Update panda3d for python 3.10

.github/workflows/ci-python-version-test.yml

@@ -0,0 +1,30 @@
+name: SMARTS CI Python Version Tests
+
+on:
+  push:
+    branches:
+      - master
+
+env:
+  venv_dir: .venv
+
+jobs:
+  install_python:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.8', '3.9', '3.10', '3.11']
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Update requirements
+        run: |
+          cd $GITHUB_WORKSPACE
+          python${{ matrix.python-version }} -m venv ${{env.venv_dir}}
+          . ${{env.venv_dir}}/bin/activate
+          pip install --upgrade pip
+          pip install wheel==0.38.4
+          pip install .[camera_obs,rllib,sumo,test,torch,train]

CHANGELOG.md

@@ -11,8 +11,10 @@ Copy and pasting the git commit messages is __NOT__ enough.
 ## [Unreleased] - XXXX-XX-XX
 ### Added
 ### Changed
+- The following dependencies have been loosened: `numpy`, `opencv`, `torch`.
 ### Deprecated
 ### Fixed
+- The `smarts` package now works with `python3.10` and `python3.11`.
 ### Removed
 ### Security
 

examples/env/create_run_visualize.ipynb

@@ -1,6 +1,7 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "id": "wkR0YvENQni4"
@@ -22,7 +23,7 @@
    "outputs": [],
    "source": [
     "!git clone https://github.com/huawei-noah/SMARTS 2> /dev/null\n",
-    "!cd SMARTS && ls && git checkout develop && pip install .[camera_obs]"
+    "!cd SMARTS && ls && git checkout tucker/fix_for_python_3_10 && pip install .[camera_obs,gymnasium]"
    ]
   },
   {
@@ -37,12 +38,16 @@
    },
    "outputs": [],
    "source": [
+    "import os\n",
     "import sys\n",
+    "from pathlib import Path\n",
     "\n",
-    "sys.path.insert(0, \"/content/SMARTS/\")"
+    "sys.path.insert(0, Path(os.path.abspath(\"\")).parents[1])\n",
+    "print(Path(os.path.abspath(\"\")) / \"SMARTS\")"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "id": "s7UtcphinvNv"
@@ -59,13 +64,14 @@
    },
    "outputs": [],
    "source": [
-    "import gym\n",
+    "import gymnasium as gym\n",
     "\n",
     "from smarts.zoo import registry\n",
     "from smarts.env.gymnasium.wrappers.episode_logger import EpisodeLogger"
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {
     "id": "LFoG7Z-FobPP"
@@ -88,14 +94,13 @@
    "outputs": [],
    "source": [
     "from smarts.core.utils.episodes import episode_range\n",
-    "from smarts.env.wrappers.record_video import RecordVideo\n",
+    "from smarts.core.utils.import_utils import import_module_from_file\n",
     "\n",
-    "import examples.env.figure_eight_env\n",
-    "\n",
-    "env = gym.make(\"figure_eight-v0\")\n",
-    "env: gym.Env = RecordVideo(\n",
-    "    env, video_folder=\"videos\", video_length=40, step_trigger=lambda s: s % 100 == 0\n",
+    "import_module_from_file(\n",
+    "    \"examples.env.figure_eight_env\", Path(os.path.abspath(\"\")) / \"figure_eight_env.py\"\n",
     ")\n",
+    "\n",
+    "env = gym.make(\"figure_eight-v0\", disable_env_checker=True)\n",
     "env: gym.Env = EpisodeLogger(env)\n",
     "\n",
     "import zoo.policies.keep_lane_agent\n",
@@ -104,24 +109,13 @@
     "\n",
     "for episode in episode_range(max_steps=450):\n",
     "    observation = env.reset()\n",
-    "    reward, done, info = None, False, None\n",
-    "    while episode.continues(observation, reward, done, info):\n",
+    "    reward, terminated, truncated, info = None, False, False, None\n",
+    "    while episode.continues(observation, reward, terminated, truncated, info):\n",
     "        action = agent.act(observation)\n",
-    "        observation, reward, done, info = env.step(action)\n",
+    "        observation, reward, terminated, info = env.step(action)\n",
     "\n",
     "env.close()"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from smarts.env.wrappers.utils.rendering import show_notebook_videos\n",
-    "\n",
-    "show_notebook_videos()"
-   ]
   }
  ],
  "metadata": {
@@ -130,7 +124,7 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "Python 3.8.10 ('.venv': venv)",
+   "display_name": ".venv",
    "language": "python",
    "name": "python3"
   },
@@ -148,7 +142,7 @@
   },
   "vscode": {
    "interpreter": {
-    "hash": "94261e0756b8490ed1a668b85ed1da8c98261f1072b842b18d4e3da7517b644d"
+    "hash": "983a288b1deae516b5d1a3268f286490dc1a3bd215a042403a142fb3df5f8acd"
    }
   }
  },

