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Optional Numpy Compute Backend #3075

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Optional Numpy Compute Backend

Optional Numpy Compute Backend #3075

GitHub Actions / Test Results succeeded Dec 12, 2024 in 1s

46 passed, 8 failed and 7 skipped

Tests failed

Report Passed Failed Skipped Time
12302141302-tests-test_controllers/test_controllers.xml 1✅ 657s
12302141302-tests-test_curobo/test_curobo.xml 1❌ 598s
12302141302-tests-test_multiple_envs/test_multiple_envs.xml 8✅ 2⚪ 565s
12302141302-tests-test_primitives/test_primitives.xml 6❌ 4⚪ 550s
12302141302-tests-test_robot_states_no_flatcache/test_robot_states_no_flatcache.xml 3✅ 592s
12302141302-tests-test_robot_teleoperation/test_robot_teleoperation.xml 1⚪ 30ms
12302141302-tests-test_scene_graph/test_scene_graph.xml 1❌ 476s
12302141302-tests-test_transform_utils/test_transform_utils.xml 34✅ 128s

✅ 12302141302-tests-test_controllers/test_controllers.xml

1 tests were completed in 657s with 1 passed, 0 failed and 0 skipped.

Test suite Passed Failed Skipped Time
pytest 1✅ 657s

✅ pytest

tests.test_controllers
  ✅ test_arm_control

❌ 12302141302-tests-test_curobo/test_curobo.xml

1 tests were completed in 598s with 0 passed, 1 failed and 0 skipped.

Test suite Passed Failed Skipped Time
pytest 1❌ 598s

❌ pytest

tests.test_curobo
  ❌ test_curobo
	def test_curobo():

✅ 12302141302-tests-test_multiple_envs/test_multiple_envs.xml

10 tests were completed in 565s with 8 passed, 0 failed and 2 skipped.

Test suite Passed Failed Skipped Time
pytest 8✅ 2⚪ 565s

✅ pytest

tests.test_multiple_envs
  ✅ test_multi_scene_dump_load_states
  ✅ test_multi_scene_get_local_position
  ✅ test_multi_scene_set_local_position
  ✅ test_multi_scene_scene_prim
  ✅ test_multi_scene_particle_source
  ✅ test_multi_scene_position_orientation_relative_to_scene
  ✅ test_tiago_getter
  ✅ test_tiago_setter
  ⚪ test_behavior_getter
  ⚪ test_behavior_setter

❌ 12302141302-tests-test_primitives/test_primitives.xml

10 tests were completed in 550s with 0 passed, 6 failed and 4 skipped.

Test suite Passed Failed Skipped Time
pytest 6❌ 4⚪ 550s

❌ pytest

tests.test_primitives.TestPrimitives
  ❌ test_navigate[Tiago]
	self = <test_primitives.TestPrimitives object at 0x7f0e4f9a7520>
  ❌ test_navigate[Fetch]
	self = <test_primitives.TestPrimitives object at 0x7f0e4f9a6530>
  ❌ test_grasp[Tiago]
	self = <test_primitives.TestPrimitives object at 0x7f0e4f9a7a60>
  ❌ test_grasp[Fetch]
	self = <test_primitives.TestPrimitives object at 0x7f0e4f9a4670>
  ❌ test_place[Tiago]
	self = <test_primitives.TestPrimitives object at 0x7f0e4f9a5600>
  ❌ test_place[Fetch]
	self = <test_primitives.TestPrimitives object at 0x7f0e4f9a52d0>
  ⚪ test_open_prismatic[Tiago]
  ⚪ test_open_prismatic[Fetch]
  ⚪ test_open_revolute[Tiago]
  ⚪ test_open_revolute[Fetch]

✅ 12302141302-tests-test_robot_states_no_flatcache/test_robot_states_no_flatcache.xml

3 tests were completed in 592s with 3 passed, 0 failed and 0 skipped.

Test suite Passed Failed Skipped Time
pytest 3✅ 592s

✅ pytest

tests.test_robot_states_no_flatcache
  ✅ test_camera_pose_flatcache_off
  ✅ test_camera_semantic_segmentation
  ✅ test_object_in_FOV_of_robot

✅ 12302141302-tests-test_robot_teleoperation/test_robot_teleoperation.xml

1 tests were completed in 30ms with 0 passed, 0 failed and 1 skipped.

Test suite Passed Failed Skipped Time
pytest 1⚪ 30ms

✅ pytest

tests.test_robot_teleoperation
  ⚪ test_teleop

❌ 12302141302-tests-test_scene_graph/test_scene_graph.xml

1 tests were completed in 476s with 0 passed, 1 failed and 0 skipped.

Test suite Passed Failed Skipped Time
pytest 1❌ 476s

❌ pytest

tests.test_scene_graph
  ❌ test_scene_graph
	def test_scene_graph():

✅ 12302141302-tests-test_transform_utils/test_transform_utils.xml

34 tests were completed in 128s with 34 passed, 0 failed and 0 skipped.

