Add check for common mistake when mixing Gym/VecEnv API (#1696)

docs/misc/changelog.rst

@@ -3,7 +3,7 @@
 Changelog
 ==========
 
-Release 2.2.0a4 (WIP)
+Release 2.2.0a5 (WIP)
 --------------------------
 
 Breaking Changes:
@@ -13,6 +13,7 @@ Breaking Changes:
 New Features:
 ^^^^^^^^^^^^^
 - Improved error message of the ``env_checker`` for env wrongly detected as GoalEnv (``compute_reward()`` is defined)
+- Improved error message when mixing Gym API with VecEnv API (see GH#1694)
 
 Bug Fixes:
 ^^^^^^^^^^

stable_baselines3/common/policies.py

@@ -343,6 +343,17 @@ class BasePolicy(BaseModel, ABC):
         # Switch to eval mode (this affects batch norm / dropout)
         self.set_training_mode(False)
 
+        # Check for common mistake that the user does not mix Gym/VecEnv API
+        # Tuple obs are not supported by SB3, so we can safely do that check
+        if isinstance(observation, tuple) and len(observation) == 2 and isinstance(observation[1], dict):
+            raise ValueError(
+                "You have passed a tuple to the predict() function instead of a Numpy array or a Dict. "
+                "You are probably mixing Gym API with SB3 VecEnv API: `obs, info = env.reset()` (Gym) "
+                "vs `obs = vec_env.reset()` (SB3 VecEnv). "
+                "See related issue https://github.com/DLR-RM/stable-baselines3/issues/1694 "
+                "and documentation for more information: https://stable-baselines3.readthedocs.io/en/master/guide/vec_envs.html#vecenv-api-vs-gym-api"
+            )
+
         observation, vectorized_env = self.obs_to_tensor(observation)
 
         with th.no_grad():

stable_baselines3/version.txt

@@ -1 +1 @@
-2.2.0a4
+2.2.0a5

tests/test_predict.py

@@ -116,3 +116,12 @@ def test_subclassed_space_env(model_class):
     model.learn(300)
     obs, _ = env.reset()
     env.step(model.predict(obs))
+
+
+def test_mixing_gym_vecenv_api():
+    env = gym.make("CartPole-v1")
+    model = PPO("MlpPolicy", env)
+    # Reset return a tuple (obs, info)
+    wrong_obs = env.reset()
+    with pytest.raises(ValueError, match="mixing Gym API"):
+        model.predict(wrong_obs)