johnjim0816 commited on May 18, 2023

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8ba2a32

•

1 Parent(s): 54d82df

update Cartpole-v1 PER DQN

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ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/config.yaml +0 -48
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/logs/log.txt +0 -54
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/models/checkpoint.pt +0 -3
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/results/learning_curve.png +0 -0
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/results/res.csv +0 -11
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_mp_20230415-215147/config.yaml +0 -55
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_mp_20230415-215147/logs/log.txt +0 -58
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_mp_20230415-215147/results/learning_curve.png +0 -0
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_mp_20230415-215147/results/res.csv +0 -11
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_ray_20230415-220540/config.yaml +0 -55
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_ray_20230415-220540/logs/log.txt +0 -58
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_ray_20230415-220540/models/checkpoint.pt +0 -3
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_ray_20230415-220540/results/learning_curve.png +0 -0
ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_ray_20230415-220540/results/res.csv +0 -11
ClassControl/CartPole-v1/Test_single_CartPole-v1_DQN_20230515-211926/logs/log.txt +0 -57
ClassControl/CartPole-v1/Test_single_CartPole-v1_DQN_20230515-211926/results/trajs_0.pkl +0 -3
ClassControl/CartPole-v1/Test_single_CartPole-v1_DQN_20230515-211926/tb_logs/model/events.out.tfevents.1684156766.DESKTOP-H34HQIQ.16348.1 +0 -3
ClassControl/CartPole-v1/Test_single_CartPole-v1_DQN_20230515-211926/videos/video.gif +0 -3
ClassControl/CartPole-v1/{Test_single_CartPole-v1_DQN_20230515-211926 → Test_single_CartPole-v1_PER_DQN_20230518-232330}/config.yaml +17 -13
ClassControl/CartPole-v1/Test_single_CartPole-v1_PER_DQN_20230518-232330/logs/log.txt +61 -0
ClassControl/CartPole-v1/{Test_single_CartPole-v1_DQN_20230515-211926/tb_logs/interact/events.out.tfevents.1684156766.DESKTOP-H34HQIQ.16348.0 → Test_single_CartPole-v1_PER_DQN_20230518-232330/tb_logs/interact/events.out.tfevents.1684423410.DESKTOP-H34HQIQ.83344.0} +1 -1
ClassControl/CartPole-v1/{Test_CartPole-v1_PER_DQN_20230331-231442/tb_logs/events.out.tfevents.1680275682.DESKTOP-H34HQIQ.290376.0 → Test_single_CartPole-v1_PER_DQN_20230518-232330/tb_logs/model/events.out.tfevents.1684423410.DESKTOP-H34HQIQ.83344.1} +1 -1
ClassControl/CartPole-v1/Train_CartPole-v1_PERQue_DQN_20230331-233749/config.yaml +0 -48
ClassControl/CartPole-v1/Train_CartPole-v1_PERQue_DQN_20230331-233749/logs/log.txt +0 -260
ClassControl/CartPole-v1/Train_CartPole-v1_PERQue_DQN_20230331-233749/models/checkpoint.pt +0 -3
ClassControl/CartPole-v1/Train_CartPole-v1_PERQue_DQN_20230331-233749/results/learning_curve.png +0 -0
ClassControl/CartPole-v1/Train_CartPole-v1_PERQue_DQN_20230331-233749/results/res.csv +0 -201
ClassControl/CartPole-v1/Train_CartPole-v1_PERQue_DQN_20230331-233749/tb_logs/events.out.tfevents.1680277069.DESKTOP-H34HQIQ.305216.0 +0 -3
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_20230331-225815/config.yaml +0 -48
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_20230331-225815/logs/log.txt +0 -267
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_20230331-225815/models/checkpoint.pt +0 -3
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_20230331-225815/results/learning_curve.png +0 -0
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_20230331-225815/results/res.csv +0 -201
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_20230331-225815/tb_logs/events.out.tfevents.1680274695.DESKTOP-H34HQIQ.317208.0 +0 -3
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_mp__20230415-215002/config.yaml +0 -55
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_mp__20230415-215002/logs/log.txt +0 -48
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_mp__20230415-215002/models/checkpoint.pt +0 -3
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_mp__20230415-215002/results/learning_curve.png +0 -0
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_mp__20230415-215002/results/res.csv +0 -202
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_ray_20230415-215738/config.yaml +0 -55
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_ray_20230415-215738/logs/log.txt +0 -48
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_ray_20230415-215738/models/checkpoint.pt +0 -3
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_ray_20230415-215738/results/learning_curve.png +0 -0
ClassControl/CartPole-v1/Train_CartPole-v1_PER_DQN_ray_20230415-215738/results/res.csv +0 -251
ClassControl/CartPole-v1/Train_ray_CartPole-v1_DQN_20230515-221916/config.yaml +0 -45
ClassControl/CartPole-v1/Train_ray_CartPole-v1_DQN_20230515-221916/logs/log.txt +0 -166
ClassControl/CartPole-v1/Train_ray_CartPole-v1_DQN_20230515-221916/models/1000 +0 -0
ClassControl/CartPole-v1/Train_ray_CartPole-v1_DQN_20230515-221916/models/1500 +0 -0
ClassControl/CartPole-v1/Train_ray_CartPole-v1_DQN_20230515-221916/models/2000 +0 -0
ClassControl/CartPole-v1/Train_ray_CartPole-v1_DQN_20230515-221916/models/2500 +0 -0

ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/config.yaml DELETED Viewed

@@ -1,48 +0,0 @@
-general_cfg:
-  algo_name: PER_DQN
-  device: cuda
-  env_name: CartPole-v1
-  eval_eps: 10
-  eval_per_episode: 5
-  load_checkpoint: true
-  load_path: Train_CartPole-v1_PER_DQN_20230331-225815
-  max_steps: 200
-  mode: test
-  new_step_api: true
-  render: false
-  save_fig: true
-  seed: 1
-  show_fig: false
-  test_eps: 10
-  train_eps: 100
-  wrapper: null
-algo_cfg:
-  batch_size: 64
-  buffer_size: 100000
-  epsilon_decay: 500
-  epsilon_end: 0.01
-  epsilon_start: 0.95
-  gamma: 0.99
-  hidden_dim: 256
-  lr: 0.0001
-  per_alpha: 0.6
-  per_beta: 0.4
-  per_beta_annealing: 0.001
-  per_epsilon: 0.01
-  target_update: 4
-  value_layers:
-  - activation: relu
-    layer_dim:
-    - n_states
-    - 256
-    layer_type: linear
-  - activation: relu
-    layer_dim:
-    - 256
-    - 256
-    layer_type: linear
-  - activation: none
-    layer_dim:
-    - 256
-    - n_actions
-    layer_type: linear

ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/logs/log.txt DELETED Viewed

