Stable Baseline Running

environments/factory/base_factory.py

@@ -1,3 +1,4 @@
+import abc
 from typing import List, Union, Iterable
 
 import gym
@@ -61,17 +62,14 @@ class BaseFactory(gym.Env):
         self.allow_horizontal_movement = True
         self.allow_no_OP = True
         self._monitor_list = list()
-        self._registered_actions = self.movement_actions + int(self.allow_no_OP)
+        self._registered_actions = self.movement_actions + int(self.allow_no_OP) + self.register_additional_actions()
         self.level = h.one_hot_level(
             h.parse_level(Path(__file__).parent / h.LEVELS_DIR / f'{level}.txt')
         )
         self.slice_strings = {0: 'level', **{i: f'agent#{i}' for i in range(1, self.n_agents+1)}}
         self.reset()
 
-    def __init_subclass__(cls):
-        print(cls)
-
-    def register_additional_actions(self):
+    def register_additional_actions(self) -> int:
         raise NotImplementedError('Please register additional actions ')
 
     def reset(self) -> (np.ndarray, int, bool, dict):
@@ -111,6 +109,8 @@ class BaseFactory(gym.Env):
             agent_i_state = AgentState(agent_i, action)
             if self._is_moving_action(action):
                 pos, valid = self.move_or_colide(agent_i, action)
+            elif self._is_no_op(action):
+                pos, valid = self.agent_i_position(agent_i), True
             else:
                 pos, valid = self.additional_actions(agent_i, action)
             # Update state accordingly
@@ -129,10 +129,10 @@ class BaseFactory(gym.Env):
         return self.state, self.cumulative_reward, self.done, info
 
     def _is_moving_action(self, action):
-        if action < self.movement_actions:
-            return True
-        else:
-            return False
+        return action < self.movement_actions
+
+    def _is_no_op(self, action):
+        return self.allow_no_OP and (action - self.movement_actions) == 0
 
     def check_all_collisions(self, agent_states: List[AgentState], collisions: int) -> np.ndarray:
         collision_vecs = np.zeros((len(agent_states), collisions))  # n_agents x n_slices