Rebuttal (#15)

* pg+nuplan train

* Need map

* use gym wrapper

* use createGymWrapper

* doc

* use all scenarios!

* update 80000 scenario

* train script

scenarionet_training/scripts/train_nuplan.py

@@ -1,13 +1,13 @@
 import os.path
-from metadrive.envs.gym_wrapper import GymEnvWrapper
+from metadrive.envs.gym_wrapper import createGymWrapper
 from metadrive.envs.scenario_env import ScenarioEnv
 from scenarionet import SCENARIONET_REPO_PATH, SCENARIONET_DATASET_PATH
 from scenarionet_training.train_utils.multi_worker_PPO import MultiWorkerPPO
 from scenarionet_training.train_utils.utils import train, get_train_parser, get_exp_name
 
 config = dict(
-    env=GymEnvWrapper,
-    env_config=dict(inner_class=ScenarioEnv, inner_config=dict(
+    env=createGymWrapper(ScenarioEnv),
+    env_config=dict(
         # scenario
         start_scenario_index=0,
         num_scenarios=40000,
@@ -16,7 +16,7 @@ config = dict(
 
         # curriculum training
         curriculum_level=100,
-        target_success_rate=0.8, # or 0.7
+        target_success_rate=0.7,
         # episodes_to_evaluate_curriculum=400,  # default=num_scenarios/curriculum_level
 
         # traffic & light
@@ -42,7 +42,7 @@ config = dict(
 
         vehicle_config=dict(side_detector=dict(num_lasers=0))
 
-    )),
+    ),
 
     # ===== Evaluation =====
     evaluation_interval=15,