fix(nyz): fix atari a2c entry bug and add lunarlander parallel demo

Author: PaParaZz1

dizoo/atari/config/serial/pong/pong_a2c_config.py

@@ -51,11 +51,12 @@
     ),
     env_manager=dict(type='subprocess'),
     policy=dict(type='a2c'),
+    replay_buffer=dict(type='naive'),
 )
 pong_a2c_create_config = EasyDict(pong_a2c_create_config)
 create_config = pong_a2c_create_config
 
 if __name__ == '__main__':
-    # or you can enter `ding -m serial -c pong_a2c_config.py -s 0`
-    from ding.entry import serial_pipeline
-    serial_pipeline((main_config, create_config), seed=0)
+    # or you can enter `ding -m serial_onpolicy -c pong_a2c_config.py -s 0`
+    from ding.entry import serial_pipeline_onpolicy
+    serial_pipeline_onpolicy((main_config, create_config), seed=0)

dizoo/atari/config/serial/qbert/qbert_a2c_config.py

@@ -52,10 +52,11 @@
     ),
     env_manager=dict(type='subprocess'),
     policy=dict(type='a2c'),
+    replay_buffer=dict(type='naive'),
 )
 create_config = EasyDict(qbert_a2c_create_config)
 
 if __name__ == '__main__':
-    # or you can enter ding -m serial -c qbert_a2c_config.py -s 0
-    from ding.entry import serial_pipeline
-    serial_pipeline((main_config, create_config), seed=0)
+    # or you can enter ding -m serial_onpolicy -c qbert_a2c_config.py -s 0
+    from ding.entry import serial_pipeline_onpolicy
+    serial_pipeline_onpolicy((main_config, create_config), seed=0)

dizoo/atari/config/serial/spaceinvaders/spaceinvaders_a2c_config.py

@@ -54,11 +54,12 @@
     ),
     env_manager=dict(type='subprocess'),
     policy=dict(type='a2c'),
+    replay_buffer=dict(type='naive'),
 )
 spaceinvaders_a2c_create_config = EasyDict(spaceinvaders_a2c_create_config)
 create_config = spaceinvaders_a2c_create_config
 
 if __name__ == '__main__':
     # or you can enter ding -m serial_onpolicy -c spaceinvaders_a2c_config.py -s 0
-    from ding.entry import serial_pipeline
-    serial_pipeline((main_config, create_config), seed=0)
+    from ding.entry import serial_pipeline_onpolicy
+    serial_pipeline_onpolicy((main_config, create_config), seed=0)

dizoo/atari/entry/spaceinavders_dqn_eval.py renamed to dizoo/atari/entry/spaceinvaders_dqn_eval.py

@@ -0,0 +1,68 @@
+import gym
+from ditk import logging
+from ding.data.model_loader import FileModelLoader
+from ding.data.storage_loader import FileStorageLoader
+from ding.model import DQN
+from ding.policy import DQNPolicy
+from ding.envs import DingEnvWrapper, SubprocessEnvManagerV2
+from ding.data import DequeBuffer
+from ding.config import compile_config
+from ding.framework import task, ding_init
+from ding.framework.context import OnlineRLContext
+from ding.framework.middleware import OffPolicyLearner, StepCollector, interaction_evaluator, data_pusher, \
+    eps_greedy_handler, CkptSaver, ContextExchanger, ModelExchanger, online_logger, termination_checker, \
+    nstep_reward_enhancer
+from ding.utils import set_pkg_seed
+from dizoo.box2d.lunarlander.config.lunarlander_dqn_config import main_config, create_config
+
+
+def main():
+    logging.getLogger().setLevel(logging.INFO)
+    cfg = compile_config(main_config, create_cfg=create_config, auto=True, save_cfg=task.router.node_id == 0)
+    ding_init(cfg)
+    with task.start(async_mode=False, ctx=OnlineRLContext()):
+        collector_env = SubprocessEnvManagerV2(
+            env_fn=[lambda: DingEnvWrapper(gym.make("LunarLander-v2")) for _ in range(cfg.env.collector_env_num)],
+            cfg=cfg.env.manager
+        )
+        evaluator_env = SubprocessEnvManagerV2(
+            env_fn=[lambda: DingEnvWrapper(gym.make("LunarLander-v2")) for _ in range(cfg.env.evaluator_env_num)],
+            cfg=cfg.env.manager
+        )
+
+        set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda)
+
+        model = DQN(**cfg.policy.model)
+        buffer_ = DequeBuffer(size=cfg.policy.other.replay_buffer.replay_buffer_size)
+        policy = DQNPolicy(cfg.policy, model=model)
+
+        # Consider the case with multiple processes
+        if task.router.is_active:
+            # You can use labels to distinguish between workers with different roles,
+            # here we use node_id to distinguish.
+            if task.router.node_id == 0:
+                task.add_role(task.role.LEARNER)
+            elif task.router.node_id == 1:
+                task.add_role(task.role.EVALUATOR)
+            else:
+                task.add_role(task.role.COLLECTOR)
+
+            # Sync their context and model between each worker.
+            task.use(ContextExchanger(skip_n_iter=1))
+            task.use(ModelExchanger(model))
+
+        # Here is the part of single process pipeline.
+        task.use(interaction_evaluator(cfg, policy.eval_mode, evaluator_env))
+        task.use(eps_greedy_handler(cfg))
+        task.use(StepCollector(cfg, policy.collect_mode, collector_env))
+        task.use(nstep_reward_enhancer(cfg))
+        task.use(data_pusher(cfg, buffer_))
+        task.use(OffPolicyLearner(cfg, policy.learn_mode, buffer_))
+        task.use(online_logger(train_show_freq=50))
+        task.use(CkptSaver(cfg, policy, train_freq=1000))
+        task.use(termination_checker(max_env_step=int(3e6)))
+        task.run()
+
+
+if __name__ == "__main__":
+    main()