Fixes environment closing and tests for task implementations (#231)

# Description

This MR fixes the test scripts inside the `omni.isaac.orbit_tasks`
extension. The tests were previously crashing since they weren't updated
to latest changes in the core framework.

Additionally, the tests helped in realizing that the environment did not
close properly, i.e. some managers do not get destroyed properly and
still hold references to certain scene entities. The MR now explicitly
calls all `del` operators over all the managers to delete them in the
right-order.

## Type of change

- Bug fix (non-breaking change which fixes an issue)

## Checklist

- [x] I have run the [`pre-commit` checks](https://pre-commit.com/) with
`./orbit.sh --format`
- [ ] I have made corresponding changes to the documentation
- [x] My changes generate no new warnings
- [x] I have added tests that prove my fix is effective or that my
feature works
- [x] I have updated the changelog and the corresponding version in the
extension's `config/extension.toml` file
- [x] I have added my name to the `CONTRIBUTORS.md` or my name already
exists there

---------
Signed-off-by: Mayank Mittal <12863862+Mayankm96@users.noreply.github.com>

source/extensions/omni.isaac.orbit/config/extension.toml

 [package]
 
 # Note: Semantic Versioning is used: https://semver.org/
-version = "0.9.35"
+version = "0.9.36"
 
 # Description
 title = "ORBIT framework for Robot Learning"

source/extensions/omni.isaac.orbit/docs/CHANGELOG.rst

 Changelog
 ---------
 
+0.9.36 (2023-11-03)
+~~~~~~~~~~~~~~~~~~~
+
+Fixed
+^^^^^
+
+* Added explicit deleting of different managers in the :class:`omni.isaac.orbit.envs.BaseEnv` and
+  :class:`omni.isaac.orbit.envs.RLTaskEnv` classes. This is required since deleting the managers
+  is order-sensitive (many managers need to be deleted before the scene is deleted).
+
+
 0.9.35 (2023-11-02)
 ~~~~~~~~~~~~~~~~~~~
 

source/extensions/omni.isaac.orbit/omni/isaac/orbit/envs/base_env.py

@@ -76,7 +76,9 @@ class BaseEnv:
         else:
             raise RuntimeError("Simulation context already exists. Cannot create a new one.")
         # set camera view for "/OmniverseKit_Persp" camera
-        self.sim.set_camera_view(eye=self.cfg.viewer.eye, target=self.cfg.viewer.lookat)
+        # viewport is not available in other rendering modes so the function will throw a warning
+        if self.sim.render_mode >= self.sim.RenderMode.PARTIAL_RENDERING:
+            self.sim.set_camera_view(eye=self.cfg.viewer.eye, target=self.cfg.viewer.lookat)
 
         # print useful information
         print("[INFO]: Base environment:")
@@ -187,6 +189,11 @@ class BaseEnv:
     def close(self):
         """Cleanup for the environment."""
         if not self._is_closed:
+            # destructor is order-sensitive
+            del self.action_manager
+            del self.observation_manager
+            del self.randomization_manager
+            del self.scene
             # clear callbacks and instance
             self.sim.clear_all_callbacks()
             self.sim.clear_instance()

source/extensions/omni.isaac.orbit/omni/isaac/orbit/envs/rl_task_env.py

@@ -285,6 +285,16 @@ class RLTaskEnv(BaseEnv, gym.Env):
                 f"Render mode '{mode}' is not supported. Please use: {self.metadata['render.modes']}."
             )
 
+    def close(self):
+        if not self._is_closed:
+            # destructor is order-sensitive
+            del self.command_manager
+            del self.reward_manager