Test suite Passed Failed Skipped Time
pytest 34✅ 128s

✅ pytest

tests.test_transform_utils.TestQuaternionOperations
  ✅ test_quat2mat_special_cases
  ✅ test_quat_multiply
  ✅ test_quat_conjugate
  ✅ test_quat_inverse
  ✅ test_quat_distance
tests.test_transform_utils.TestVectorOperations
  ✅ test_normalize
  ✅ test_dot_product
  ✅ test_l2_distance
tests.test_transform_utils.TestMatrixOperations
  ✅ test_rotation_matrix_properties
  ✅ test_rotation_matrix
  ✅ test_transformation_matrix
  ✅ test_transformation_matrix_no_point
  ✅ test_matrix_inverse
tests.test_transform_utils.TestCoordinateTransformations
  ✅ test_cartesian_to_polar
tests.test_transform_utils.TestPoseTransformations
  ✅ test_pose2mat_and_mat2pose
  ✅ test_pose_inv
tests.test_transform_utils.TestAxisAngleConversions
  ✅ test_axisangle2quat_and_quat2axisangle
  ✅ test_vecs2axisangle
  ✅ test_vecs2quat
tests.test_transform_utils.TestEulerAngleConversions
  ✅ test_euler2quat_and_quat2euler
  ✅ test_euler2mat_and_mat2euler
tests.test_transform_utils.TestQuaternionApplications
  ✅ test_quat_apply
  ✅ test_quat_slerp
tests.test_transform_utils.TestTransformPoints
  ✅ test_transform_points_2d
  ✅ test_transform_points_3d
tests.test_transform_utils.TestMiscellaneousFunctions
  ✅ test_convert_quat
  ✅ test_random_quaternion
  ✅ test_random_axis_angle
  ✅ test_align_vector_sets
  ✅ test_copysign
  ✅ test_anorm
  ✅ test_check_quat_right_angle
  ✅ test_z_angle_from_quat
  ✅ test_integer_spiral_coordinates

Annotations

Check failure on line 0 in 12302141302-tests-test_curobo/test_curobo.xml

See this annotation in the file changed.

@github-actions github-actions / Test Results

pytest ► tests.test_curobo ► test_curobo 

Failed test found in:
  12302141302-tests-test_curobo/test_curobo.xml
Error:
  def test_curobo():
Raw output 
def test_curobo():
        # Make sure object states are enabled
        assert gm.ENABLE_OBJECT_STATES
    
        # Create env
        cfg = {
            "env": {
                "action_frequency": 30,
                "physics_frequency": 300,
            },
            "scene": {
                "type": "Scene",
            },
            "objects": [
                {
                    "type": "PrimitiveObject",
                    "name": "obj0",
                    "primitive_type": "Cube",
                    "scale": [0.4, 0.4, 0.4],
                    "fixed_base": True,
                    "position": [0.5, -0.1, 0.2],
                    "orientation": [0, 0, 0, 1],
                },
                {
                    "type": "PrimitiveObject",
                    "name": "eef_marker_0",
                    "primitive_type": "Sphere",
                    "radius": 0.05,
                    "visual_only": True,
                    "position": [0, 0, 0],
                    "orientation": [0, 0, 0, 1],
                    "rgba": [1, 0, 0, 1],
                },
                {
                    "type": "PrimitiveObject",
                    "name": "eef_marker_1",
                    "primitive_type": "Sphere",
                    "radius": 0.05,
                    "visual_only": True,
                    "position": [0, 0, 0],
                    "orientation": [0, 0, 0, 1],
                    "rgba": [0, 1, 0, 1],
                },
            ],
            "robots": [],
        }
    
        robot_cfgs = [
            {
                "type": "FrankaPanda",
                "obs_modalities": "rgb",
                "position": [0.7, -0.55, 0.0],
                "orientation": [0, 0, 0.707, 0.707],
                "self_collisions": True,
                "action_normalize": False,
                "controller_config": {
                    "arm_0": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "gripper_0": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                },
            },
            {
                "type": "R1",
                "obs_modalities": "rgb",
                "position": [0.7, -0.7, 0.056],
                "orientation": [0, 0, 0.707, 0.707],
                "self_collisions": True,
                "action_normalize": False,
                "controller_config": {
                    "base": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "trunk": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "arm_left": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "arm_right": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "gripper_left": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "gripper_right": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                },
            },
            {
                "type": "Tiago",
                "obs_modalities": "rgb",
                "position": [0.7, -0.85, 0],
                "orientation": [0, 0, 0.707, 0.707],
                "self_collisions": True,
                "action_normalize": False,
                "controller_config": {
                    "base": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "trunk": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "camera": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "arm_left": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "arm_right": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "gripper_left": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                    "gripper_right": {
                        "name": "JointController",
                        "motor_type": "position",
                        "command_input_limits": None,
                        "use_delta_commands": False,
                        "use_impedances": True,
                    },
                },
            },
        ]
        for robot_cfg in robot_cfgs:
            cfg["robots"] = [robot_cfg]
    
            env = og.Environment(configs=cfg)
            robot = env.robots[0]
            obj = env.scene.object_registry("name", "obj0")
            eef_markers = [env.scene.object_registry("name", f"eef_marker_{i}") for i in range(2)]
    
            floor_touching_base_link_prim_paths = (
                [os.path.join(robot.prim_path, link_name) for link_name in robot.floor_touching_base_link_names]
                if isinstance(robot, LocomotionRobot)
                else []
            )
    
            robot.reset()
    
            # Open the gripper(s) to match cuRobo's default state
            for arm_name in robot.gripper_control_idx.keys():
                gripper_control_idx = robot.gripper_control_idx[arm_name]
                robot.set_joint_positions(th.ones_like(gripper_control_idx), indices=gripper_control_idx, normalized=True)
    
            robot.keep_still()
    
            for _ in range(5):
                og.sim.step()
    
            env.scene.update_initial_state()
            env.scene.reset()
    
            # Create CuRobo instance
            batch_size = 2
            n_samples = 20
    
            cmg = CuRoboMotionGenerator(
                robot=robot,
                batch_size=batch_size,
                debug=False,
                use_cuda_graph=True,
                use_default_embodiment_only=True,
            )
    
