style(pu): bash format.sh

opendilab · Nov 4, 2024 · 22d5110 · 22d5110
1 parent 0968723
commit 22d5110
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Showing 29 changed files with 137 additions and 168 deletions.
diff --git a/ding/entry/serial_entry.py b/ding/entry/serial_entry.py
@@ -47,7 +47,15 @@ def serial_pipeline(
         cfg, create_cfg = deepcopy(input_cfg)
     create_cfg.policy.type = create_cfg.policy.type + '_command'
     env_fn = None if env_setting is None else env_setting[0]
-    cfg = compile_config(cfg, seed=seed, env=env_fn, auto=True, create_cfg=create_cfg, save_cfg=True, renew_dir=not cfg.policy.learn.resume_training)
+    cfg = compile_config(
+        cfg,
+        seed=seed,
+        env=env_fn,
+        auto=True,
+        create_cfg=create_cfg,
+        save_cfg=True,
+        renew_dir=not cfg.policy.learn.resume_training
+    )
     # Create main components: env, policy
     if env_setting is None:
         env_fn, collector_env_cfg, evaluator_env_cfg = get_vec_env_setting(cfg.env)

diff --git a/ding/entry/serial_entry_mbrl.py b/ding/entry/serial_entry_mbrl.py
@@ -30,7 +30,15 @@ def mbrl_entry_setup(
         cfg, create_cfg = deepcopy(input_cfg)
     create_cfg.policy.type = create_cfg.policy.type + '_command'
     env_fn = None if env_setting is None else env_setting[0]
-    cfg = compile_config(cfg, seed=seed, env=env_fn, auto=True, create_cfg=create_cfg, save_cfg=True, renew_dir=not cfg.policy.learn.resume_training)
+    cfg = compile_config(
+        cfg,
+        seed=seed,
+        env=env_fn,
+        auto=True,
+        create_cfg=create_cfg,
+        save_cfg=True,
+        renew_dir=not cfg.policy.learn.resume_training
+    )
 
     if env_setting is None:
         env_fn, collector_env_cfg, evaluator_env_cfg = get_vec_env_setting(cfg.env)
@@ -71,16 +79,7 @@ def mbrl_entry_setup(
     )
 
     return (
-        cfg,
-        policy,
-        world_model,
-        env_buffer,
-        learner,
-        collector,
-        collector_env,
-        evaluator,
-        commander,
-        tb_logger,
+        cfg, policy, world_model, env_buffer, learner, collector, collector_env, evaluator, commander, tb_logger,
         resume_training
     )
 

diff --git a/ding/entry/serial_entry_ngu.py b/ding/entry/serial_entry_ngu.py
@@ -47,7 +47,15 @@ def serial_pipeline_ngu(
         cfg, create_cfg = deepcopy(input_cfg)
     create_cfg.policy.type = create_cfg.policy.type + '_command'
     env_fn = None if env_setting is None else env_setting[0]
-    cfg = compile_config(cfg, seed=seed, env=env_fn, auto=True, create_cfg=create_cfg, save_cfg=True, renew_dir=not cfg.policy.learn.resume_training)
+    cfg = compile_config(
+        cfg,
+        seed=seed,
+        env=env_fn,
+        auto=True,
+        create_cfg=create_cfg,
+        save_cfg=True,
+        renew_dir=not cfg.policy.learn.resume_training
+    )
     # Create main components: env, policy
     if env_setting is None:
         env_fn, collector_env_cfg, evaluator_env_cfg = get_vec_env_setting(cfg.env)

diff --git a/ding/entry/serial_entry_onpolicy.py b/ding/entry/serial_entry_onpolicy.py
@@ -45,7 +45,15 @@ def serial_pipeline_onpolicy(
         cfg, create_cfg = deepcopy(input_cfg)
     create_cfg.policy.type = create_cfg.policy.type + '_command'
     env_fn = None if env_setting is None else env_setting[0]
-    cfg = compile_config(cfg, seed=seed, env=env_fn, auto=True, create_cfg=create_cfg, save_cfg=True, renew_dir=not cfg.policy.learn.resume_training)
+    cfg = compile_config(
+        cfg,
+        seed=seed,
+        env=env_fn,
+        auto=True,
+        create_cfg=create_cfg,
+        save_cfg=True,
+        renew_dir=not cfg.policy.learn.resume_training
+    )
     # Create main components: env, policy
     if env_setting is None:
         env_fn, collector_env_cfg, evaluator_env_cfg = get_vec_env_setting(cfg.env)