+            del self.termination_manager
+            del self.curriculum_manager
+            # call the parent class to close the environment
+            super().close()
+
     """
     Implementation specifics.
     """

source/extensions/omni.isaac.orbit/omni/isaac/orbit/terrains/height_field/hf_terrains.py

@@ -8,7 +8,7 @@
 from __future__ import annotations
 
 import numpy as np
-from scipy.interpolate import interpolate
+import scipy.interpolate as interpolate
 from typing import TYPE_CHECKING
 
 from .utils import height_field_to_mesh
@@ -69,7 +69,7 @@ def random_uniform_terrain(difficulty: float, cfg: hf_terrains_cfg.HfRandomUnifo
     # create interpolation function for the sampled heights
     x = np.linspace(0, cfg.size[0] * cfg.horizontal_scale, width_downsampled)
     y = np.linspace(0, cfg.size[1] * cfg.horizontal_scale, length_downsampled)
-    func = interpolate.interp2d(y, x, height_field_downsampled, kind="linear")
+    func = interpolate.RectBivariateSpline(y, x, height_field_downsampled)
 
     # interpolate the sampled heights to obtain the height field
     x_upsampled = np.linspace(0, cfg.size[0] * cfg.horizontal_scale, width_pixels)

source/extensions/omni.isaac.orbit/omni/isaac/orbit/terrains/terrain_generator.py

@@ -150,7 +150,7 @@ class TerrainGenerator:
         for index in range(self.cfg.num_cols):
             sub_index = np.min(np.where(index / self.cfg.num_cols + 0.001 < np.cumsum(proportions))[0])
             sub_indices.append(sub_index)
-        sub_indices = np.array(sub_indices, dtype=np.int)
+        sub_indices = np.array(sub_indices, dtype=np.int32)
         # create a list of all terrain configs
         sub_terrains_cfgs = list(self.cfg.sub_terrains.values())
 

source/extensions/omni.isaac.orbit/test/deps/isaacsim/check_app.py

+# Copyright (c) 2022-2023, The ORBIT Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+"""
+This script shows the issue with launching Isaac Sim application in headless mode.
+
+On launching the application in headless mode, the application does not exit gracefully.
+There are multiple warnings and errors that are printed on the console.
+
+```
+_isaac_sim/python.sh source/extensions/omni.isaac.orbit/test/deps/isaacsim/check_app.py
+```
+
+Output:
+
+```
+[10.948s] Simulation App Startup Complete
+[11.471s] Simulation App Shutting Down
+...... [Warning] [carb] [Plugin: omni.spectree.delegate.plugin] Module /media/vulcan/packman-repo/chk/kit-sdk/105.1+release.129498.98d86eae.tc.linux-x86_64.release/exts/omni.usd_resolver/bin/libomni.spectree.delegate.plugin.so remained loaded after unload request
+...... [Warning] [omni.core.ITypeFactory] Module /media/vulcan/packman-repo/chk/kit-sdk/105.1+release.129498.98d86eae.tc.linux-x86_64.release/exts/omni.graph.action/bin/libomni.graph.action.plugin.so remained loaded after unload request.
+...... [Warning] [omni.core.ITypeFactory] Module /media/vulcan/packman-repo/chk/kit-sdk/105.1+release.129498.98d86eae.tc.linux-x86_64.release/exts/omni.activity.core/bin/libomni.activity.core.plugin.so remained loaded after unload request.
+```
+
+"""
+
+from __future__ import annotations
+
+from omni.isaac.kit import SimulationApp
+
+if __name__ == "__main__":
+    app = SimulationApp({"headless": True})
+    app.close()

source/extensions/omni.isaac.orbit/test/isaacsim/check_camera.py → source/extensions/omni.isaac.orbit/test/deps/isaacsim/check_camera.py

@@ -11,9 +11,9 @@ and have the same image as the previous episode for the first few steps.
 