            # Sample values for robot
            th.manual_seed(1)
            lo, hi = robot.joint_lower_limits.clone().view(1, -1), robot.joint_upper_limits.clone().view(1, -1)
    
            if isinstance(robot, HolonomicBaseRobot):
                lo[0, :2] = -0.1
                lo[0, 2:5] = 0.0
                lo[0, 5] = -math.pi
                hi[0, :2] = 0.1
                hi[0, 2:5] = 0.0
                hi[0, 5] = math.pi
    
            random_qs = lo + th.rand((n_samples, robot.n_dof)) * (hi - lo)
    
            # Test collision with the environment (not including self-collisions)
            collision_results = cmg.check_collisions(q=random_qs)
    
            target_pos, target_quat = defaultdict(list), defaultdict(list)
    
            floor_plane_prim_paths = {child.GetPath().pathString for child in og.sim.floor_plane._prim.GetChildren()}
    
            # View results
            false_positive = 0
            false_negative = 0
    
            target_pos_in_world_frame = defaultdict(list)
            for i, (q, curobo_has_contact) in enumerate(zip(random_qs, collision_results)):
                # Set robot to desired qpos
                robot.set_joint_positions(q)
                robot.keep_still()
                og.sim.step_physics()
    
                # To debug
                # cmg.save_visualization(robot.get_joint_positions(), "/scr/chengshu/Downloads/test.obj")
    
                # Sanity check in the GUI that the robot pose makes sense
                for _ in range(10):
                    og.sim.render()
    
                # Validate that expected collision result is correct
                self_collision_pairs = set()
                floor_contact_pairs = set()
                wheel_contact_pairs = set()
                obj_contact_pairs = set()
    
                for contact in robot.contact_list():
                    assert contact.body0 in robot.link_prim_paths
                    if contact.body1 in robot.link_prim_paths:
                        self_collision_pairs.add((contact.body0, contact.body1))
                    elif contact.body1 in floor_plane_prim_paths:
                        if contact.body0 not in floor_touching_base_link_prim_paths:
                            floor_contact_pairs.add((contact.body0, contact.body1))
                        else:
                            wheel_contact_pairs.add((contact.body0, contact.body1))
                    elif contact.body1 in obj.link_prim_paths:
                        obj_contact_pairs.add((contact.body0, contact.body1))
                    else:
                        assert False, f"Unexpected contact pair: {contact.body0}, {contact.body1}"
    
                touching_itself = len(self_collision_pairs) > 0
                touching_floor = len(floor_contact_pairs) > 0
                touching_object = len(obj_contact_pairs) > 0
    
                curobo_has_contact = curobo_has_contact.item()
                physx_has_contact = touching_itself or touching_floor or touching_object
    
                # cuRobo reports contact, but physx reports no contact
                if curobo_has_contact and not physx_has_contact:
                    false_positive += 1
                    print(
                        f"False positive {i}: {curobo_has_contact} vs. {physx_has_contact} (touching_itself/obj/floor: {touching_itself}/{touching_object}/{touching_floor})"
                    )
    
                # physx reports contact, but cuRobo reports no contact
                elif not curobo_has_contact and physx_has_contact:
                    false_negative += 1
                    print(
                        f"False negative {i}: {curobo_has_contact} vs. {physx_has_contact} (touching_itself/obj/floor: {touching_itself}/{touching_object}/{touching_floor})"
                    )
    
                # neither cuRobo nor physx reports contact, valid planning goals
                elif not curobo_has_contact and not physx_has_contact:
                    for arm_name in robot.arm_names:
                        # For holonomic base robots, we need to be in the frame of @robot.root_link, not @robot.base_footprint_link
                        if isinstance(robot, HolonomicBaseRobot):
                            base_link_pose = robot.root_link.get_position_orientation()
                            eef_link_pose = robot.eef_links[arm_name].get_position_orientation()
                            eef_pos, eef_quat = T.relative_pose_transform(*eef_link_pose, *base_link_pose)
                        else:
                            eef_pos, eef_quat = robot.get_relative_eef_pose(arm_name)
    
                        target_pos[robot.eef_link_names[arm_name]].append(eef_pos)
                        target_quat[robot.eef_link_names[arm_name]].append(eef_quat)
    
                        target_pos_in_world_frame[robot.eef_link_names[arm_name]].append(robot.get_eef_position(arm_name))
    
            print(
                f"Collision checking false positive: {false_positive / n_samples}, false negative: {false_negative / n_samples}."
            )
            assert (
                false_positive / n_samples == 0.0
            ), f"Collision checking false positive rate: {false_positive / n_samples}, should be == 0.0."
            assert (
                false_negative / n_samples == 0.0
            ), f"Collision checking false negative rate: {false_negative / n_samples}, should be == 0.0."
    
            env.scene.reset()
    
            for arm_name in robot.arm_names:
                target_pos[robot.eef_link_names[arm_name]] = th.stack(target_pos[robot.eef_link_names[arm_name]], dim=0)
                target_quat[robot.eef_link_names[arm_name]] = th.stack(target_quat[robot.eef_link_names[arm_name]], dim=0)
                target_pos_in_world_frame[robot.eef_link_names[arm_name]] = th.stack(
                    target_pos_in_world_frame[robot.eef_link_names[arm_name]], dim=0
                )
    
            # Cast defaultdict to dict
            target_pos = dict(target_pos)
            target_quat = dict(target_quat)
            target_pos_in_world_frame = dict(target_pos_in_world_frame)
    
            print(f"Planning for {len(target_pos[robot.eef_link_names[robot.default_arm]])} eef targets...")
    