@@ -1,54 +0,0 @@
-2023-03-31 23:14:42 - r - INFO: - Hyperparameters:
-2023-03-31 23:14:42 - r - INFO: - ================================================================================
-2023-03-31 23:14:42 - r - INFO: -         Name        	       Value        	        Type
-2023-03-31 23:14:42 - r - INFO: -       env_name      	    CartPole-v1     	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -     new_step_api    	         1          	   <class 'bool'>
-2023-03-31 23:14:42 - r - INFO: -       wrapper       	        None        	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -        render       	         0          	   <class 'bool'>
-2023-03-31 23:14:42 - r - INFO: -      algo_name      	      PER_DQN       	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -         mode        	        test        	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -         seed        	         1          	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -        device       	        cuda        	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -      train_eps      	        100         	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -       test_eps      	         10         	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -       eval_eps      	         10         	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -   eval_per_episode  	         5          	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -      max_steps      	        200         	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -   load_checkpoint   	         1          	   <class 'bool'>
-2023-03-31 23:14:42 - r - INFO: -      load_path      	Train_CartPole-v1_PER_DQN_20230331-225815	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -       show_fig      	         0          	   <class 'bool'>
-2023-03-31 23:14:42 - r - INFO: -       save_fig      	         1          	   <class 'bool'>
-2023-03-31 23:14:42 - r - INFO: -    epsilon_start    	        0.95        	  <class 'float'>
-2023-03-31 23:14:42 - r - INFO: -     epsilon_end     	        0.01        	  <class 'float'>
-2023-03-31 23:14:42 - r - INFO: -    epsilon_decay    	        500         	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -      hidden_dim     	        256         	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -        gamma        	        0.99        	  <class 'float'>
-2023-03-31 23:14:42 - r - INFO: -          lr         	       0.0001       	  <class 'float'>
-2023-03-31 23:14:42 - r - INFO: -     buffer_size     	       100000       	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -      per_alpha      	        0.6         	  <class 'float'>
-2023-03-31 23:14:42 - r - INFO: -       per_beta      	        0.4         	  <class 'float'>
-2023-03-31 23:14:42 - r - INFO: -  per_beta_annealing 	       0.001        	  <class 'float'>
-2023-03-31 23:14:42 - r - INFO: -     per_epsilon     	        0.01        	  <class 'float'>
-2023-03-31 23:14:42 - r - INFO: -      batch_size     	         64         	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -    target_update    	         4          	   <class 'int'>
-2023-03-31 23:14:42 - r - INFO: -     value_layers    	[{'layer_type': 'linear', 'layer_dim': ['n_states', 256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_dim': [256, 256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_dim': [256, 'n_actions'], 'activation': 'none'}]	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -       task_dir      	C:\Users\24438\Desktop\joyrl-offline/tasks/Test_CartPole-v1_PER_DQN_20230331-231442	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -       res_dir       	C:\Users\24438\Desktop\joyrl-offline/tasks/Test_CartPole-v1_PER_DQN_20230331-231442/results	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -       log_dir       	C:\Users\24438\Desktop\joyrl-offline/tasks/Test_CartPole-v1_PER_DQN_20230331-231442/logs	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -       traj_dir      	C:\Users\24438\Desktop\joyrl-offline/tasks/Test_CartPole-v1_PER_DQN_20230331-231442/traj	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: -        tb_dir       	C:\Users\24438\Desktop\joyrl-offline/tasks/Test_CartPole-v1_PER_DQN_20230331-231442/tb_logs	   <class 'str'>
-2023-03-31 23:14:42 - r - INFO: - ================================================================================
-2023-03-31 23:14:42 - r - INFO: - n_states: 4, n_actions: 2
-2023-03-31 23:14:43 - r - INFO: - Start testing!
-2023-03-31 23:14:43 - r - INFO: - Env: CartPole-v1, Algorithm: PER_DQN, Device: cuda
-2023-03-31 23:14:44 - r - INFO: - Episode: 1/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Episode: 2/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Episode: 3/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Episode: 4/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Episode: 5/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Episode: 6/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Episode: 7/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Episode: 8/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Episode: 9/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Episode: 10/10, Reward: 200.000, Step: 200
-2023-03-31 23:14:44 - r - INFO: - Finish testing!

ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/models/checkpoint.pt DELETED Viewed

@@ -1,3 +0,0 @@
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-size 272471

ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/results/learning_curve.png DELETED Viewed

Binary file (26.1 kB)

ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_20230331-231442/results/res.csv DELETED Viewed

@@ -1,11 +0,0 @@
-episodes,rewards,steps
-0,200.0,200
-1,200.0,200
-2,200.0,200
-3,200.0,200
-4,200.0,200
-5,200.0,200
-6,200.0,200
-7,200.0,200
-8,200.0,200
-9,200.0,200

ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_mp_20230415-215147/config.yaml DELETED Viewed

@@ -1,55 +0,0 @@
-general_cfg:
-  algo_name: PER_DQN
-  device: cpu
-  env_name: gym
-  eval_eps: 10
-  eval_per_episode: 5
-  load_checkpoint: true
-  load_path: Train_gym_PER_DQN_20230415-215002
-  max_steps: 200
-  mode: test
-  mp_backend: mp
-  n_workers: 1
-  new_step_api: true
-  render: false
-  render_mode: human
-  save_fig: true
-  seed: 1
-  show_fig: false
-  test_eps: 10
-  train_eps: 200
-  wrapper: null
-algo_cfg:
-  batch_size: 64
-  buffer_size: 100000
-  epsilon_decay: 500
-  epsilon_end: 0.01
-  epsilon_start: 0.95
-  gamma: 0.99
-  hidden_dim: 256
-  lr: 0.0001
-  per_alpha: 0.6
-  per_beta: 0.4
-  per_beta_annealing: 0.001
-  per_epsilon: 0.01
-  target_update: 4
-  value_layers:
-  - activation: relu
-    layer_dim:
-    - n_states
-    - 256
-    layer_type: linear
-  - activation: relu
-    layer_dim:
-    - 256
-    - 256
-    layer_type: linear
-  - activation: none
-    layer_dim:
-    - 256
-    - n_actions
-    layer_type: linear
-env_cfg:
-  id: CartPole-v1
-  new_step_api: true
-  render_mode: null

