Add has_attr for VecEnv (#2077)

* Add `has_attr` for `VecEnv`

* Add special case for gymnasium<1.0

* Update changelog.rst

* Update black version

Author: araffin

docs/misc/changelog.rst

@@ -3,24 +3,20 @@
 Changelog
 ==========
 
-Release 2.5.0 (2025-01-27)
+Release 2.6.0a0 (WIP)
 --------------------------
 
-**New algorithm: SimBa in SBX, NumPy 2.0 support**
-
 
 Breaking Changes:
 ^^^^^^^^^^^^^^^^^
-- Increased minimum required version of PyTorch to 2.3.0
-- Removed support for Python 3.8
 
 New Features:
 ^^^^^^^^^^^^^
-- Added support for NumPy v2.0: ``VecNormalize`` now cast normalized rewards to float32, updated bit flipping env to avoid overflow issues too
-- Added official support for Python 3.12
+- Added ``has_attr`` method for ``VecEnv`` to check if an attribute exists
 
 Bug Fixes:
 ^^^^^^^^^^
+- `SubProcVecEnv` will now exit gracefully (without big traceback) when using `KeyboardInterrupt`
 
 `SB3-Contrib`_
 ^^^^^^^^^^^^^^
@@ -30,12 +26,39 @@ Bug Fixes:
 
 `SBX`_ (SB3 + Jax)
 ^^^^^^^^^^^^^^^^^^
-- Added SimBa Policy: Simplicity Bias for Scaling Up Parameters in DRL
-- Added support for parameter resets
 
 Deprecations:
 ^^^^^^^^^^^^^
 
+Others:
+^^^^^^^
+- Updated black from v24 to v25
+
+Documentation:
+^^^^^^^^^^^^^^
+
+
+Release 2.5.0 (2025-01-27)
+--------------------------
+
+**New algorithm: SimBa in SBX, NumPy 2.0 support**
+
+
+Breaking Changes:
+^^^^^^^^^^^^^^^^^
+- Increased minimum required version of PyTorch to 2.3.0
+- Removed support for Python 3.8
+
+New Features:
+^^^^^^^^^^^^^
+- Added support for NumPy v2.0: ``VecNormalize`` now cast normalized rewards to float32, updated bit flipping env to avoid overflow issues too
+- Added official support for Python 3.12
+
+`SBX`_ (SB3 + Jax)
+^^^^^^^^^^^^^^^^^^
+- Added SimBa Policy: Simplicity Bias for Scaling Up Parameters in DRL
+- Added support for parameter resets
+
 Others:
 ^^^^^^^
 - Updated Dockerfile

setup.py

@@ -98,7 +98,7 @@
             # Lint code and sort imports (flake8 and isort replacement)
             "ruff>=0.3.1",
             # Reformat
-            "black>=24.2.0,<25",
+            "black>=25.1.0,<26",
         ],
         "docs": [
             "sphinx>=5,<9",

stable_baselines3/common/vec_env/base_vec_env.py

@@ -147,6 +147,21 @@ def close(self) -> None:
         """
         raise NotImplementedError()
 
+    def has_attr(self, attr_name: str) -> bool:
+        """
+        Check if an attribute exists for a vectorized environment.
+
+        :param attr_name: The name of the attribute to check
+        :return: True if 'attr_name' exists in all environments
+        """
+        # Default implementation, will not work with things that cannot be pickled:
+        # https://github.com/Stable-Baselines-Team/stable-baselines3-contrib/issues/49
+        try:
+            self.get_attr(attr_name)
+            return True
+        except AttributeError:
+            return False
+
     @abstractmethod
     def get_attr(self, attr_name: str, indices: VecEnvIndices = None) -> list[Any]:
         """
@@ -392,6 +407,9 @@ def render(self, mode: Optional[str] = None) -> Optional[np.ndarray]:
     def get_images(self) -> Sequence[Optional[np.ndarray]]:
         return self.venv.get_images()
 