            # Generate collision-free trajectories to the sampled eef poses (including self-collisions)
            successes, traj_paths = cmg.compute_trajectories(
                target_pos=target_pos,
                target_quat=target_quat,
                is_local=True,
                max_attempts=1,
                timeout=60.0,
                ik_fail_return=5,
                enable_finetune_trajopt=True,
                finetune_attempts=1,
                return_full_result=False,
                success_ratio=1.0,
                attached_obj=None,
            )
    
            # Make sure collision-free trajectories are generated
            success_rate = successes.double().mean().item()
            print(f"Collision-free trajectory generation success rate: {success_rate}")
            assert success_rate == 1.0, f"Collision-free trajectory generation success rate: {success_rate}"
    
            # 1cm and 3 degrees error tolerance for prismatic and revolute joints, respectively
            error_tol = th.tensor(
                [0.01 if joint.joint_type == "PrismaticJoint" else 3.0 / 180.0 * math.pi for joint in robot.joints.values()]
            )
    
            # for bypass_physics in [True, False]:
            for bypass_physics in [True]:
                for traj_idx, (success, traj_path) in enumerate(zip(successes, traj_paths)):
                    if not success:
                        continue
    
                    # Reset the environment
                    env.scene.reset()
    
                    # Move the markers to the desired eef positions
                    for marker, arm_name in zip(eef_markers, robot.arm_names):
                        eef_link_name = robot.eef_link_names[arm_name]
                        marker.set_position_orientation(position=target_pos_in_world_frame[eef_link_name][traj_idx])
    
                    q_traj = cmg.path_to_joint_trajectory(traj_path)
                    # joint_positions_set_point = []
                    # joint_positions_response = []
                    for i, q in enumerate(q_traj):
                        if bypass_physics:
                            print(f"Teleporting waypoint {i}/{len(q_traj)}")
                            robot.set_joint_positions(q)
                            robot.keep_still()
                            og.sim.step()
                            for contact in robot.contact_list():
                                assert contact.body0 in robot.link_prim_paths
                                if (
                                    contact.body1 in floor_plane_prim_paths
                                    and contact.body0 in floor_touching_base_link_prim_paths
                                ):
                                    continue
                                if th.tensor(list(contact.impulse)).norm() == 0:
                                    continue
                                print(f"Unexpected contact pair during traj rollout: {contact.body0}, {contact.body1}")
>                               assert (
                                    False
                                ), f"Unexpected contact pair during traj rollout: {contact.body0}, {contact.body1}"
E                               AssertionError: Unexpected contact pair during traj rollout: /World/scene_0/controllable__r1__robot_yybcvt/left_arm_link6, /World/scene_0/controllable__r1__robot_yybcvt/left_arm_link1
E                               assert False

tests/test_curobo.py:422: AssertionError

Check failure on line 0 in 12302141302-tests-test_primitives/test_primitives.xml

See this annotation in the file changed.

@github-actions github-actions / Test Results

pytest ► tests.test_primitives.TestPrimitives ► test_navigate[Tiago] 

Failed test found in:
  12302141302-tests-test_primitives/test_primitives.xml
Error:
  self = <test_primitives.TestPrimitives object at 0x7f0e4f9a7520>
Raw output 
self = <test_primitives.TestPrimitives object at 0x7f0e4f9a7520>
robot = 'Tiago'

    def test_navigate(self, robot):
        categories = ["floors", "ceilings", "walls"]
        env = setup_environment(categories, robot=robot)
    
        objects = []
        obj_1 = {
            "object": DatasetObject(name="cologne", category="bottle_of_cologne", model="lyipur"),
            "position": [-0.3, -0.8, 0.5],
            "orientation": [0, 0, 0, 1],
        }
        objects.append(obj_1)
    
        primitives = [StarterSemanticActionPrimitiveSet.NAVIGATE_TO]
        primitives_args = [(obj_1["object"],)]
    
>       primitive_tester(env, objects, primitives, primitives_args)

tests/test_primitives.py:105: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
tests/test_primitives.py:82: in primitive_tester
    execute_controller(controller.apply_ref(primitive, *args, attempts=1), env)
tests/test_primitives.py:69: in execute_controller
    for action in ctrl_gen:
omnigibson/action_primitives/starter_semantic_action_primitives.py:518: in apply_ref
    yield from ctrl(*args)
omnigibson/action_primitives/starter_semantic_action_primitives.py:1682: in _navigate_to_obj
    pose = self._sample_pose_near_object(obj, pose_on_obj=pose_on_obj, **kwargs)
omnigibson/action_primitives/starter_semantic_action_primitives.py:1808: in _sample_pose_near_object
    with PlanningContext(self.env, self.robot, self.robot_copy, "simplified") as context:
omnigibson/action_primitives/starter_semantic_action_primitives.py:146: in __enter__
    self._assemble_robot_copy()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <omnigibson.action_primitives.starter_semantic_action_primitives.PlanningContext object at 0x7f0e40d1bfd0>

    def _assemble_robot_copy(self):
        if m.TIAGO_TORSO_FIXED:
            fk_descriptor = "left_fixed"
        else:
            fk_descriptor = (
>               "combined" if "combined" in self.robot.robot_arm_descriptor_yamls else self.robot.default_arm
            )
E           AttributeError: 'Tiago' object has no attribute 'robot_arm_descriptor_yamls'

omnigibson/action_primitives/starter_semantic_action_primitives.py:160: AttributeError

Check failure on line 0 in 12302141302-tests-test_primitives/test_primitives.xml

See this annotation in the file changed.

