default ActionTuple to None

ml-agents-envs/mlagents_envs/base_env.py

         for the correct number of agents and ensures the type.
         """
         _expected_shape = (n_agents, self.continuous_size)
-        if actions.continuous.shape != _expected_shape:
+        if self.continuous_size > 0 and actions.continuous.shape != _expected_shape:
             raise UnityActionException(
                 f"The behavior {name} needs a continuous input of dimension "
                 f"{_expected_shape} for (<number of agents>, <action size>) but "
-        if actions.discrete.shape != _expected_shape:
+        if self.discrete_size > 0 and actions.discrete.shape != _expected_shape:
             raise UnityActionException(
                 f"The behavior {name} needs a discrete input of dimension "
                 f"{_expected_shape} for (<number of agents>, <action size>) but "

ml-agents/mlagents/trainers/env_manager.py

 
     @staticmethod
     def action_tuple_from_numpy_dict(action_dict: Dict[str, np.ndarray]) -> ActionTuple:
-        continuous: np.ndarray = np.array([], dtype=np.float32)
-        discrete: np.ndarray = np.array([], dtype=np.int32)
+        continuous: np.ndarray = None
+        discrete: np.ndarray = None
         if "continuous_action" in action_dict:
             continuous = action_dict["continuous_action"]
         if "discrete_action" in action_dict: