Update

[ghstack-poisoned]

Author: vmoens

.github/unittest/linux_libs/scripts_isaaclab/isaac.sh

@@ -20,6 +20,8 @@ export TF_CPP_MIN_LOG_LEVEL=0
 export BATCHED_PIPE_TIMEOUT=60
 export TD_GET_DEFAULTS_TO_NONE=1
 export OMNI_KIT_ACCEPT_EULA=yes
+export PIP_DISABLE_PIP_VERSION_CHECK=1
+export PYTHONNOUSERSITE=1
 
 nvidia-smi
 
@@ -52,14 +54,31 @@ export LD_LIBRARY_PATH=${lib_dir}:${LD_LIBRARY_PATH:-}
 # Ensure libexpat is at the correct version BEFORE installing other packages
 conda install -c conda-forge expat -y
 
+# Force the loader to pick conda's libexpat over the system one
+if [ -f "${lib_dir}/libexpat.so.1" ]; then
+  export LD_PRELOAD="${lib_dir}/libexpat.so.1:${LD_PRELOAD:-}"
+elif [ -f "${lib_dir}/libexpat.so" ]; then
+  export LD_PRELOAD="${lib_dir}/libexpat.so:${LD_PRELOAD:-}"
+fi
+
+# Quick diagnostic to confirm which expat is resolved by pyexpat
+PYEXPAT_SO=$(python - <<'PY'
+import importlib.util
+spec = importlib.util.find_spec('pyexpat')
+print(spec.origin)
+PY
+)
+echo "* pyexpat module: ${PYEXPAT_SO}"
+ldd "${PYEXPAT_SO}" | grep -i expat || true
+
 # Reinstall Python to ensure it links against the correct expat
 conda install --force-reinstall python=3.10 -y
 
 # Pin pytorch to 2.5.1 for IsaacLab
 conda install pytorch==2.5.1 torchvision==0.20.1 pytorch-cuda=12.4 -c pytorch -c nvidia -y
 
-python -m pip install --upgrade pip
-python -m pip install 'isaacsim[all,extscache]==4.5.0' --extra-index-url https://pypi.nvidia.com
+python -m pip install --upgrade pip --disable-pip-version-check
+python -m pip install 'isaacsim[all,extscache]==4.5.0' --extra-index-url https://pypi.nvidia.com --disable-pip-version-check
 conda install conda-forge::"cmake>3.22" -y
 
 git clone https://github.com/isaac-sim/IsaacLab.git
@@ -70,21 +89,21 @@ cd ../
 # install tensordict
 if [[ "$RELEASE" == 0 ]]; then
   conda install "anaconda::cmake>=3.22" -y
-  python -m pip install "pybind11[global]"
-  python -m pip install git+https://github.com/pytorch/tensordict.git
+  python -m pip install "pybind11[global]" --disable-pip-version-check
+  python -m pip install git+https://github.com/pytorch/tensordict.git --disable-pip-version-check
 else
-  python -m pip install tensordict
+  python -m pip install tensordict --disable-pip-version-check
 fi
 
 # smoke test
 python -c "import tensordict"
 
 printf "* Installing torchrl\n"
-python -m pip install -e . --no-build-isolation
+python -m pip install -e . --no-build-isolation --disable-pip-version-check
 python -c "import torchrl"
 
 # Install pytest
-python -m pip install pytest pytest-cov pytest-mock pytest-instafail pytest-rerunfailures pytest-error-for-skips pytest-asyncio
+python -m pip install pytest pytest-cov pytest-mock pytest-instafail pytest-rerunfailures pytest-error-for-skips pytest-asyncio --disable-pip-version-check
 
 # Run tests
 python -m pytest test/test_libs.py -k isaac -s

test/test_libs.py

@@ -3464,7 +3464,9 @@ def test_dataset_build(self, task, split_trajs, from_env):
             task, split_trajs=split_trajs, from_env=from_env, batch_size=2
         )
         sample = data.sample()
-        env = GymWrapper(gym.make(task))
+        # D4RL environments are registered with gym, not gymnasium
+        with set_gym_backend("gym"):
+            env = GymWrapper(gym.make(task))
         rollout = env.rollout(2)
         for key in rollout.keys(True, True):
             if "truncated" in key:

torchrl/data/datasets/d4rl.py

@@ -267,16 +267,19 @@ def _get_dataset_direct_download(self, name, env_kwargs):
         return dataset
 
     def _get_dataset_direct(self, name, env_kwargs):
-        from torchrl.envs.libs.gym import GymWrapper
+        from torchrl.envs.libs.gym import GymWrapper, set_gym_backend
 
         type(self)._import_d4rl()
 
         if not self._has_d4rl:
             raise ImportError("Could not import d4rl") from self.D4RL_ERR
         import d4rl
-        import gym
 
-        env = GymWrapper(gym.make(name))
+        # D4RL environments are registered with gym, not gymnasium
+        # so we need to ensure we're using the gym backend
+        with set_gym_backend("gym"):
+            import gym
+            env = GymWrapper(gym.make(name))
         with tempfile.TemporaryDirectory() as tmpdir:
             os.environ["D4RL_DATASET_DIR"] = tmpdir
             dataset = d4rl.qlearning_dataset(env._env, **env_kwargs)
@@ -347,12 +350,14 @@ def _get_dataset_from_env(self, name, env_kwargs):
         if env_kwargs:
             raise RuntimeError("env_kwargs cannot be passed with using from_env=True")
         import d4rl  # noqa: F401
-        import gym
 
         # we do a local import to avoid circular import issues
-        from torchrl.envs.libs.gym import GymWrapper
+        from torchrl.envs.libs.gym import GymWrapper, set_gym_backend
 
-        with tempfile.TemporaryDirectory() as tmpdir:
+        # D4RL environments are registered with gym, not gymnasium
+        # so we need to ensure we're using the gym backend
+        with set_gym_backend("gym"), tempfile.TemporaryDirectory() as tmpdir:
+            import gym
             os.environ["D4RL_DATASET_DIR"] = tmpdir
             env = GymWrapper(gym.make(name))
             dataset = make_tensordict(