@github-actions github-actions / Test Results

pytest ► tests.test_primitives.TestPrimitives ► test_navigate[Fetch] 

Failed test found in:
  12302141302-tests-test_primitives/test_primitives.xml
Error:
  self = <test_primitives.TestPrimitives object at 0x7f0e4f9a6530>
Raw output 
self = <test_primitives.TestPrimitives object at 0x7f0e4f9a6530>
robot = 'Fetch'

    def test_navigate(self, robot):
        categories = ["floors", "ceilings", "walls"]
        env = setup_environment(categories, robot=robot)
    
        objects = []
        obj_1 = {
            "object": DatasetObject(name="cologne", category="bottle_of_cologne", model="lyipur"),
            "position": [-0.3, -0.8, 0.5],
            "orientation": [0, 0, 0, 1],
        }
        objects.append(obj_1)
    
        primitives = [StarterSemanticActionPrimitiveSet.NAVIGATE_TO]
        primitives_args = [(obj_1["object"],)]
    
>       primitive_tester(env, objects, primitives, primitives_args)

tests/test_primitives.py:105: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
tests/test_primitives.py:82: in primitive_tester
    execute_controller(controller.apply_ref(primitive, *args, attempts=1), env)
tests/test_primitives.py:69: in execute_controller
    for action in ctrl_gen:
omnigibson/action_primitives/starter_semantic_action_primitives.py:518: in apply_ref
    yield from ctrl(*args)
omnigibson/action_primitives/starter_semantic_action_primitives.py:1682: in _navigate_to_obj
    pose = self._sample_pose_near_object(obj, pose_on_obj=pose_on_obj, **kwargs)
omnigibson/action_primitives/starter_semantic_action_primitives.py:1808: in _sample_pose_near_object
    with PlanningContext(self.env, self.robot, self.robot_copy, "simplified") as context:
omnigibson/action_primitives/starter_semantic_action_primitives.py:146: in __enter__
    self._assemble_robot_copy()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <omnigibson.action_primitives.starter_semantic_action_primitives.PlanningContext object at 0x7f0e4c9165c0>

    def _assemble_robot_copy(self):
        if m.TIAGO_TORSO_FIXED:
            fk_descriptor = "left_fixed"
        else:
            fk_descriptor = (
>               "combined" if "combined" in self.robot.robot_arm_descriptor_yamls else self.robot.default_arm
            )
E           AttributeError: 'Fetch' object has no attribute 'robot_arm_descriptor_yamls'

omnigibson/action_primitives/starter_semantic_action_primitives.py:160: AttributeError

Check failure on line 0 in 12302141302-tests-test_primitives/test_primitives.xml

See this annotation in the file changed.

@github-actions github-actions / Test Results

pytest ► tests.test_primitives.TestPrimitives ► test_grasp[Tiago] 

Failed test found in:
  12302141302-tests-test_primitives/test_primitives.xml
Error:
  self = <test_primitives.TestPrimitives object at 0x7f0e4f9a7a60>
Raw output 
self = <test_primitives.TestPrimitives object at 0x7f0e4f9a7a60>
robot = 'Tiago'

    def test_grasp(self, robot):
        categories = ["floors", "ceilings", "walls", "coffee_table"]
        env = setup_environment(categories, robot=robot)
    
        objects = []
        obj_1 = {
            "object": DatasetObject(name="cologne", category="bottle_of_cologne", model="lyipur"),
            "position": [-0.3, -0.8, 0.5],
            "orientation": [0, 0, 0, 1],
        }
        objects.append(obj_1)
    
        primitives = [StarterSemanticActionPrimitiveSet.GRASP]
        primitives_args = [(obj_1["object"],)]
    
>       primitive_tester(env, objects, primitives, primitives_args)

tests/test_primitives.py:122: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
tests/test_primitives.py:82: in primitive_tester
    execute_controller(controller.apply_ref(primitive, *args, attempts=1), env)
tests/test_primitives.py:69: in execute_controller
    for action in ctrl_gen:
omnigibson/action_primitives/starter_semantic_action_primitives.py:518: in apply_ref
    yield from ctrl(*args)
omnigibson/action_primitives/starter_semantic_action_primitives.py:743: in _grasp
    yield from self._navigate_if_needed(obj, pose_on_obj=grasp_pose)
omnigibson/action_primitives/starter_semantic_action_primitives.py:1663: in _navigate_if_needed
    if self._target_in_reach_of_robot(pose_on_obj):
omnigibson/action_primitives/starter_semantic_action_primitives.py:913: in _target_in_reach_of_robot
    return self._target_in_reach_of_robot_relative(relative_target_pose)
omnigibson/action_primitives/starter_semantic_action_primitives.py:925: in _target_in_reach_of_robot_relative
    return self._ik_solver_cartesian_to_joint_space(relative_target_pose) is not None
omnigibson/action_primitives/starter_semantic_action_primitives.py:965: in _ik_solver_cartesian_to_joint_space
    robot_description_path=self._manipulation_descriptor_path,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <omnigibson.action_primitives.starter_semantic_action_primitives.StarterSemanticActionPrimitives object at 0x7f0e38d34c70>

    @property
    def _manipulation_descriptor_path(self):
        """The appropriate manipulation descriptor for the current settings."""
        if isinstance(self.robot, Tiago) and m.TIAGO_TORSO_FIXED:
            assert self.arm == "left", "Fixed torso mode only supports left arm!"
            return self.robot.robot_arm_descriptor_yamls["left_fixed"]
    
        # Otherwise just return the default arm control idx
>       return self.robot.robot_arm_descriptor_yamls[self.arm]
E       AttributeError: 'Tiago' object has no attribute 'robot_arm_descriptor_yamls'

omnigibson/action_primitives/starter_semantic_action_primitives.py:950: AttributeError

Check failure on line 0 in 12302141302-tests-test_primitives/test_primitives.xml

See this annotation in the file changed.

@github-actions github-actions / Test Results

pytest ► tests.test_primitives.TestPrimitives ► test_grasp[Fetch] 

Failed test found in:
  12302141302-tests-test_primitives/test_primitives.xml
Error:
  self = <test_primitives.TestPrimitives object at 0x7f0e4f9a4670>
Raw output 
self = <test_primitives.TestPrimitives object at 0x7f0e4f9a4670>
robot = 'Fetch'

    def test_grasp(self, robot):
        categories = ["floors", "ceilings", "walls", "coffee_table"]
        env = setup_environment(categories, robot=robot)
    
        objects = []
        obj_1 = {
            "object": DatasetObject(name="cologne", category="bottle_of_cologne", model="lyipur"),
            "position": [-0.3, -0.8, 0.5],
            "orientation": [0, 0, 0, 1],
        }
        objects.append(obj_1)
    
        primitives = [StarterSemanticActionPrimitiveSet.GRASP]
        primitives_args = [(obj_1["object"],)]
    
>       primitive_tester(env, objects, primitives, primitives_args)

tests/test_primitives.py:122: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
tests/test_primitives.py:82: in primitive_tester
    execute_controller(controller.apply_ref(primitive, *args, attempts=1), env)
tests/test_primitives.py:69: in execute_controller
    for action in ctrl_gen:
omnigibson/action_primitives/starter_semantic_action_primitives.py:518: in apply_ref
    yield from ctrl(*args)
omnigibson/action_primitives/starter_semantic_action_primitives.py:743: in _grasp
    yield from self._navigate_if_needed(obj, pose_on_obj=grasp_pose)
omnigibson/action_primitives/starter_semantic_action_primitives.py:1663: in _navigate_if_needed
    if self._target_in_reach_of_robot(pose_on_obj):
omnigibson/action_primitives/starter_semantic_action_primitives.py:913: in _target_in_reach_of_robot
    return self._target_in_reach_of_robot_relative(relative_target_pose)
omnigibson/action_primitives/starter_semantic_action_primitives.py:925: in _target_in_reach_of_robot_relative
    return self._ik_solver_cartesian_to_joint_space(relative_target_pose) is not None
omnigibson/action_primitives/starter_semantic_action_primitives.py:965: in _ik_solver_cartesian_to_joint_space
    robot_description_path=self._manipulation_descriptor_path,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <omnigibson.action_primitives.starter_semantic_action_primitives.StarterSemanticActionPrimitives object at 0x7f0e42b39210>

    @property
    def _manipulation_descriptor_path(self):
        """The appropriate manipulation descriptor for the current settings."""
        if isinstance(self.robot, Tiago) and m.TIAGO_TORSO_FIXED:
            assert self.arm == "left", "Fixed torso mode only supports left arm!"
            return self.robot.robot_arm_descriptor_yamls["left_fixed"]
    
        # Otherwise just return the default arm control idx
>       return self.robot.robot_arm_descriptor_yamls[self.arm]
E       AttributeError: 'Fetch' object has no attribute 'robot_arm_descriptor_yamls'

omnigibson/action_primitives/starter_semantic_action_primitives.py:950: AttributeError

Check failure on line 0 in 12302141302-tests-test_primitives/test_primitives.xml

See this annotation in the file changed.

@github-actions github-actions / Test Results

pytest ► tests.test_primitives.TestPrimitives ► test_place[Tiago] 

Failed test found in:
  12302141302-tests-test_primitives/test_primitives.xml
Error:
  self = <test_primitives.TestPrimitives object at 0x7f0e4f9a5600>
Raw output 
self = <test_primitives.TestPrimitives object at 0x7f0e4f9a5600>
robot = 'Tiago'

    def test_place(self, robot):
        categories = ["floors", "ceilings", "walls", "coffee_table"]
        env = setup_environment(categories, robot=robot)
    
        objects = []
        obj_1 = {
            "object": DatasetObject(name="table", category="breakfast_table", model="rjgmmy", scale=[0.3, 0.3, 0.3]),
            "position": [-0.7, 0.5, 0.2],
            "orientation": [0, 0, 0, 1],
        }
        obj_2 = {
            "object": DatasetObject(name="cologne", category="bottle_of_cologne", model="lyipur"),
            "position": [-0.3, -0.8, 0.5],
            "orientation": [0, 0, 0, 1],
        }
        objects.append(obj_1)
        objects.append(obj_2)
    
        primitives = [StarterSemanticActionPrimitiveSet.GRASP, StarterSemanticActionPrimitiveSet.PLACE_ON_TOP]
        primitives_args = [(obj_2["object"],), (obj_1["object"],)]
    