 ```
 # run with cube
-_isaac_sim/python.sh source/extensions/omni.isaac.orbit/test/isaacsim/check_camera.py --scenario cube
+_isaac_sim/python.sh source/extensions/omni.isaac.orbit/test/deps/isaacsim/check_camera.py --scenario cube
 # run with anymal
-_isaac_sim/python.sh source/extensions/omni.isaac.orbit/test/isaacsim/check_camera.py --scenario anymal
+_isaac_sim/python.sh source/extensions/omni.isaac.orbit/test/deps/isaacsim/check_camera.py --scenario anymal
 ```
 """
 

source/extensions/omni.isaac.orbit/test/isaacsim/check_rep_texture_randomizer.py → source/extensions/omni.isaac.orbit/test/deps/isaacsim/check_rep_texture_randomizer.py

@@ -15,7 +15,7 @@ Usage:
 
 .. code-block:: bash
 
-    ./orbit.sh -p source/extensions/omni.isaac.orbit/test/isaacsim/check_rep_texture_randomizer.py
+    ./orbit.sh -p source/extensions/omni.isaac.orbit/test/deps/isaacsim/check_rep_texture_randomizer.py
 
 """
 

source/extensions/omni.isaac.orbit/test/deps/test_scipy.py

+# Copyright (c) 2022-2023, The ORBIT Project Developers.
+# All rights reserved.
+#
+# SPDX-License-Identifier: BSD-3-Clause
+
+from __future__ import annotations
+
+# isort: off
+import warnings
+
+warnings.filterwarnings("ignore", category=DeprecationWarning)
+# isort: on
+
+import numpy as np
+import scipy.interpolate as interpolate
+import unittest
+
+
+class TestScipyOperations(unittest.TestCase):
+    """Tests for assuring scipy related operations used in Orbit."""
+
+    def test_interpolation(self):
+        """Test scipy interpolation 2D method."""
+        # parameters
+        size = (10.0, 10.0)
+        horizontal_scale = 0.1
+        vertical_scale = 0.005
+        downsampled_scale = 0.2
+        noise_range = (-0.02, 0.1)
+        noise_step = 0.02
+        # switch parameters to discrete units
+        # -- horizontal scale
+        width_pixels = int(size[0] / horizontal_scale)
+        length_pixels = int(size[1] / horizontal_scale)
+        # -- downsampled scale
+        width_downsampled = int(size[0] / downsampled_scale)
+        length_downsampled = int(size[1] / downsampled_scale)
+        # -- height
+        height_min = int(noise_range[0] / vertical_scale)
+        height_max = int(noise_range[1] / vertical_scale)
+        height_step = int(noise_step / vertical_scale)
+
+        # create range of heights possible
+        height_range = np.arange(height_min, height_max + height_step, height_step)
+        # sample heights randomly from the range along a grid
+        height_field_downsampled = np.random.choice(height_range, size=(width_downsampled, length_downsampled))
+        # create interpolation function for the sampled heights
+        x = np.linspace(0, size[0] * horizontal_scale, width_downsampled)
+        y = np.linspace(0, size[1] * horizontal_scale, length_downsampled)
+
+        # interpolate the sampled heights to obtain the height field
+        x_upsampled = np.linspace(0, size[0] * horizontal_scale, width_pixels)
+        y_upsampled = np.linspace(0, size[1] * horizontal_scale, length_pixels)
+        # -- method 1: interp2d (this will be deprecated in the future 1.13 release)
+        func_interp2d = interpolate.interp2d(y, x, height_field_downsampled, kind="cubic")
+        z_upsampled_interp2d = func_interp2d(y_upsampled, x_upsampled)
+        # -- method 2: RectBivariateSpline (alternate to interp2d)
+        func_RectBiVariate = interpolate.RectBivariateSpline(y, x, height_field_downsampled)
+        z_upsampled_RectBivariant = func_RectBiVariate(y_upsampled, x_upsampled)
+        # -- method 3: RegularGridInterpolator (recommended from scipy but slow!)
+        # Ref: https://github.com/scipy/scipy/issues/18010
+        func_RegularGridInterpolator = interpolate.RegularGridInterpolator(
+            (y, x), height_field_downsampled, method="cubic"
+        )
+        yy_upsampled, xx_upsampled = np.meshgrid(y_upsampled, x_upsampled, indexing="ij", sparse=True)
+        z_upsampled_RegularGridInterpolator = func_RegularGridInterpolator((yy_upsampled, xx_upsampled))
+
+        # check if the interpolated height field is the same as the sampled height field
+        np.testing.assert_allclose(z_upsampled_interp2d, z_upsampled_RectBivariant, atol=1e-14)
+        np.testing.assert_allclose(z_upsampled_RectBivariant, z_upsampled_RegularGridInterpolator, atol=1e-14)
+        np.testing.assert_allclose(z_upsampled_RegularGridInterpolator, z_upsampled_interp2d, atol=1e-14)
+
+
+if __name__ == "__main__":
+    unittest.main()

source/extensions/omni.isaac.orbit_tasks/test/test_data_collector.py

@@ -18,10 +18,10 @@ class TestRobomimicDataCollector(unittest.TestCase):
     def test_basic_flushing(self):
         """Adds random data into the collector and checks saving of the data."""
         # name of the environment (needed by robomimic)
-        task_name = "Isaac-Franka-Lift-v0"
+        task_name = "My-Task-v0"