ClassControl/CartPole-v1/Test_CartPole-v1_PER_DQN_mp_20230415-215147/logs/log.txt DELETED Viewed

@@ -1,58 +0,0 @@
-2023-04-15 21:51:47 - r - INFO: - Hyperparameters:
-2023-04-15 21:51:47 - r - INFO: - ================================================================================
-2023-04-15 21:51:47 - r - INFO: -         Name        	       Value        	        Type
-2023-04-15 21:51:47 - r - INFO: -       env_name      	        gym         	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -     new_step_api    	         1          	   <class 'bool'>
-2023-04-15 21:51:47 - r - INFO: -       wrapper       	        None        	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -        render       	         0          	   <class 'bool'>
-2023-04-15 21:51:47 - r - INFO: -     render_mode     	        None        	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -      algo_name      	      PER_DQN       	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -         mode        	        test        	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -      mp_backend     	         mp         	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -         seed        	         1          	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -        device       	        cpu         	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -      train_eps      	        200         	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -       test_eps      	         10         	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -       eval_eps      	         10         	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -   eval_per_episode  	         5          	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -      max_steps      	        200         	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -   load_checkpoint   	         1          	   <class 'bool'>
-2023-04-15 21:51:47 - r - INFO: -      load_path      	Train_gym_PER_DQN_20230415-215002	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -       show_fig      	         0          	   <class 'bool'>
-2023-04-15 21:51:47 - r - INFO: -       save_fig      	         1          	   <class 'bool'>
-2023-04-15 21:51:47 - r - INFO: -      n_workers      	         1          	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -    epsilon_start    	        0.95        	  <class 'float'>
-2023-04-15 21:51:47 - r - INFO: -     epsilon_end     	        0.01        	  <class 'float'>
-2023-04-15 21:51:47 - r - INFO: -    epsilon_decay    	        500         	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -      hidden_dim     	        256         	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -        gamma        	        0.99        	  <class 'float'>
-2023-04-15 21:51:47 - r - INFO: -          lr         	       0.0001       	  <class 'float'>
-2023-04-15 21:51:47 - r - INFO: -     buffer_size     	       100000       	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -      per_alpha      	        0.6         	  <class 'float'>
-2023-04-15 21:51:47 - r - INFO: -       per_beta      	        0.4         	  <class 'float'>
-2023-04-15 21:51:47 - r - INFO: -  per_beta_annealing 	       0.001        	  <class 'float'>
-2023-04-15 21:51:47 - r - INFO: -     per_epsilon     	        0.01        	  <class 'float'>
-2023-04-15 21:51:47 - r - INFO: -      batch_size     	         64         	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -    target_update    	         4          	   <class 'int'>
-2023-04-15 21:51:47 - r - INFO: -     value_layers    	[{'layer_type': 'linear', 'layer_dim': ['n_states', 256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_dim': [256, 256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_dim': [256, 'n_actions'], 'activation': 'none'}]	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -          id         	    CartPole-v1     	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -       task_dir      	/media/disk/gsc/joyrl-offline/tasks/Test_gym_PER_DQN_20230415-215147	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -       res_dir       	/media/disk/gsc/joyrl-offline/tasks/Test_gym_PER_DQN_20230415-215147/results	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -       log_dir       	/media/disk/gsc/joyrl-offline/tasks/Test_gym_PER_DQN_20230415-215147/logs	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -       traj_dir      	/media/disk/gsc/joyrl-offline/tasks/Test_gym_PER_DQN_20230415-215147/traj	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: -      video_dir      	/media/disk/gsc/joyrl-offline/tasks/Test_gym_PER_DQN_20230415-215147/videos	   <class 'str'>
-2023-04-15 21:51:47 - r - INFO: - ================================================================================
-2023-04-15 21:51:47 - r - INFO: - n_states: 4, n_actions: 2
-2023-04-15 21:51:47 - r - INFO: - Start testing!
-2023-04-15 21:51:47 - r - INFO: - Env: gym, Algorithm: PER_DQN, Device: cpu
-2023-04-15 21:51:47 - r - INFO: - Episode: 1/10, Reward: 200.000, Step: 200
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-2023-04-15 21:51:47 - r - INFO: - Episode: 10/10, Reward: 200.000, Step: 200
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@@ -1,55 +0,0 @@
-general_cfg:
-  algo_name: PER_DQN
-  device: cpu
-  env_name: gym
-  eval_eps: 10
-  eval_per_episode: 5
-  load_checkpoint: true
-  load_path: Train_CartPole-v1_PER_DQN_ray_20230415-215738
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-    - n_actions
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-env_cfg:
-  id: CartPole-v1
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@@ -1,58 +0,0 @@
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-2023-04-15 22:05:40 - r - INFO: -      batch_size     	         64         	   <class 'int'>
-2023-04-15 22:05:40 - r - INFO: -    target_update    	         4          	   <class 'int'>
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-2023-04-15 22:05:40 - r - INFO: -          id         	    CartPole-v1     	   <class 'str'>
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-2023-04-15 22:05:40 - r - INFO: -      video_dir      	/media/disk/gsc/joyrl-offline/tasks/Test_gym_PER_DQN_20230415-220540/videos	   <class 'str'>
-2023-04-15 22:05:40 - r - INFO: - ================================================================================
-2023-04-15 22:05:40 - r - INFO: - n_states: 4, n_actions: 2
-2023-04-15 22:05:40 - r - INFO: - Start testing!
-2023-04-15 22:05:40 - r - INFO: - Env: gym, Algorithm: PER_DQN, Device: cpu
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-2023-04-15 22:05:41 - r - INFO: - Finish testing!