examples/env/crv.py

@@ -0,0 +1,31 @@
+import os
+import sys
+from pathlib import Path
+
+import gymnasium as gym
+from gymnasium.wrappers.record_video import RecordVideo
+
+from smarts.core.utils.episodes import Episode, episode_range, episodes
+from smarts.env.gymnasium.wrappers.episode_logger import EpisodeLogger
+from smarts.zoo import registry
+
+SMARTS_DIR = Path(os.path.abspath(""))
+sys.path.insert(0, SMARTS_DIR)
+
+from examples.env import figure_eight_env
+
+env = gym.make("figure_eight-v0", disable_env_checker=True)
+env: gym.Env = EpisodeLogger(env)
+
+import zoo.policies.keep_lane_agent
+
+agent = registry.make_agent("zoo.policies:keep-lane-agent-v0")
+
+for episode in episode_range(max_steps=450):
+    observation, info = env.reset()
+    reward, terminated, truncated, info = None, False, False, None
+    while episode.continues(observation, reward, terminated, truncated, info):
+        action = agent.act(observation)
+        observation, reward, _, terminated, info = env.step(action)
+
+env.close()

examples/env/figure_eight_env.py

@@ -4,6 +4,8 @@
 
 from smarts.core.agent_interface import AgentInterface, AgentType
 from smarts.env.gymnasium.wrappers.single_agent import SingleAgent
+from smarts.env.utils.action_conversion import ActionOptions
+from smarts.env.utils.observation_conversion import ObservationOptions
 
 agent_interface = AgentInterface.from_type(
     AgentType.Laner,
@@ -27,8 +29,14 @@ def entry_point(*args, **kwargs):
         agent_interfaces={"agent-007": agent_interface},
         scenarios=[scenario],
         headless=True,
+        action_options=ActionOptions.unformatted,
+        observation_options=ObservationOptions.unformatted,
+        disable_env_checker=True,
     )
-    env.metadata["render.modes"] = set(env.metadata["render.modes"]) | {"rgb_array"}
+    env.unwrapped.render_mode = "rgb_array"
+    env.metadata["render_modes"] = set(env.metadata.get("render_modes", ())) | {
+        "rgb_array"
+    }
     return SingleAgent(env)
 
 

examples/tests/test_examples.py

@@ -43,7 +43,7 @@ def test_rllib_pg_example():
     from examples.rl.rllib import pg_example
 
     main = pg_example.main
-    with tempfile.TemporaryDirectory() as result_dir, tempfile.TemporaryDirectory() as model_dir:
+    with tempfile.TemporaryDirectory() as result_dir:
         main(
             scenarios=["./scenarios/sumo/loop"],
             envision=False,

setup.cfg

@@ -11,6 +11,7 @@ classifiers=
     Programming Language :: Python :: 3 :: Only
     Programming Language :: Python :: 3.8
     Programming Language :: Python :: 3.9
+    Programming Language :: Python :: 3.10
     License :: OSI Approved :: MIT License
 
 [options]
@@ -25,8 +26,7 @@ install_requires =
     setuptools>=41.0.0,!=50.0
     click>=7.1.2  # used in scl
     # numpy>=1.19.5 required for tf 2.4
-    # numpy<1.24 required for ray (see https://github.com/ray-project/ray/issues/31258)
-    numpy>=1.19.5,<1.24.0
+    numpy>=1.19.5
     psutil>=5.4.8
     shapely>=2.0.0
     tableprint>=0.9.1
@@ -35,8 +35,8 @@ install_requires =
     PyYAML>=3.13
     twisted>=21.7.0 # for scenario requirements.txt files
 
