Log Environments

tianshou/highlevel/env.py

@@ -8,6 +8,7 @@ import gymnasium as gym
 from tianshou.env import BaseVectorEnv
 from tianshou.highlevel.persistence import PersistableConfigProtocol
 from tianshou.utils.net.common import TActionShape
+from tianshou.utils.string import ToStringMixin
 
 TObservationShape: TypeAlias = int | Sequence[int]
 
@@ -31,12 +32,18 @@ class EnvType(Enum):
             raise AssertionError(f"{requiring_entity} requires discrete environments")
 
 
-class Environments(ABC):
+class Environments(ToStringMixin, ABC):
     def __init__(self, env: gym.Env, train_envs: BaseVectorEnv, test_envs: BaseVectorEnv):
         self.env = env
         self.train_envs = train_envs
         self.test_envs = test_envs
 
+    def _tostring_includes(self) -> list[str]:
+        return []
+
+    def _tostring_additional_entries(self) -> dict[str, Any]:
+        return self.info()
+
     def info(self) -> dict[str, Any]:
         return {
             "action_shape": self.get_action_shape(),

tianshou/highlevel/experiment.py

@@ -102,6 +102,7 @@ class Experiment(Generic[TPolicy, TTrainer], ToStringMixin):
     def run(self, log_name: str) -> None:
         self._set_seed()
         envs = self.env_factory(self.env_config)
+        log.info(f"Created {envs}")
 
         full_config = self._build_config_dict()
         full_config.update(envs.info())