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ClassControl/CartPole-v1/{Test_single_CartPole-v1_DQN_20230515-211926 → Test_single_CartPole-v1_PER_DQN_20230518-232330}/config.yaml RENAMED Viewed

@@ -1,39 +1,43 @@
 general_cfg:
-  algo_name: DQN
-  collect_traj: true
-  device: cpu
   env_name: gym
   load_checkpoint: true
   load_model_step: best
-  load_path: Train_single_CartPole-v1_DQN_20230515-211721
   max_episode: 10
   max_step: 200
   mode: test
   model_save_fre: 500
   mp_backend: single
-  n_workers: 1
   online_eval: true
   online_eval_episode: 10
-  save_fig: true
   seed: 1
-  show_fig: false
 algo_cfg:
   batch_size: 64
   buffer_size: 100000
-  buffer_type: REPLAY_QUE
-  epsilon_decay: 500
   epsilon_end: 0.01
   epsilon_start: 0.95
-  gamma: 0.95
   lr: 0.0001
   target_update: 4
   value_layers:
   - activation: relu
-    layer_dim:
     - 256
     layer_type: linear
   - activation: relu
-    layer_dim:
     - 256
     layer_type: linear
 env_cfg:
@@ -41,5 +45,5 @@ env_cfg:
   ignore_params:
   - wrapper
   - ignore_params
-  render_mode: rgb_array
   wrapper: null

 general_cfg:
+  algo_name: PER_DQN
+  collect_traj: false
+  device: cuda
   env_name: gym
   load_checkpoint: true
   load_model_step: best
+  load_path: Train_single_CartPole-v1_PER_DQN_20230518-232215
   max_episode: 10
   max_step: 200
   mode: test
   model_save_fre: 500
   mp_backend: single
+  n_learners: 1
+  n_workers: 2
   online_eval: true
   online_eval_episode: 10
   seed: 1
+  share_buffer: true
 algo_cfg:
   batch_size: 64
   buffer_size: 100000
+  buffer_type: PER_QUE
+  epsilon_decay: 1000
   epsilon_end: 0.01
   epsilon_start: 0.95
+  gamma: 0.99
   lr: 0.0001
+  per_alpha: 0.6
+  per_beta: 0.4
+  per_beta_annealing: 0.001
+  per_epsilon: 0.01
   target_update: 4
   value_layers:
   - activation: relu
+    layer_size:
     - 256
     layer_type: linear
   - activation: relu
+    layer_size:
     - 256
     layer_type: linear
 env_cfg:
   ignore_params:
   - wrapper
   - ignore_params
+  render_mode: null
   wrapper: null

ClassControl/CartPole-v1/Test_single_CartPole-v1_PER_DQN_20230518-232330/logs/log.txt ADDED Viewed