>       primitive_tester(env, objects, primitives, primitives_args)

tests/test_primitives.py:145: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
tests/test_primitives.py:82: in primitive_tester
    execute_controller(controller.apply_ref(primitive, *args, attempts=1), env)
tests/test_primitives.py:69: in execute_controller
    for action in ctrl_gen:
omnigibson/action_primitives/starter_semantic_action_primitives.py:518: in apply_ref
    yield from ctrl(*args)
omnigibson/action_primitives/starter_semantic_action_primitives.py:743: in _grasp
    yield from self._navigate_if_needed(obj, pose_on_obj=grasp_pose)
omnigibson/action_primitives/starter_semantic_action_primitives.py:1663: in _navigate_if_needed
    if self._target_in_reach_of_robot(pose_on_obj):
omnigibson/action_primitives/starter_semantic_action_primitives.py:913: in _target_in_reach_of_robot
    return self._target_in_reach_of_robot_relative(relative_target_pose)
omnigibson/action_primitives/starter_semantic_action_primitives.py:925: in _target_in_reach_of_robot_relative
    return self._ik_solver_cartesian_to_joint_space(relative_target_pose) is not None
omnigibson/action_primitives/starter_semantic_action_primitives.py:965: in _ik_solver_cartesian_to_joint_space
    robot_description_path=self._manipulation_descriptor_path,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <omnigibson.action_primitives.starter_semantic_action_primitives.StarterSemanticActionPrimitives object at 0x7f0e32124130>

    @property
    def _manipulation_descriptor_path(self):
        """The appropriate manipulation descriptor for the current settings."""
        if isinstance(self.robot, Tiago) and m.TIAGO_TORSO_FIXED:
            assert self.arm == "left", "Fixed torso mode only supports left arm!"
            return self.robot.robot_arm_descriptor_yamls["left_fixed"]
    
        # Otherwise just return the default arm control idx
>       return self.robot.robot_arm_descriptor_yamls[self.arm]
E       AttributeError: 'Tiago' object has no attribute 'robot_arm_descriptor_yamls'

omnigibson/action_primitives/starter_semantic_action_primitives.py:950: AttributeError

Check failure on line 0 in 12302141302-tests-test_primitives/test_primitives.xml

See this annotation in the file changed.

@github-actions github-actions / Test Results

pytest ► tests.test_primitives.TestPrimitives ► test_place[Fetch] 

Failed test found in:
  12302141302-tests-test_primitives/test_primitives.xml
Error:
  self = <test_primitives.TestPrimitives object at 0x7f0e4f9a52d0>
Raw output 
self = <test_primitives.TestPrimitives object at 0x7f0e4f9a52d0>
robot = 'Fetch'

    def test_place(self, robot):
        categories = ["floors", "ceilings", "walls", "coffee_table"]
        env = setup_environment(categories, robot=robot)
    
        objects = []
        obj_1 = {
            "object": DatasetObject(name="table", category="breakfast_table", model="rjgmmy", scale=[0.3, 0.3, 0.3]),
            "position": [-0.7, 0.5, 0.2],
            "orientation": [0, 0, 0, 1],
        }
        obj_2 = {
            "object": DatasetObject(name="cologne", category="bottle_of_cologne", model="lyipur"),
            "position": [-0.3, -0.8, 0.5],
            "orientation": [0, 0, 0, 1],
        }
        objects.append(obj_1)
        objects.append(obj_2)
    
        primitives = [StarterSemanticActionPrimitiveSet.GRASP, StarterSemanticActionPrimitiveSet.PLACE_ON_TOP]
        primitives_args = [(obj_2["object"],), (obj_1["object"],)]
    
>       primitive_tester(env, objects, primitives, primitives_args)

tests/test_primitives.py:145: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
tests/test_primitives.py:82: in primitive_tester
    execute_controller(controller.apply_ref(primitive, *args, attempts=1), env)
tests/test_primitives.py:69: in execute_controller
    for action in ctrl_gen:
omnigibson/action_primitives/starter_semantic_action_primitives.py:518: in apply_ref
    yield from ctrl(*args)
omnigibson/action_primitives/starter_semantic_action_primitives.py:743: in _grasp
    yield from self._navigate_if_needed(obj, pose_on_obj=grasp_pose)
omnigibson/action_primitives/starter_semantic_action_primitives.py:1663: in _navigate_if_needed
    if self._target_in_reach_of_robot(pose_on_obj):
omnigibson/action_primitives/starter_semantic_action_primitives.py:913: in _target_in_reach_of_robot
    return self._target_in_reach_of_robot_relative(relative_target_pose)
omnigibson/action_primitives/starter_semantic_action_primitives.py:925: in _target_in_reach_of_robot_relative
    return self._ik_solver_cartesian_to_joint_space(relative_target_pose) is not None
omnigibson/action_primitives/starter_semantic_action_primitives.py:965: in _ik_solver_cartesian_to_joint_space
    robot_description_path=self._manipulation_descriptor_path,
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <omnigibson.action_primitives.starter_semantic_action_primitives.StarterSemanticActionPrimitives object at 0x7f0e06504ac0>

    @property
    def _manipulation_descriptor_path(self):
        """The appropriate manipulation descriptor for the current settings."""
        if isinstance(self.robot, Tiago) and m.TIAGO_TORSO_FIXED:
            assert self.arm == "left", "Fixed torso mode only supports left arm!"
            return self.robot.robot_arm_descriptor_yamls["left_fixed"]
    
        # Otherwise just return the default arm control idx
>       return self.robot.robot_arm_descriptor_yamls[self.arm]
E       AttributeError: 'Fetch' object has no attribute 'robot_arm_descriptor_yamls'

omnigibson/action_primitives/starter_semantic_action_primitives.py:950: AttributeError

Check failure on line 0 in 12302141302-tests-test_scene_graph/test_scene_graph.xml

See this annotation in the file changed.