+    def has_attr(self, attr_name: str) -> bool:
+        return self.venv.has_attr(attr_name)
+
     def get_attr(self, attr_name: str, indices: VecEnvIndices = None) -> list[Any]:
         return self.venv.get_attr(attr_name, indices)
 

stable_baselines3/common/vec_env/subproc_vec_env.py

@@ -17,7 +17,7 @@
 from stable_baselines3.common.vec_env.patch_gym import _patch_env
 
 
-def _worker(
+def _worker(  # noqa: C901
     remote: mp.connection.Connection,
     parent_remote: mp.connection.Connection,
     env_fn_wrapper: CloudpickleWrapper,
@@ -58,6 +58,12 @@ def _worker(
                 remote.send(method(*data[1], **data[2]))
             elif cmd == "get_attr":
                 remote.send(env.get_wrapper_attr(data))
+            elif cmd == "has_attr":
+                try:
+                    env.get_wrapper_attr(data)
+                    remote.send(True)
+                except AttributeError:
+                    remote.send(False)
             elif cmd == "set_attr":
                 remote.send(setattr(env, data[0], data[1]))  # type: ignore[func-returns-value]
             elif cmd == "is_wrapped":
@@ -66,6 +72,8 @@ def _worker(
                 raise NotImplementedError(f"`{cmd}` is not implemented in the worker")
         except EOFError:
             break
+        except KeyboardInterrupt:
+            break
 
 
 class SubprocVecEnv(VecEnv):
@@ -165,6 +173,13 @@ def get_images(self) -> Sequence[Optional[np.ndarray]]:
         outputs = [pipe.recv() for pipe in self.remotes]
         return outputs
 
+    def has_attr(self, attr_name: str) -> bool:
+        """Check if an attribute exists for a vectorized environment. (see base class)."""
+        target_remotes = self._get_target_remotes(indices=None)
+        for remote in target_remotes:
+            remote.send(("has_attr", attr_name))
+        return all([remote.recv() for remote in target_remotes])
+
     def get_attr(self, attr_name: str, indices: VecEnvIndices = None) -> list[Any]:
         """Return attribute from vectorized environment (see base class)."""
         target_remotes = self._get_target_remotes(indices)

stable_baselines3/version.txt

@@ -1 +1 @@
-2.5.0
+2.6.0a0

tests/test_vec_envs.py

@@ -123,12 +123,30 @@ def make_env():
     # we need a X server to test the "human" mode (uses OpenCV)
     # vec_env.render(mode="human")
 
+    # Set a new attribute, on the last wrapper and on the env
+    assert not vec_env.has_attr("dummy")
+    # Set value for the last wrapper only
+    vec_env.set_attr("dummy", 12)
+    assert vec_env.get_attr("dummy") == [12] * N_ENVS
+    if vec_env_class == DummyVecEnv:
+        assert vec_env.envs[0].dummy == 12
+
+    assert not vec_env.has_attr("dummy2")
+    # Set the value on the original env
+    # `set_wrapper_attr` doesn't exist before v1.0
+    if gym.__version__ > "1":
+        vec_env.env_method("set_wrapper_attr", "dummy2", 2)
+        assert vec_env.get_attr("dummy2") == [2] * N_ENVS
+        if vec_env_class == DummyVecEnv:
+            assert vec_env.envs[0].unwrapped.dummy2 == 2
+
     env_method_results = vec_env.env_method("custom_method", 1, indices=None, dim_1=2)
     setattr_results = []
     # Set current_step to an arbitrary value
     for env_idx in range(N_ENVS):
         setattr_results.append(vec_env.set_attr("current_step", env_idx, indices=env_idx))
     # Retrieve the value for each environment
+    assert vec_env.has_attr("current_step")
     getattr_results = vec_env.get_attr("current_step")
 
     assert len(env_method_results) == N_ENVS