 1, ((b * k) * m)).astype(dtype).reshape([b, k, m])
    if (dtype in (np.complex64, np.complex128)):
        y.imag = np.random.normal(0, 1, ((b * k) * m)).astype(dtype).reshape([b, k, m])
    self._checkGrad(x, y, adjoint_a, adjoint_b)
def _compare(self, b, n, k, m, dtype, adjoint_a, adjoint_b):
    np.random.seed(42)
    x = np.random.normal(0, 1, ((b * n) * k)).astype(dtype).reshape([b, n, k])
    if (dtype in (np.complex64, np.complex128)):
        x.imag = np.random.normal(0, 1, ((b * n) * k)).astype(dtype).reshape([b, n, k])
    y = np.random.normal(0, 1, ((b * k) * m)).astype(dtype).reshape([b, k, m])
    if (dtype in (np.complex64, np.complex128)):
        y.imag = np.random.normal(0, 1, ((b * k) * m)).astype(dtype).reshape([b, k, m])
    self._checkGrad(x, y, adjoint_a, adjoint_b)