diff --git a/ding/entry/serial_entry_onpolicy_ppg.py b/ding/entry/serial_entry_onpolicy_ppg.py
@@ -45,7 +45,15 @@ def serial_pipeline_onpolicy_ppg(
         cfg, create_cfg = deepcopy(input_cfg)
     create_cfg.policy.type = create_cfg.policy.type + '_command'
     env_fn = None if env_setting is None else env_setting[0]
-    cfg = compile_config(cfg, seed=seed, env=env_fn, auto=True, create_cfg=create_cfg, save_cfg=True, renew_dir=not cfg.policy.learn.resume_training)
+    cfg = compile_config(
+        cfg,
+        seed=seed,
+        env=env_fn,
+        auto=True,
+        create_cfg=create_cfg,
+        save_cfg=True,
+        renew_dir=not cfg.policy.learn.resume_training
+    )
     # Create main components: env, policy
     if env_setting is None:
         env_fn, collector_env_cfg, evaluator_env_cfg = get_vec_env_setting(cfg.env)

diff --git a/dizoo/cliffwalking/envs/cliffwalking_env.py b/dizoo/cliffwalking/envs/cliffwalking_env.py
@@ -24,8 +24,8 @@ def __init__(self, cfg: dict) -> None:
         self._replay_path = None
         self._observation_space = gym.spaces.Box(low=0, high=1, shape=(48, ), dtype=np.float32)
         self._env = gym.make(
-                "CliffWalking", render_mode=self._cfg.render_mode, max_episode_steps=self._cfg.max_episode_steps
-            )
+            "CliffWalking", render_mode=self._cfg.render_mode, max_episode_steps=self._cfg.max_episode_steps
+        )
         self._action_space = self._env.action_space
         self._reward_space = gym.spaces.Box(
             low=self._env.reward_range[0], high=self._env.reward_range[1], shape=(1, ), dtype=np.float32

diff --git a/dizoo/d4rl/config/antmaze_umaze_pd_config.py b/dizoo/d4rl/config/antmaze_umaze_pd_config.py
@@ -45,7 +45,7 @@
             value_model_cfg=dict(
                 model='TemporalValue',
                 model_cfg=dict(
-                    horizon = 256,
+                    horizon=256,
                     transition_dim=37,
                     dim=32,
                     dim_mults=[1, 2, 4, 8],
@@ -92,10 +92,8 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)
-create_config = create_config
+create_config = create_config
diff --git a/dizoo/d4rl/config/halfcheetah_medium_expert_pd_config.py b/dizoo/d4rl/config/halfcheetah_medium_expert_pd_config.py
@@ -45,7 +45,7 @@
             value_model_cfg=dict(
                 model='TemporalValue',
                 model_cfg=dict(
-                    horizon = 4,
+                    horizon=4,
                     transition_dim=23,
                     dim=32,
                     dim_mults=[1, 4, 8],
@@ -92,9 +92,7 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)

diff --git a/dizoo/d4rl/config/halfcheetah_medium_expert_qgpo_config.py b/dizoo/d4rl/config/halfcheetah_medium_expert_qgpo_config.py
@@ -7,9 +7,7 @@
         evaluator_env_num=8,
         n_evaluator_episode=8,
     ),
-    dataset=dict(
-        env_id="halfcheetah-medium-expert-v2",
-    ),
+    dataset=dict(env_id="halfcheetah-medium-expert-v2", ),
     policy=dict(
         cuda=True,
         on_policy=False,
@@ -44,8 +42,6 @@
 
 create_config = dict(
     env_manager=dict(type='base'),
-    policy=dict(
-        type='qgpo',
-    ),
+    policy=dict(type='qgpo', ),
 )
 create_config = EasyDict(create_config)
diff --git a/dizoo/d4rl/config/halfcheetah_medium_pd_config.py b/dizoo/d4rl/config/halfcheetah_medium_pd_config.py
@@ -45,7 +45,7 @@
             value_model_cfg=dict(
                 model='TemporalValue',
                 model_cfg=dict(
-                    horizon = 4,
+                    horizon=4,
                     transition_dim=23,
                     dim=32,
                     dim_mults=[1, 4, 8],
@@ -92,9 +92,7 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)

diff --git a/dizoo/d4rl/config/hopper_medium_expert_pd_config.py b/dizoo/d4rl/config/hopper_medium_expert_pd_config.py
@@ -45,7 +45,7 @@
             value_model_cfg=dict(
                 model='TemporalValue',
                 model_cfg=dict(
-                    horizon = 32,
+                    horizon=32,
                     transition_dim=14,
                     dim=32,
                     dim_mults=[1, 2, 4, 8],
@@ -92,10 +92,8 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)
-create_config = create_config
+create_config = create_config
diff --git a/dizoo/d4rl/config/hopper_medium_expert_qgpo_config.py b/dizoo/d4rl/config/hopper_medium_expert_qgpo_config.py
@@ -7,9 +7,7 @@
         evaluator_env_num=8,
         n_evaluator_episode=8,
     ),
-    dataset=dict(
-        env_id="hopper-medium-expert-v2",
-    ),
+    dataset=dict(env_id="hopper-medium-expert-v2", ),
     policy=dict(
         cuda=True,
         on_policy=False,
@@ -44,8 +42,6 @@
 
 create_config = dict(
     env_manager=dict(type='base'),
-    policy=dict(
-        type='qgpo',
-    ),
+    policy=dict(type='qgpo', ),
 )
 create_config = EasyDict(create_config)
diff --git a/dizoo/d4rl/config/hopper_medium_pd_config.py b/dizoo/d4rl/config/hopper_medium_pd_config.py
@@ -45,7 +45,7 @@
             value_model_cfg=dict(
                 model='TemporalValue',
                 model_cfg=dict(
-                    horizon = 32,
+                    horizon=32,
                     transition_dim=14,
                     dim=32,
                     dim_mults=[1, 2, 4, 8],
@@ -92,10 +92,8 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)
-create_config = create_config
+create_config = create_config
diff --git a/dizoo/d4rl/config/maze2d_large_pd_config.py b/dizoo/d4rl/config/maze2d_large_pd_config.py
@@ -75,10 +75,8 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)
-create_config = create_config
+create_config = create_config
diff --git a/dizoo/d4rl/config/maze2d_medium_pd_config.py b/dizoo/d4rl/config/maze2d_medium_pd_config.py
@@ -75,10 +75,8 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)
-create_config = create_config
+create_config = create_config
diff --git a/dizoo/d4rl/config/maze2d_umaze_pd_config.py b/dizoo/d4rl/config/maze2d_umaze_pd_config.py
@@ -75,10 +75,8 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)
-create_config = create_config
+create_config = create_config
diff --git a/dizoo/d4rl/config/walker2d_medium_expert_pd_config.py b/dizoo/d4rl/config/walker2d_medium_expert_pd_config.py
@@ -45,7 +45,7 @@
             value_model_cfg=dict(
                 model='TemporalValue',
                 model_cfg=dict(
-                    horizon = 32,
+                    horizon=32,
                     transition_dim=23,
                     dim=32,
                     dim_mults=[1, 2, 4, 8],
@@ -92,10 +92,8 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)
-create_config = create_config
+create_config = create_config
diff --git a/dizoo/d4rl/config/walker2d_medium_expert_qgpo_config.py b/dizoo/d4rl/config/walker2d_medium_expert_qgpo_config.py
@@ -7,9 +7,7 @@
         evaluator_env_num=8,
         n_evaluator_episode=8,
     ),
-    dataset=dict(
-        env_id="walker2d-medium-expert-v2",
-    ),
+    dataset=dict(env_id="walker2d-medium-expert-v2", ),
     policy=dict(
         cuda=True,
         on_policy=False,
@@ -44,8 +42,6 @@
 
 create_config = dict(
     env_manager=dict(type='base'),
-    policy=dict(
-        type='qgpo',
-    ),
+    policy=dict(type='qgpo', ),
 )
 create_config = EasyDict(create_config)
diff --git a/dizoo/d4rl/config/walker2d_medium_pd_config.py b/dizoo/d4rl/config/walker2d_medium_pd_config.py
@@ -45,7 +45,7 @@
             value_model_cfg=dict(
                 model='TemporalValue',
                 model_cfg=dict(
-                    horizon = 32,
+                    horizon=32,
                     transition_dim=23,
                     dim=32,
                     dim_mults=[1, 2, 4, 8],
@@ -92,10 +92,8 @@
         import_names=['dizoo.d4rl.envs.d4rl_env'],
     ),
     env_manager=dict(type='subprocess'),
-    policy=dict(
-        type='pd',
-    ),
+    policy=dict(type='pd', ),
     replay_buffer=dict(type='naive', ),
 )
 create_config = EasyDict(create_config)
-create_config = create_config
+create_config = create_config
diff --git a/dizoo/d4rl/entry/d4rl_pd_main.py b/dizoo/d4rl/entry/d4rl_pd_main.py
@@ -5,7 +5,7 @@
 
 def train(args):
     # launch from anywhere
-    config = Path(__file__).absolute().parent.parent / 'config' / args.config 
+    config = Path(__file__).absolute().parent.parent / 'config' / args.config
     config = read_config(str(config))
     config[0].exp_name = config[0].exp_name.replace('0', str(args.seed))
     serial_pipeline_offline(config, seed=args.seed)
@@ -18,4 +18,4 @@ def train(args):
     parser.add_argument('--seed', '-s', type=int, default=10)
     parser.add_argument('--config', '-c', type=str, default='halfcheetah_medium_pd_config.py')
     args = parser.parse_args()
-    train(args)
+    train(args)