Develop better error message for #3953 (#3963)

* Making the error for wrong number of agents raise consistently

* Better error message for inputs of wrong dimensions

Author: vincentpierre

gym-unity/gym_unity/envs/__init__.py

@@ -53,7 +53,6 @@ def __init__(
             self._env.step()
 
         self.visual_obs = None
-        self._n_agents = -1
 
         # Save the step result from the last time all Agents requested decisions.
         self._previous_decision_step: DecisionSteps = None
@@ -172,6 +171,7 @@ def step(self, action: List[Any]) -> GymStepResult:
 
         self._env.step()
         decision_step, terminal_step = self._env.get_steps(self.name)
+        self._check_agents(max(len(decision_step), len(terminal_step)))
         if len(terminal_step) != 0:
             # The agent is done
             self.game_over = True
@@ -264,10 +264,11 @@ def seed(self, seed: Any = None) -> None:
         logger.warning("Could not seed environment %s", self.name)
         return
 
-    def _check_agents(self, n_agents: int) -> None:
-        if self._n_agents > 1:
+    @staticmethod
+    def _check_agents(n_agents: int) -> None:
+        if n_agents > 1:
             raise UnityGymException(
-                "There can only be one Agent in the environment but {n_agents} were detected."
+                f"There can only be one Agent in the environment but {n_agents} were detected."
             )
 
     @property
@@ -290,10 +291,6 @@ def action_space(self):
     def observation_space(self):
         return self._observation_space
 
-    @property
-    def number_agents(self):
-        return self._n_agents
-
 
 class ActionFlattener:
     """

ml-agents-envs/mlagents_envs/environment.py

@@ -415,9 +415,9 @@ def set_actions(self, behavior_name: BehaviorName, action: np.ndarray) -> None:
         expected_shape = (len(self._env_state[behavior_name][0]), spec.action_size)
         if action.shape != expected_shape:
             raise UnityActionException(
-                "The behavior {0} needs an input of dimension {1} but received input of dimension {2}".format(
-                    behavior_name, expected_shape, action.shape
-                )
+                "The behavior {0} needs an input of dimension {1} for "
+                "(<number of agents>, <action size>) but received input of "
+                "dimension {2}".format(behavior_name, expected_shape, action.shape)
             )
         if action.dtype != expected_type:
             action = action.astype(expected_type)