yaml working

environments/factory/base_factory.py

@@ -1,4 +1,4 @@
-import pickle
+from argparse import Namespace
 from pathlib import Path
 from typing import List, Union, Iterable, NamedTuple
 
@@ -89,7 +89,8 @@ class Actions(Register):
         self.allow_diagonal_movement = movement_properties.allow_diagonal_movement
         self.allow_square_movement = movement_properties.allow_square_movement
         # FIXME: There is a bug in helpers because there actions are ints. and the order matters.
-        assert not(self.allow_square_movement is False and self.allow_diagonal_movement is True), "There is a bug in helpers!!!"
+        assert not(self.allow_square_movement is False and self.allow_diagonal_movement is True), \
+            "There is a bug in helpers!!!"
         super(Actions, self).__init__()
 
         if self.allow_square_movement:
@@ -109,11 +110,14 @@ class StateSlice(Register):
         self.register_additional_items(['level', *[f'agent#{i}' for i in range(offset, n_agents+offset)]])
 
 
+# noinspection PyAttributeOutsideInit
 class BaseFactory(gym.Env):
 
-    # def __setattr__(self, key, value):
-    #     if isinstance(value, dict):
-
+    def __setattr__(self, key, value):
+        if isinstance(value, dict):
+            super(BaseFactory, self).__setattr__(key, Namespace(**value))
+        else:
+            super(BaseFactory, self).__setattr__(key, value)
 
     @property
     def action_space(self):
@@ -199,8 +203,8 @@ class BaseFactory(gym.Env):
                 obs_padded = np.full((obs.shape[0], self.pomdp_radius ** 2 + 1, self.pomdp_radius ** 2 + 1), 1)
                 a_pos = np.argwhere(obs[h.AGENT_START_IDX] == h.IS_OCCUPIED_CELL)[0]
                 obs_padded[:,
-                    abs(a_pos[0]-self.pomdp_radius):abs(a_pos[0]-self.pomdp_radius)+obs.shape[1],
-                    abs(a_pos[1]-self.pomdp_radius):abs(a_pos[1]-self.pomdp_radius)+obs.shape[2]] = obs
+                           abs(a_pos[0]-self.pomdp_radius):abs(a_pos[0]-self.pomdp_radius)+obs.shape[1],
+                           abs(a_pos[1]-self.pomdp_radius):abs(a_pos[1]-self.pomdp_radius)+obs.shape[2]] = obs
                 obs = obs_padded
         else:
             obs = self._state
@@ -323,9 +327,11 @@ class BaseFactory(gym.Env):
         raise NotImplementedError
 
     def save_params(self, filepath: Path):
-        d = {key: val for key, val in self.__dict__.items() if not key.startswith('_') and not key.startswith('__')}
+        # noinspection PyProtectedMember
+        d = {key: val._asdict() if hasattr(val, '_asdict') else val for key, val in self.__dict__.items()
+             if not key.startswith('_') and not key.startswith('__')}
         filepath.parent.mkdir(parents=True, exist_ok=True)
 
-        with filepath.open('wb') as f:
-            # yaml.dump(d, f)
-            pickle.dump(d, f, protocol=pickle.HIGHEST_PROTOCOL)
+        with filepath.open('w') as f:
+            yaml.dump(d, f)
+            # pickle.dump(d, f, protocol=pickle.HIGHEST_PROTOCOL)

environments/factory/simple_factory.py

@@ -185,17 +185,21 @@ class SimpleFactory(BaseFactory):
 
 if __name__ == '__main__':
     render = True
+    import yaml
+    with Path(r'C:\Users\steff\projects\f_iks\debug_out\yaml.txt').open('r') as f:
+        env_kwargs = yaml.load(f)
+    factory = SimpleFactory(**env_kwargs)
 
