init

.github/unittest/linux_libs/scripts_habitat/run_test.sh

@@ -42,6 +42,9 @@ conda deactivate && conda activate ./env
 
 
 # this workflow only tests the libs
+mkdir data
+python -m habitat_sim.utils.datasets_download --uids rearrange_dataset_v1 rearrange_pick_dataset_v0 rearrange_task_assets --data-path ./data
+
 python -c "import habitat;import habitat.gym"
 python -c """from torchrl.envs.libs.habitat import HabitatEnv
 env = HabitatEnv('HabitatRenderPick-v0')

torchrl/envs/libs/habitat.py

@@ -9,7 +9,7 @@
 from torchrl._utils import _make_ordinal_device
 from torchrl.data.utils import DEVICE_TYPING
 from torchrl.envs.common import EnvBase
-from torchrl.envs.libs.gym import GymEnv, set_gym_backend
+from torchrl.envs.libs.gym import GymEnv, set_gym_backend, GymWrapper
 from torchrl.envs.utils import _classproperty
 
 _has_habitat = importlib.util.find_spec("habitat") is not None
@@ -106,6 +106,23 @@ def __init__(self, env_name, **kwargs):
         ]
         super().__init__(env_name=env_name, **kwargs)
 
+    @classmethod
+    def from_config(cls, cfg):
+        """Creates a HabitatEnv from the config.
+
+        Examples:
+            >>> config = habitat.get_config(
+            ...     "benchmark/nav/objectnav/objectnav_hssd-hab.yaml"
+            ... )
+            >>> env = HabitatEnv(config)
+
+        """
+        import habitat.gym
+
+        wrapper = cls.__new__(cls)
+        wrapper.__dict__.update(GymWrapper(habitat.gym.make_gym_from_config(cfg)).__dict__)
+        return wrapper
+
     @_classproperty
     def available_envs(cls):
         if not _has_habitat: