def METHOD_NAME(self):
    affine_1 = np.array(
        [
            [1.499277e00, 2.699563e-02, 3.805804e-02, -1.948635e02],
            [-2.685805e-02, 1.499757e00, -2.635604e-12, 4.438188e01],
            [-3.805194e-02, -5.999028e-04, 1.499517e00, 4.036536e01],
            [0.000000e00, 0.000000e00, 0.000000e00, 1.000000e00],
        ]
    )
    affine_2 = np.array(
        [
            [1.499275e00, 2.692252e-02, 3.805728e-02, -1.948635e02],
            [-2.693010e-02, 1.499758e00, -4.260525e-05, 4.438188e01],
            [-3.805190e-02, -6.406730e-04, 1.499517e00, 4.036536e01],
            [0.000000e00, 0.000000e00, 0.000000e00, 1.000000e00],
        ]
    )
    img_1 = MetaTensor(np.zeros((1, 238, 145, 315)), affine=affine_1)
    img_2 = MetaTensor(np.zeros((1, 238, 145, 315)), affine=affine_2)
    out = Spacingd(("img_1", "img_2"), pixdim=1)({"img_1": img_1, "img_2": img_2})
    self.assertEqual(out["img_1"].shape, out["img_2"].shape)  # ensure_same_shape True
    out = Spacingd(("img_1", "img_2"), pixdim=1, ensure_same_shape=False)({"img_1": img_1, "img_2": img_2})
    self.assertNotEqual(out["img_1"].shape, out["img_2"].shape)  # ensure_same_shape False