Merge pull request #5 from DLR-RM/check_test_env

Check test env in tests

tests/test_buffers.py

@@ -5,6 +5,7 @@
 from gym import spaces
 
 from stable_baselines3.common.buffers import DictReplayBuffer, DictRolloutBuffer, ReplayBuffer, RolloutBuffer
+from stable_baselines3.common.env_checker import check_env
 from stable_baselines3.common.env_util import make_vec_env
 from stable_baselines3.common.type_aliases import DictReplayBufferSamples, ReplayBufferSamples
 from stable_baselines3.common.utils import get_device
@@ -19,7 +20,7 @@ class DummyEnv(gym.Env):
     def __init__(self):
         self.action_space = spaces.Box(1, 5, (1,))
         self.observation_space = spaces.Box(1, 5, (1,))
-        self._observations = [1, 2, 3, 4, 5]
+        self._observations = np.array([[1.0], [2.0], [3.0], [4.0], [5.0]], dtype=np.float32)
         self._rewards = [1, 2, 3, 4, 5]
         self._t = 0
         self._ep_length = 100
@@ -47,7 +48,7 @@ def __init__(self):
         self.action_space = spaces.Box(1, 5, (1,))
         space = spaces.Box(1, 5, (1,))
         self.observation_space = spaces.Dict({"observation": space, "achieved_goal": space, "desired_goal": space})
-        self._observations = [1, 2, 3, 4, 5]
+        self._observations = np.array([[1.0], [2.0], [3.0], [4.0], [5.0]], dtype=np.float32)
         self._rewards = [1, 2, 3, 4, 5]
         self._t = 0
         self._ep_length = 100
@@ -66,6 +67,13 @@ def step(self, action):
         return obs, reward, done, truncated, {}
 
 
+@pytest.mark.parametrize("env_cls", [DummyEnv, DummyDictEnv])
+def test_env(env_cls):
+    # Check the env used for testing
+    # Do not warn for assymetric space
+    check_env(env_cls(), warn=False, skip_render_check=True)
+
+
 @pytest.mark.parametrize("replay_buffer_cls", [ReplayBuffer, DictReplayBuffer])
 def test_replay_buffer_normalization(replay_buffer_cls):
     env = {ReplayBuffer: DummyEnv, DictReplayBuffer: DummyDictEnv}[replay_buffer_cls]

tests/test_dict_env.py

@@ -6,6 +6,7 @@
 from gym import spaces
 
 from stable_baselines3 import A2C, DDPG, DQN, PPO, SAC, TD3
+from stable_baselines3.common.env_checker import check_env
 from stable_baselines3.common.env_util import make_vec_env
 from stable_baselines3.common.envs import BitFlippingEnv, SimpleMultiObsEnv
 from stable_baselines3.common.evaluation import evaluate_policy
@@ -71,9 +72,6 @@ def step(self, action):
         done = truncated = False
         return self.observation_space.sample(), reward, done, truncated, {}
 
-    def compute_reward(self, achieved_goal, desired_goal, info):
-        return np.zeros((len(achieved_goal),))
-
     def reset(self, *, seed: Optional[int] = None, options: Optional[Dict] = None):
         if seed is not None:
             self.observation_space.seed(seed)
@@ -83,6 +81,19 @@ def render(self):
         pass
 
 
+@pytest.mark.parametrize("use_discrete_actions", [True, False])
+@pytest.mark.parametrize("channel_last", [True, False])
+@pytest.mark.parametrize("nested_dict_obs", [True, False])
+@pytest.mark.parametrize("vec_only", [True, False])
+def test_env(use_discrete_actions, channel_last, nested_dict_obs, vec_only):
+    # Check the env used for testing
+    if nested_dict_obs:
+        with pytest.warns(UserWarning, match="Nested observation spaces are not supported"):
+            check_env(DummyDictEnv(use_discrete_actions, channel_last, nested_dict_obs, vec_only))
+    else:
+        check_env(DummyDictEnv(use_discrete_actions, channel_last, nested_dict_obs, vec_only))
+
+
 @pytest.mark.parametrize("policy", ["MlpPolicy", "CnnPolicy"])
 def test_policy_hint(policy):
     # Common mistake: using the wrong policy