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+2023-05-18 23:23:30 - SimpleLog - INFO: -   load_checkpoint   	         1          	   <class 'bool'>
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+2023-05-18 23:23:30 - SimpleLog - INFO: -   load_model_step   	        best        	   <class 'str'>
+2023-05-18 23:23:30 - SimpleLog - INFO: - ================================================================================
+2023-05-18 23:23:30 - SimpleLog - INFO: - Algo Configs:
+2023-05-18 23:23:30 - SimpleLog - INFO: - ================================================================================
+2023-05-18 23:23:30 - SimpleLog - INFO: -         Name        	       Value        	        Type
+2023-05-18 23:23:30 - SimpleLog - INFO: -    epsilon_start    	        0.95        	  <class 'float'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -     epsilon_end     	        0.01        	  <class 'float'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -    epsilon_decay    	        1000        	   <class 'int'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -        gamma        	        0.99        	  <class 'float'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -          lr         	       0.0001       	  <class 'float'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -     buffer_type     	      PER_QUE       	   <class 'str'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -     buffer_size     	       100000       	   <class 'int'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -      per_alpha      	        0.6         	  <class 'float'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -       per_beta      	        0.4         	  <class 'float'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -  per_beta_annealing 	       0.001        	  <class 'float'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -     per_epsilon     	        0.01        	  <class 'float'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -      batch_size     	         64         	   <class 'int'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -    target_update    	         4          	   <class 'int'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -     value_layers    	[{'layer_type': 'linear', 'layer_size': [256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_size': [256], 'activation': 'relu'}]	   <class 'str'>
+2023-05-18 23:23:30 - SimpleLog - INFO: - ================================================================================
+2023-05-18 23:23:30 - SimpleLog - INFO: - Env Configs:
+2023-05-18 23:23:30 - SimpleLog - INFO: - ================================================================================
+2023-05-18 23:23:30 - SimpleLog - INFO: -         Name        	       Value        	        Type
+2023-05-18 23:23:30 - SimpleLog - INFO: -          id         	    CartPole-v1     	   <class 'str'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -     render_mode     	        None        	   <class 'str'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -       wrapper       	        None        	   <class 'str'>
+2023-05-18 23:23:30 - SimpleLog - INFO: -    ignore_params    	['wrapper', 'ignore_params']	   <class 'str'>
+2023-05-18 23:23:30 - SimpleLog - INFO: - ================================================================================
+2023-05-18 23:23:30 - SimpleLog - INFO: - obs_space: Box([-4.8000002e+00 -3.4028235e+38 -4.1887903e-01 -3.4028235e+38], [4.8000002e+00 3.4028235e+38 4.1887903e-01 3.4028235e+38], (4,), float32), n_actions: Discrete(2)
+2023-05-18 23:23:31 - SimpleLog - INFO: - Start testing!
+2023-05-18 23:23:32 - SimpleLog - INFO: - episode: 0, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:32 - SimpleLog - INFO: - episode: 1, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:32 - SimpleLog - INFO: - episode: 2, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:32 - SimpleLog - INFO: - episode: 3, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:32 - SimpleLog - INFO: - episode: 4, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:33 - SimpleLog - INFO: - episode: 5, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:33 - SimpleLog - INFO: - episode: 6, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:33 - SimpleLog - INFO: - episode: 7, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:33 - SimpleLog - INFO: - episode: 8, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:33 - SimpleLog - INFO: - episode: 9, ep_reward: 200.0, ep_step: 200
+2023-05-18 23:23:33 - SimpleLog - INFO: - Finish testing! total time consumed: 2.60s

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ClassControl/CartPole-v1/Train_CartPole-v1_PERQue_DQN_20230331-233749/config.yaml DELETED Viewed

@@ -1,48 +0,0 @@
-general_cfg:
-  algo_name: PER_DQN
-  device: cuda
-  env_name: CartPole-v1
-  eval_eps: 10
-  eval_per_episode: 5
-  load_checkpoint: false
-  load_path: Train_CartPole-v1_PER_DQN
-  max_steps: 200
-  mode: train
-  new_step_api: true
-  render: false
-  save_fig: true
-  seed: 1
-  show_fig: false
-  test_eps: 10
-  train_eps: 200
-  wrapper: null
-algo_cfg:
-  batch_size: 64
-  buffer_size: 100000
-  epsilon_decay: 500
-  epsilon_end: 0.01
-  epsilon_start: 0.95
-  gamma: 0.99
-  hidden_dim: 256
-  lr: 0.0001
-  per_alpha: 0.6
-  per_beta: 0.4
-  per_beta_annealing: 0.001
-  per_epsilon: 0.01
-  target_update: 4
-  value_layers:
-  - activation: relu
-    layer_dim:
-    - n_states
-    - 256
-    layer_type: linear
-  - activation: relu
-    layer_dim:
-    - 256
-    - 256
-    layer_type: linear
-  - activation: none
-    layer_dim:
-    - 256
-    - n_actions
-    layer_type: linear