         # specify directory for logging experiments
         test_dir = os.path.dirname(os.path.abspath(__file__))
-        log_dir = os.path.join(test_dir, "logs", "demos")
+        log_dir = os.path.join(test_dir, "output", "demos")
         # name of the file to save data
         filename = "hdf_dataset.hdf5"
         # number of episodes to collect

source/extensions/omni.isaac.orbit_tasks/test/test_environments.py

@@ -3,18 +3,18 @@
 #
 # SPDX-License-Identifier: BSD-3-Clause
 
-"""Launch Isaac Sim Simulator first."""
-
 from __future__ import annotations
 
+"""Launch Isaac Sim Simulator first."""
+
 import os
 
-from omni.isaac.kit import SimulationApp
+from omni.isaac.orbit.app import AppLauncher
 
 # launch the simulator
 app_experience = f"{os.environ['EXP_PATH']}/omni.isaac.sim.python.gym.headless.kit"
-config = {"headless": True}
-simulation_app = SimulationApp(config, experience=app_experience)
+app_launcher = AppLauncher(headless=True, experience=app_experience)
+simulation_app = app_launcher.app
 
 
 """Rest everything follows."""
@@ -23,10 +23,14 @@ simulation_app = SimulationApp(config, experience=app_experience)
 import gym
 import gym.envs
 import torch
+import traceback
 import unittest
 
+import carb
 import omni.usd
 
+from omni.isaac.orbit.envs import RLTaskEnv, RLTaskEnvCfg
+
 import omni.isaac.orbit_tasks  # noqa: F401
 from omni.isaac.orbit_tasks.utils.parse_cfg import parse_env_cfg
 
@@ -35,34 +39,35 @@ class TestEnvironments(unittest.TestCase):
     """Test cases for all registered environments."""
 
     @classmethod
-    def tearDownClass(cls):
-        """Closes simulator after running all test fixtures."""
-        simulation_app.close()
-
-    def setUp(self) -> None:
-        self.num_envs = 512
-        self.headless = simulation_app.config["headless"]
+    def setUpClass(cls):
         # acquire all Isaac environments names
-        self.registered_tasks = list()
+        cls.registered_tasks = list()
         for task_spec in gym.envs.registry.all():
             if "Isaac" in task_spec.id:
-                self.registered_tasks.append(task_spec.id)
+                cls.registered_tasks.append(task_spec.id)
         # sort environments by name
-        self.registered_tasks.sort()
+        cls.registered_tasks.sort()
         # print all existing task names
-        print(">>> All registered environments:", self.registered_tasks)
+        print(">>> All registered environments:", cls.registered_tasks)
+
+    def setUp(self) -> None:
+        # common parameters
+        self.num_envs = 512
+        self.use_gpu = True
 
     def test_random_actions(self):
         """Run random actions and check environments return valid signals."""
-
         for task_name in self.registered_tasks:
             print(f">>> Running test for environment: {task_name}")
             # create a new stage
             omni.usd.get_context().new_stage()
             # parse configuration
-            env_cfg = parse_env_cfg(task_name, use_gpu=True, num_envs=self.num_envs)
+            env_cfg: RLTaskEnvCfg = parse_env_cfg(task_name, use_gpu=self.use_gpu, num_envs=self.num_envs)
+            # note: we don't want to shutdown the app on stop during the tests since we reload the stage
+            env_cfg.sim.shutdown_app_on_stop = False
+
             # create environment
-            env = gym.make(task_name, cfg=env_cfg)
+            env: RLTaskEnv = gym.make(task_name, cfg=env_cfg)
 
             # reset environment
             obs = env.reset()
@@ -74,12 +79,10 @@ class TestEnvironments(unittest.TestCase):
                 # sample actions from -1 to 1
                 actions = 2 * torch.rand((env.num_envs, env.action_space.shape[0]), device=env.device) - 1
                 # apply actions
-                obs, rew, dones, info = env.step(actions)
+                transition = env.step(actions)
                 # check signals
-                self.assertTrue(self._check_valid_tensor(obs))
-                self.assertTrue(self._check_valid_tensor(rew))
-                self.assertTrue(self._check_valid_tensor(dones))
-                self.assertTrue(self._check_valid_tensor(info))
+                for data in transition:
+                    self.assertTrue(self._check_valid_tensor(data), msg=f"Invalid data: {data}")
 
             # close the environment
             print(f">>> Closing environment: {task_name}")
@@ -106,7 +109,7 @@ class TestEnvironments(unittest.TestCase):
             for value in data.values():
                 if isinstance(value, dict):
                     return TestEnvironments._check_valid_tensor(value)
-                else:
+                elif isinstance(value, torch.Tensor):
                     valid_tensor = valid_tensor and not torch.any(torch.isnan(value))
             return valid_tensor
         else:
@@ -114,4 +117,12 @@ class TestEnvironments(unittest.TestCase):
 
 