tests/test_gae.py

@@ -8,6 +8,7 @@
 
 from stable_baselines3 import A2C, PPO, SAC
 from stable_baselines3.common.callbacks import BaseCallback
+from stable_baselines3.common.env_checker import check_env
 from stable_baselines3.common.policies import ActorCriticPolicy
 
 
@@ -121,6 +122,12 @@ def forward(self, obs, deterministic=False):
         return actions, values, log_prob
 
 
+@pytest.mark.parametrize("env_cls", [CustomEnv, InfiniteHorizonEnv])
+def test_env(env_cls):
+    # Check the env used for testing
+    check_env(env_cls(), skip_render_check=True)
+
+
 @pytest.mark.parametrize("model_class", [A2C, PPO])
 @pytest.mark.parametrize("gae_lambda", [1.0, 0.9])
 @pytest.mark.parametrize("gamma", [1.0, 0.99])

tests/test_logger.py

@@ -13,6 +13,7 @@
 from pandas.errors import EmptyDataError
 
 from stable_baselines3 import A2C, DQN
+from stable_baselines3.common.env_checker import check_env
 from stable_baselines3.common.logger import (
     DEBUG,
     INFO,
@@ -363,6 +364,12 @@ def step(self, action):
         return obs, 0.0, True, False, {}
 
 
+@pytest.mark.parametrize("env_cls", [TimeDelayEnv])
+def test_env(env_cls):
+    # Check the env used for testing
+    check_env(env_cls(), skip_render_check=True)
+
+
 class InMemoryLogger(Logger):
     """
     Logger that keeps key/value pairs in memory without any writers.

tests/test_predict.py

@@ -5,6 +5,7 @@
 from gym import spaces
 
 from stable_baselines3 import A2C, DQN, PPO, SAC, TD3
+from stable_baselines3.common.env_checker import check_env
 from stable_baselines3.common.envs import IdentityEnv
 from stable_baselines3.common.utils import get_device
 from stable_baselines3.common.vec_env import DummyVecEnv
@@ -36,6 +37,12 @@ def step(self, action):
         return self.observation_space.sample(), 0.0, np.random.rand() > 0.5, False, {}
 
 
+@pytest.mark.parametrize("env_cls", [CustomSubClassedSpaceEnv])
+def test_env(env_cls):
+    # Check the env used for testing
+    check_env(env_cls(), skip_render_check=True)
+
+
 @pytest.mark.parametrize("model_class", MODEL_LIST)
 def test_auto_wrap(model_class):
     """Test auto wrapping of env into a VecEnv."""

tests/test_spaces.py

@@ -6,6 +6,7 @@
 from gym import spaces
 
 from stable_baselines3 import A2C, DDPG, DQN, PPO, SAC, TD3
+from stable_baselines3.common.env_checker import check_env
 from stable_baselines3.common.env_util import make_vec_env
 from stable_baselines3.common.evaluation import evaluate_policy
 
@@ -53,6 +54,12 @@ def step(self, action):
         return self.observation_space.sample(), 0.0, False, False, {}
 
 
+@pytest.mark.parametrize("env", [DummyMultiDiscreteSpace([4, 3]), DummyMultiBinary(8), DummyMultiBinary((3, 2))])
+def test_env(env):
+    # Check the env used for testing
+    check_env(env, skip_render_check=True)
+
+
 @pytest.mark.parametrize("model_class", [SAC, TD3, DQN])
 @pytest.mark.parametrize("env", [DummyMultiDiscreteSpace([4, 3]), DummyMultiBinary(8), DummyMultiBinary((3, 2))])
 def test_identity_spaces(model_class, env):