-    pybullet>=3,<4.0 # planned to be made optional
-    cloudpickle>=1.3.0,<=2.1.0 # planned for removal
+    pybullet>=3,<4.0 # planned to be made optional (For >3.9 this requires python3.<ver>-dev)
+    cloudpickle>=1.3.0 # planned for removal
 
 [options.packages.find]
 exclude =
@@ -52,7 +52,7 @@ argoverse =
     av2>=0.2.1
     Rtree>=0.9.7
 camera_obs = 
-    Panda3D==1.10.9
+    Panda3D>=1.10.13
     panda3d-gltf==0.13
 dev = 
     black[jupyter]==22.6.0
@@ -86,8 +86,8 @@ opendrive =
     opendrive2lanelet>=1.2.1
     Rtree>=0.9.7
 rllib = 
-    opencv-python==4.1.2.30
-    opencv-python-headless==4.1.2.30
+    opencv-python>=4.1.2.30,<5.0
+    opencv-python-headless>=4.1.2.30,<5.0
     ray[rllib]~=2.5.0
     tensorflow-probability
 ray = 
@@ -96,7 +96,7 @@ ros =
     catkin_pkg
     rospkg
 sumo =
-    eclipse-sumo>=1.12.0  # sumo
+    eclipse-sumo>=1.12.0
     Rtree>=0.9.7 # technically optional, but used by sumo internally for performance (see `getNeighboringLanes()`)
 test = # The following are for testing
     pytest>=6.2.5
@@ -109,8 +109,8 @@ test_notebook =
     jupyter-client>=7.1.2
     pytest-notebook>=0.7.0
 torch = 
-    torch==1.4.0
-    torchvision==0.5.0
+    torch>=1.4.0
+    torchvision>=0.5.0
 train = 
     tensorflow>=2.4.0
 visdom =
@@ -130,8 +130,8 @@ all =
     %(gif_recorder)s
     %(gymnasium)s
     %(opendrive)s
+    %(ray)s
     %(rllib)s
-    # %(ray)s # incompatible with [rllib] for now
     %(ros)s
     %(sumo)s
     %(test)s

smarts/core/utils/episodes.py

@@ -200,16 +200,16 @@ class Episode:
     def __init__(self, episodes: Episodes):
         self._episodes = episodes
 
-    def continues(self, observation, reward, done, info) -> bool:
+    def continues(self, observation, reward, terminated, truncated, info) -> bool:
         """Determine if the current episode can continue."""
 
         self._episodes.current_step += 1
 
         if self._episodes.current_step >= self._episodes.max_steps:
             return False
-        if isinstance(done, dict):
-            return not done.get("__all__", all(done.values()))
-        return not done
+        if isinstance(terminated, dict):
+            return not terminated.get("__all__", all(terminated.values()))
+        return not terminated
 
 
 def episode_range(max_steps):

smarts/engine.ini

@@ -1,6 +1,6 @@
 [benchmark]
 [core]
-debug = false
+debug = False
 observation_workers = 0
 reset_retries = 0
 [controllers]

smarts/env/gymnasium/hiway_env_v1.py

@@ -428,7 +428,10 @@ def render(
         Note:
             Make sure that your class's :attr:`metadata` ``"render_modes"`` key includes the list of supported modes.
         """
-        if "rgb_array" in self.metadata["render_modes"]:
+        if (
+            "rgb_array" in self.metadata["render_modes"]
+            or self.render_mode == "rgb_array"
+        ):
             if self._env_renderer is None:
                 from smarts.env.utils.record import AgentCameraRGBRender
 

smarts/env/gymnasium/wrappers/metric/utils.py

@@ -117,7 +117,7 @@ def nearest_waypoint(
     Returns:
         Tuple[Tuple[int, int], Optional[int]] : `matrix` index of shape (a,b) and scalar `point` index.
     """
-    cur_point_index = ((np.int(1e10), np.int(1e10)), None)
+    cur_point_index = ((np.int32(1e10), np.int32(1e10)), None)
 
     if points.shape == (0,):
         return cur_point_index