 if __name__ == "__main__":
-    unittest.main()
+    try:
+        unittest.main()
+    except Exception as err:
+        carb.log_error(err)
+        carb.log_error(traceback.format_exc())
+        raise
+    finally:
+        # close sim app
+        simulation_app.close()

source/extensions/omni.isaac.orbit_tasks/test/test_record_video.py

@@ -9,12 +9,12 @@ from __future__ import annotations
 
 import os
 
-from omni.isaac.kit import SimulationApp
+from omni.isaac.orbit.app import AppLauncher
 
 # launch the simulator
-app_experience = f"{os.environ['EXP_PATH']}/omni.isaac.sim.python.gym.headless.render.kit"
-config = {"headless": True}
-simulation_app = SimulationApp(config, experience=app_experience)
+app_experience = f"{os.environ['EXP_PATH']}/omni.isaac.sim.python.gym.headless.kit"
+app_launcher = AppLauncher(headless=True, offscreen_render=True, experience=app_experience)
+simulation_app = app_launcher.app
 
 """Rest everything follows."""
 
@@ -22,8 +22,14 @@ simulation_app = SimulationApp(config, experience=app_experience)
 import gym
 import os
 import torch
+import traceback
 import unittest
 
+import carb
+import omni.usd
+
+from omni.isaac.orbit.envs import RLTaskEnv, RLTaskEnvCfg
+
 import omni.isaac.contrib_tasks  # noqa: F401
 import omni.isaac.orbit_tasks  # noqa: F401
 from omni.isaac.orbit_tasks.utils import parse_env_cfg
@@ -33,41 +39,41 @@ class TestRecordVideoWrapper(unittest.TestCase):
     """Test recording videos using the RecordVideo wrapper."""
 
     @classmethod
-    def tearDownClass(cls):
-        """Closes simulator after running all test fixtures."""
-        simulation_app.close()
+    def setUpClass(cls):
+        # acquire all Isaac environments names
+        cls.registered_tasks = list()
+        for task_spec in gym.envs.registry.all():
+            if "Isaac" in task_spec.id:
+                cls.registered_tasks.append(task_spec.id)
+        # sort environments by name
+        cls.registered_tasks.sort()
+        # print all existing task names
+        print(">>> All registered environments:", cls.registered_tasks)
+        # directory to save videos
+        cls.videos_dir = os.path.join(os.path.dirname(__file__), "output", "videos")
 
     def setUp(self) -> None:
         # common parameters
         self.num_envs = 64
         self.use_gpu = True
-        self.headless = simulation_app.config["headless"]
-        # directory to save videos
-        self.videos_dir = os.path.join(os.path.dirname(__file__), "videos")
+        # video parameters
         self.step_trigger = lambda step: step % 225 == 0
         self.video_length = 200
-        # acquire all Isaac environments names
-        self.registered_tasks = list()
-        for task_spec in gym.envs.registry.all():
-            if "Isaac" in task_spec.id:
-                self.registered_tasks.append(task_spec.id)
-        # sort environments by name
-        self.registered_tasks.sort()
-        # print all existing task names
-        print(">>> All registered environments:", self.registered_tasks)
 
     def test_record_video(self):
         """Run random actions agent with recording of videos."""
-        import omni.usd
-
         for task_name in self.registered_tasks:
             print(f">>> Running test for environment: {task_name}")
             # create a new stage
             omni.usd.get_context().new_stage()
+
             # parse configuration
-            env_cfg = parse_env_cfg(task_name, use_gpu=self.use_gpu, num_envs=self.num_envs)
+            env_cfg: RLTaskEnvCfg = parse_env_cfg(task_name, use_gpu=self.use_gpu, num_envs=self.num_envs)
+            # note: we don't want to shutdown the app on stop during the tests since we reload the stage
+            env_cfg.sim.shutdown_app_on_stop = False
+
             # create environment
-            env = gym.make(task_name, cfg=env_cfg)
+            env: RLTaskEnv = gym.make(task_name, cfg=env_cfg)
 
             # directory to save videos
             videos_dir = os.path.join(self.videos_dir, task_name)
@@ -83,16 +89,21 @@ class TestRecordVideoWrapper(unittest.TestCase):
                 # compute zero actions
                 actions = 2 * torch.rand((env.num_envs, env.action_space.shape[0]), device=env.device) - 1
                 # apply actions
-                _, _, _, _ = env.step(actions)
+                _ = env.step(actions)
                 # render environment
                 env.render(mode="human")
-                # check if simulator is stopped
-                if env.unwrapped.sim.is_stopped():
-                    break
 
             # close the simulator
             env.close()
 
 
 if __name__ == "__main__":
-    unittest.main()
+    try:
+        unittest.main()
+    except Exception as err:
+        carb.log_error(err)
+        carb.log_error(traceback.format_exc())
+        raise
+    finally:
+        # close sim app
+        simulation_app.close()