@github-actions github-actions / Test Results

pytest ► tests.test_scene_graph ► test_scene_graph 

Failed test found in:
  12302141302-tests-test_scene_graph/test_scene_graph.xml
Error:
  def test_scene_graph():
Raw output 
def test_scene_graph():
    
        if og.sim is None:
            # Set global flags
            gm.ENABLE_OBJECT_STATES = True
        else:
            # Make sure sim is stopped
            og.sim.stop()
    
        def create_robot_config(name, position):
            return {
                "name": name,
                "type": "Fetch",
                "obs_modalities": "all",
                "position": position,
                "orientation": T.euler2quat(th.tensor([0, 0, -math.pi / 2], dtype=th.float32)),
                "controller_config": {
                    "arm_0": {
                        "name": "NullJointController",
                        "motor_type": "position",
                    },
                },
            }
    
        robot_names = ["fetch_1", "fetch_2", "fetch_3"]
        robot_positions = [[0, 0.8, 0], [1, 0.8, 0], [2, 0.8, 0]]
    
        config = {
            "scene": {
                "type": "Scene",
            },
            "robots": [create_robot_config(name, position) for name, position in zip(robot_names, robot_positions)],
            "objects": [
                {
                    "type": "DatasetObject",
                    "fit_avg_dim_volume": True,
                    "name": "breakfast_table",
                    "category": "breakfast_table",
                    "model": "skczfi",
                    "prim_type": PrimType.RIGID,
                    "position": [150, 150, 150],
                    "scale": None,
                    "bounding_box": None,
                    "abilities": None,
                    "visual_only": False,
                },
                {
                    "type": "DatasetObject",
                    "fit_avg_dim_volume": True,
                    "name": "bowl",
                    "category": "bowl",
                    "model": "ajzltc",
                    "prim_type": PrimType.RIGID,
                    "position": [150, 150, 150],
                    "scale": None,
                    "bounding_box": None,
                    "abilities": None,
                    "visual_only": False,
                },
            ],
        }
    
        env = og.Environment(configs=config)
    
        scene = og.sim.scenes[0]
    
        breakfast_table = scene.object_registry("name", "breakfast_table")
        bowl = scene.object_registry("name", "bowl")
        place_obj_on_floor_plane(breakfast_table)
        bowl.set_position_orientation(position=[0.0, -0.8, 0.1], orientation=[0, 0, 0, 1])
    
        # Test single robot scene graph
        scene_graph_builder_single = SceneGraphBuilder(
            robot_names=robot_names[:1], egocentric=False, full_obs=True, only_true=True, merge_parallel_edges=True
        )
        scene_graph_builder_single.start(scene)
        for _ in range(3):
            og.sim.step()
            scene_graph_builder_single.step(scene)
    
        assert isinstance(
>           visualize_scene_graph(
                scene, scene_graph_builder_single.get_scene_graph(), show_window=False, cartesian_positioning=True
            ),
            th.Tensor,
        )

tests/test_scene_graph.py:94: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

scene = <omnigibson.scenes.scene_base.Scene object at 0x7fbbe11ea920>
G = <networkx.classes.digraph.DiGraph object at 0x7fbb893de8f0>
show_window = False, cartesian_positioning = True

    def visualize_scene_graph(scene, G, show_window=True, cartesian_positioning=False):
        """
        Converts the graph into an image and shows it in a cv2 window if preferred.
        Note: Currently, this function only works when we merge parallel edges, i.e. the graph is a DiGraph.
    
        Args:
            show_window (bool): Whether a cv2 GUI window containing the visualization should be shown.
            realistic_positioning (bool): Whether nodes should be positioned based on their position in the scene (if True)
                or placed using a graphviz layout (neato) that makes it easier to read edges & find clusters.
        """
    
        nodes = list(G.nodes)
        all_robots = [robot for robot in nodes if isinstance(robot, BaseRobot)]
    
        def _draw_graph():
            node_labels = {obj: obj.category for obj in nodes}
    
            # get all objects in fov of robots
            objects_in_fov = set()
            for robot in all_robots:
                objects_in_fov.update(robot.states[object_states.ObjectsInFOVOfRobot].get_value())
            colors = [
                ("yellow" if obj.category == "agent" else ("green" if obj in objects_in_fov else "red")) for obj in nodes
            ]
            positions = (
                {obj: (-pose[1][-1], pose[0][-1]) for obj, pose in G.nodes.data("pose")}
                if cartesian_positioning
                else nx.nx_pydot.pydot_layout(G, prog="neato")
            )
            nx.drawing.draw_networkx(
                G,
                pos=positions,
                labels=node_labels,
                nodelist=nodes,
                node_color=colors,
                font_size=5,
                arrowsize=5,
                node_size=200,
            )
    
            edge_labels = {}
            for edge in G.edges:
                state_value_pairs = []
                if len(edge) == 3:
                    # When we don't merge parallel edges
                    raise ValueError("Visualization does not support parallel edges.")
                else:
                    # When we merge parallel edges
                    assert len(edge) == 2, "Invalid graph format for scene graph visualization."
                for state, value in G.edges[edge]["states"]:
                    state_value_pairs.append(state + "=" + str(value))
                edge_labels[edge] = ", ".join(state_value_pairs)
    
            nx.drawing.draw_networkx_edge_labels(G, pos=positions, edge_labels=edge_labels, font_size=4)
    
        # Prepare pyplot figure that's sized to match the robot video.
        robot = all_robots[0]  # If there are multiple robots, we only include the first one
>       (robot_camera_sensor,) = [
            s for s in robot.sensors.values() if isinstance(s, VisionSensor) and "rgb" in s.modalities
        ]
E       ValueError: too many values to unpack (expected 1)

omnigibson/scene_graphs/graph_builder.py:285: ValueError
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