ClassControl/CartPole-v1/Train_CartPole-v1_PERQue_DQN_20230331-233749/logs/log.txt DELETED Viewed

@@ -1,260 +0,0 @@
-2023-03-31 23:37:49 - r - INFO: - Hyperparameters:
-2023-03-31 23:37:49 - r - INFO: - ================================================================================
-2023-03-31 23:37:49 - r - INFO: -         Name        	       Value        	        Type
-2023-03-31 23:37:49 - r - INFO: -       env_name      	    CartPole-v1     	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -     new_step_api    	         1          	   <class 'bool'>
-2023-03-31 23:37:49 - r - INFO: -       wrapper       	        None        	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -        render       	         0          	   <class 'bool'>
-2023-03-31 23:37:49 - r - INFO: -      algo_name      	      PER_DQN       	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -         mode        	       train        	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -         seed        	         1          	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -        device       	        cuda        	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -      train_eps      	        200         	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -       test_eps      	         10         	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -       eval_eps      	         10         	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -   eval_per_episode  	         5          	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -      max_steps      	        200         	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -   load_checkpoint   	         0          	   <class 'bool'>
-2023-03-31 23:37:49 - r - INFO: -      load_path      	Train_CartPole-v1_PER_DQN	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -       show_fig      	         0          	   <class 'bool'>
-2023-03-31 23:37:49 - r - INFO: -       save_fig      	         1          	   <class 'bool'>
-2023-03-31 23:37:49 - r - INFO: -    epsilon_start    	        0.95        	  <class 'float'>
-2023-03-31 23:37:49 - r - INFO: -     epsilon_end     	        0.01        	  <class 'float'>
-2023-03-31 23:37:49 - r - INFO: -    epsilon_decay    	        500         	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -      hidden_dim     	        256         	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -        gamma        	        0.99        	  <class 'float'>
-2023-03-31 23:37:49 - r - INFO: -          lr         	       0.0001       	  <class 'float'>
-2023-03-31 23:37:49 - r - INFO: -     buffer_size     	       100000       	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -      per_alpha      	        0.6         	  <class 'float'>
-2023-03-31 23:37:49 - r - INFO: -       per_beta      	        0.4         	  <class 'float'>
-2023-03-31 23:37:49 - r - INFO: -  per_beta_annealing 	       0.001        	  <class 'float'>
-2023-03-31 23:37:49 - r - INFO: -     per_epsilon     	        0.01        	  <class 'float'>
-2023-03-31 23:37:49 - r - INFO: -      batch_size     	         64         	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -    target_update    	         4          	   <class 'int'>
-2023-03-31 23:37:49 - r - INFO: -     value_layers    	[{'layer_type': 'linear', 'layer_dim': ['n_states', 256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_dim': [256, 256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_dim': [256, 'n_actions'], 'activation': 'none'}]	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -       task_dir      	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-233749	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -       res_dir       	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-233749/results	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -       log_dir       	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-233749/logs	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -       traj_dir      	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-233749/traj	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: -        tb_dir       	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-233749/tb_logs	   <class 'str'>
