small changes to test modified tree obs, but not working

RLLib_training/RailEnvRLLibWrapper.py

@@ -19,13 +19,14 @@ class RailEnvRLLibWrapper(MultiAgentEnv):
             vector_index = config.vector_index
         else:
             vector_index = 1
-        self.rail_generator = config["rail_generator"](nr_start_goal=config['number_of_agents'], min_dist=5,
-                                                       nr_extra=30, seed=config['seed'] * (1+vector_index))
+        #self.rail_generator = config["rail_generator"](nr_start_goal=config['number_of_agents'], min_dist=5,
+         #                                              nr_extra=30, seed=config['seed'] * (1+vector_index))
         set_seed(config['seed'] * (1+vector_index))
-        self.env = RailEnv(width=config["width"], height=config["height"], rail_generator=self.rail_generator,
+        #self.env = RailEnv(width=config["width"], height=config["height"],
+        self.env = RailEnv(width=10, height=20,
                 number_of_agents=config["number_of_agents"], obs_builder_object=config['obs_builder'])
 
-        self.env.load('./baselines/torch_training/railway/complex_scene.pkl')
+        self.env.load('/mount/SDC/flatland/baselines/torch_training/railway/complex_scene.pkl')
 
         self.width = self.env.width
         self.height = self.env.height
@@ -45,7 +46,6 @@ class RailEnvRLLibWrapper(MultiAgentEnv):
         self.agents = self.env.agents
         self.agents_static = self.env.agents_static
         self.dev_obs_dict = self.env.dev_obs_dict
-
         return obs
 
     def step(self, action_dict):

RLLib_training/custom_preprocessors.py

@@ -50,10 +50,10 @@ def norm_obs_clip(obs, clip_min=-1, clip_max=1):
 
 class CustomPreprocessor(Preprocessor):
     def _init_shape(self, obs_space, options):
-        return (105,)
+        return (111,)
 
     def transform(self, observation):
-        if len(observation) == 105:
+        if len(observation) == 111:
             return norm_obs_clip(observation)
         else:
             return observation

RLLib_training/experiment_configs/n_agents_experiment/config.gin

-run_experiment.name = "n_agents_results"
+run_experiment.name = "observation_benchmark_results"
 run_experiment.num_iterations = 1002
-run_experiment.save_every = 200
-run_experiment.hidden_sizes = [32, 32]
+run_experiment.save_every = 100
+run_experiment.hidden_sizes = [32,32]
 
 run_experiment.map_width = 20
 run_experiment.map_height = 20
-run_experiment.n_agents = {"grid_search": [1]}#, 2, 5, 10]}
-run_experiment.policy_folder_name = "ppo_policy_{config[n_agents]}_agents"
+run_experiment.n_agents = {"grid_search": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]}
+run_experiment.policy_folder_name = "ppo_policy_{config[obs_builder].__class__.__name__}_entropy_coeff_{config[entropy_coeff]}_{config[n_agents]}_agents_"
 
 run_experiment.horizon = 50
 run_experiment.seed = 123
 
+run_experiment.entropy_coeff = {"grid_search": [1e-3, 1e-2, 0]}
+
+run_experiment.obs_builder = {"grid_search": [@TreeObsForRailEnv()]}# [@TreeObsForRailEnv(), @GlobalObsForRailEnv() ]}
+TreeObsForRailEnv.max_depth = 2
+LocalObsForRailEnv.view_radius = 5
 

RLLib_training/experiment_configs/observation_benchmark_loaded_env/config.gin

 run_experiment.name = "observation_benchmark_loaded_env_results"
 run_experiment.num_iterations = 1002
 run_experiment.save_every = 50
-run_experiment.hidden_sizes = 32
+run_experiment.hidden_sizes = [32, 32]
 
 run_experiment.map_width = 20
 run_experiment.map_height = 20
@@ -10,9 +10,10 @@ run_experiment.policy_folder_name = "ppo_policy_{config[obs_builder].__class__._
 
 run_experiment.horizon = 50
 run_experiment.seed = 123
+run_experiment.conv_model = False
 
 run_experiment.entropy_coeff = 1e-2
 
-run_experiment.obs_builder = {"grid_search": [@LocalObsForRailEnv(), @TreeObsForRailEnv(), @GlobalObsForRailEnv(), @GlobalObsForRailEnvDirectionDependent]}
+run_experiment.obs_builder = @TreeObsForRailEnv()#{"grid_search": [@LocalObsForRailEnv(), @TreeObsForRailEnv(), @GlobalObsForRailEnv(), @GlobalObsForRailEnvDirectionDependent()]}
 TreeObsForRailEnv.max_depth = 2
 LocalObsForRailEnv.view_radius = 5

RLLib_training/train_experiment.py

@@ -52,6 +52,10 @@ def train(config, reporter):
 
     set_seed(config['seed'], config['seed'], config['seed'])
 
+    config['map_width']= 20
+    config['map_height']= 10
+    config['n_agents'] = 8
+
     # Example configuration to generate a random rail
     env_config = {"width": config['map_width'],
                   "height": config['map_height'],
@@ -62,7 +66,7 @@ def train(config, reporter):
 
     # Observation space and action space definitions
     if isinstance(config["obs_builder"], TreeObsForRailEnv):
-        obs_space = gym.spaces.Box(low=-float('inf'), high=float('inf'), shape=(105,))
+        obs_space = gym.spaces.Box(low=-float('inf'), high=float('inf'), shape=(111,))
         preprocessor = "tree_obs_prep"
 
     elif isinstance(config["obs_builder"], GlobalObsForRailEnv):
@@ -191,6 +195,6 @@ def run_experiment(name, num_iterations, n_agents, hidden_sizes, save_every,
 
 if __name__ == '__main__':
     gin.external_configurable(tune.grid_search)
-    dir = '/home/guillaume/EPFL/Master_Thesis/flatland/baselines/RLLib_training/experiment_configs/conv_model_test'  # To Modify
+    dir = '/mount/SDC/flatland/baselines/RLLib_training/experiment_configs/observation_benchmark_loaded_env'  # To Modify
     gin.parse_config_file(dir + '/config.gin')
     run_experiment(local_dir=dir)