-    dirt_props = DirtProperties()
-    move_props = MovementProperties(allow_diagonal_movement=False, allow_no_op=False)
-    factory = SimpleFactory(n_agents=2, dirt_properties=dirt_props, movement_properties=move_props, level='rooms',
-                            pomdp_radius=2)
+    # dirt_props = DirtProperties()
+    # move_props = MovementProperties(allow_diagonal_movement=False, allow_no_op=False)
+    # factory = SimpleFactory(n_agents=2, dirt_properties=dirt_props, movement_properties=move_props, level='rooms',
+    #                         pomdp_radius=2)
 
     n_actions = factory.action_space.n - 1
 
     for epoch in range(100):
-        random_actions = [(random.randint(0, n_actions), random.randint(0, n_actions)) for _ in range(200)]
-        env_state, this_reward, done_bool, _ = factory.reset()
+        random_actions = [[random.randint(0, n_actions) for _ in range(factory.n_agents)] for _ in range(200)]
+        env_state = factory.reset()
         for agent_i_action in random_actions:
             env_state, reward, done_bool, info_obj = factory.step(agent_i_action)
             if render:

main.py

@@ -5,12 +5,10 @@ from os import PathLike
 from pathlib import Path
 import time
 
-import numpy as np
 import pandas as pd
 from gym.wrappers import FrameStack
 
 from stable_baselines3.common.callbacks import CallbackList
-from stable_baselines3.common.vec_env import VecFrameStack, DummyVecEnv
 
 from environments.factory.base_factory import MovementProperties
 from environments.factory.simple_factory import DirtProperties, SimpleFactory
@@ -102,13 +100,12 @@ if __name__ == '__main__':
 
     out_path = None
 
-    for modeL_type in [PPO, A2C, RegDQN, DQN]:
+    for modeL_type in [PPO]:  # , A2C, RegDQN, DQN]:
         for seed in range(3):
 
             env = SimpleFactory(n_agents=1, dirt_properties=dirt_props, pomdp_radius=None, max_steps=400,
                                 movement_properties=move_props, level='rooms',
                                 omit_agent_slice_in_obs=True)
-            env.save_params(Path('debug_out', 'yaml.txt'))
 
             # env = FrameStack(env, 4)
 
@@ -125,7 +122,7 @@ if __name__ == '__main__':
                 [MonitorCallback(filepath=out_path / f'monitor_{identifier}.pick', plotting=False)]
             )
 
-            model.learn(total_timesteps=int(2e5), callback=callbacks)
+            model.learn(total_timesteps=int(5e5), callback=callbacks)
 
             save_path = out_path / f'model_{identifier}.zip'
             save_path.parent.mkdir(parents=True, exist_ok=True)

reload_agent.py

@@ -1,7 +1,7 @@
-import pickle
 import warnings
 from pathlib import Path
 
+import yaml
 from natsort import natsorted
 from stable_baselines3 import PPO
 from stable_baselines3.common.evaluation import evaluate_policy
@@ -19,9 +19,9 @@ if __name__ == '__main__':
     out_path = Path(__file__).parent / 'debug_out'
     model_path = out_path / model_name
 
-    with (model_path / f'env_{model_name}.pick').open('rb') as f:
-        env_kwargs = pickle.load(f)
-    env = SimpleFactory( **env_kwargs)
+    with Path(r'C:\Users\steff\projects\f_iks\debug_out\yaml.txt').open('r') as f:
+        env_kwargs = yaml.load(f)
+    env = SimpleFactory(**env_kwargs)
 
     # Edit THIS:
     model_files = list(natsorted((model_path / f'{run_id}_{model_name}').rglob('*.zip')))

requirements.txt

@@ -6,8 +6,8 @@ filelock==3.0.12
 kiwisolver==1.3.1
 matplotlib==3.4.1
 numpy==1.20.2
-pandas==1.2.4
-pygame==2.0.0
+pandas~=1.2.3
+pygame~=2.0.1
 pep517==0.10.0
 Pillow==8.2.0
 pyparsing==2.4.7
@@ -22,3 +22,9 @@ torchaudio==0.8.1
 torchvision==0.9.1
 typing-extensions==3.10.0.0
 virtualenv==20.4.6
+
+gym~=0.18.0
+PyYAML~=5.3.1
+pyglet~=1.5.0
+optuna~=2.7.0
+natsort~=7.1.1