def _get_test_data(self, num_points, device, dtype):
        """Creates some test data.

        Batch size is fixed to 2 for all tests.
        """
        batch_size = 2
        torch.manual_seed(84)

        tau = 2 * 3.141592653589793
        axis_angle_1 = self._get_samples(shape=(1, 3), low=-tau, high=tau, dtype=dtype, device=device)
        axis_angle_2 = self._get_samples(shape=(1, 3), low=-tau, high=tau, dtype=dtype, device=device)
        rotation_1 = kornia.geometry.axis_angle_to_rotation_matrix(axis_angle_1)
        rotation_2 = kornia.geometry.axis_angle_to_rotation_matrix(axis_angle_2)

        translation_1 = self._get_samples(shape=(3,), low=-100, high=100, dtype=dtype, device=device)
        translation_2 = self._get_samples(shape=(3,), low=-100, high=100, dtype=dtype, device=device)

        temp = torch.eye(4, dtype=dtype, device=device)
        world_to_cam_mats = temp.unsqueeze(0).repeat(batch_size, 1, 1)
        world_to_cam_mats[0, :3, :3] = torch.squeeze(rotation_1)
        world_to_cam_mats[0, :3, 3] = translation_1
        world_to_cam_mats[1, :3, :3] = torch.squeeze(rotation_2)
        world_to_cam_mats[1, :3, 3] = translation_2

        intrinsic_1 = torch.tensor(
            [[500.0, 0.0, 250.0], [0.0, 500.0, 250.0], [0.0, 0.0, 1.0]], dtype=dtype, device=device
        )

        intrinsic_2 = torch.tensor(
            [[1000.0, 0.0, 550.0], [0.0, 750.0, 200.0], [0.0, 0.0, 1.0]], dtype=dtype, device=device
        )

        intrinsics = torch.stack([intrinsic_1, intrinsic_2], dim=0)

        cam_points_xy = self._get_samples(
            shape=(batch_size, num_points, 2), low=-100, high=100, dtype=dtype, device=device
        )
        cam_points_z = self._get_samples(
            shape=(batch_size, num_points, 1), low=0.5, high=100, dtype=dtype, device=device
        )
        cam_points = torch.cat([cam_points_xy, cam_points_z], dim=-1)

        repeated_intrinsics = intrinsics.unsqueeze(1).repeat(1, num_points, 1, 1)
        world_points, img_points = self._get_world_points_and_img_points(
            cam_points, world_to_cam_mats, repeated_intrinsics
        )
        world_to_cam_3x4 = world_to_cam_mats[:, :3, :]

        return intrinsics, world_to_cam_3x4, world_points, img_points
Creates some test data.

        Batch size is fixed to 2 for all tests.
        
tests/geometry/calibration/test_pnp.py