-2023-03-31 23:37:49 - r - INFO: - ================================================================================
-2023-03-31 23:37:49 - r - INFO: - n_states: 4, n_actions: 2
-2023-03-31 23:37:50 - r - INFO: - Start training!
-2023-03-31 23:37:50 - r - INFO: - Env: CartPole-v1, Algorithm: PER_DQN, Device: cuda
-2023-03-31 23:37:51 - r - INFO: - Episode: 1/200, Reward: 16.000, Step: 16
-2023-03-31 23:37:51 - r - INFO: - Episode: 2/200, Reward: 15.000, Step: 15
-2023-03-31 23:37:51 - r - INFO: - Episode: 3/200, Reward: 25.000, Step: 25
-2023-03-31 23:37:51 - r - INFO: - Episode: 4/200, Reward: 16.000, Step: 16
-2023-03-31 23:37:51 - r - INFO: - Episode: 5/200, Reward: 20.000, Step: 20
-2023-03-31 23:37:51 - r - INFO: - Current episode 5 has the best eval reward: 9.000
-2023-03-31 23:37:51 - r - INFO: - Episode: 6/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:51 - r - INFO: - Episode: 7/200, Reward: 24.000, Step: 24
-2023-03-31 23:37:51 - r - INFO: - Episode: 8/200, Reward: 20.000, Step: 20
-2023-03-31 23:37:51 - r - INFO: - Episode: 9/200, Reward: 20.000, Step: 20
-2023-03-31 23:37:51 - r - INFO: - Episode: 10/200, Reward: 25.000, Step: 25
-2023-03-31 23:37:51 - r - INFO: - Current episode 10 has the best eval reward: 9.100
-2023-03-31 23:37:51 - r - INFO: - Episode: 11/200, Reward: 9.000, Step: 9
-2023-03-31 23:37:51 - r - INFO: - Episode: 12/200, Reward: 23.000, Step: 23
-2023-03-31 23:37:51 - r - INFO: - Episode: 13/200, Reward: 14.000, Step: 14
-2023-03-31 23:37:51 - r - INFO: - Episode: 14/200, Reward: 12.000, Step: 12
-2023-03-31 23:37:51 - r - INFO: - Episode: 15/200, Reward: 11.000, Step: 11
-2023-03-31 23:37:51 - r - INFO: - Episode: 16/200, Reward: 17.000, Step: 17
-2023-03-31 23:37:51 - r - INFO: - Episode: 17/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:51 - r - INFO: - Episode: 18/200, Reward: 17.000, Step: 17
-2023-03-31 23:37:51 - r - INFO: - Episode: 19/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:51 - r - INFO: - Episode: 20/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:52 - r - INFO: - Episode: 21/200, Reward: 22.000, Step: 22
-2023-03-31 23:37:52 - r - INFO: - Episode: 22/200, Reward: 18.000, Step: 18
-2023-03-31 23:37:52 - r - INFO: - Episode: 23/200, Reward: 13.000, Step: 13
-2023-03-31 23:37:52 - r - INFO: - Episode: 24/200, Reward: 13.000, Step: 13
-2023-03-31 23:37:52 - r - INFO: - Episode: 25/200, Reward: 9.000, Step: 9
-2023-03-31 23:37:52 - r - INFO: - Current episode 25 has the best eval reward: 9.600
-2023-03-31 23:37:52 - r - INFO: - Episode: 26/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:52 - r - INFO: - Episode: 27/200, Reward: 13.000, Step: 13
-2023-03-31 23:37:52 - r - INFO: - Episode: 28/200, Reward: 11.000, Step: 11
-2023-03-31 23:37:52 - r - INFO: - Episode: 29/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:52 - r - INFO: - Episode: 30/200, Reward: 12.000, Step: 12
-2023-03-31 23:37:52 - r - INFO: - Episode: 31/200, Reward: 14.000, Step: 14
-2023-03-31 23:37:52 - r - INFO: - Episode: 32/200, Reward: 11.000, Step: 11
-2023-03-31 23:37:52 - r - INFO: - Episode: 33/200, Reward: 18.000, Step: 18
-2023-03-31 23:37:52 - r - INFO: - Episode: 34/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:52 - r - INFO: - Episode: 35/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:52 - r - INFO: - Episode: 36/200, Reward: 8.000, Step: 8
-2023-03-31 23:37:52 - r - INFO: - Episode: 37/200, Reward: 12.000, Step: 12
-2023-03-31 23:37:52 - r - INFO: - Episode: 38/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:52 - r - INFO: - Episode: 39/200, Reward: 11.000, Step: 11
-2023-03-31 23:37:52 - r - INFO: - Episode: 40/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:53 - r - INFO: - Episode: 41/200, Reward: 9.000, Step: 9
-2023-03-31 23:37:53 - r - INFO: - Episode: 42/200, Reward: 12.000, Step: 12
-2023-03-31 23:37:53 - r - INFO: - Episode: 43/200, Reward: 9.000, Step: 9
-2023-03-31 23:37:53 - r - INFO: - Episode: 44/200, Reward: 13.000, Step: 13
-2023-03-31 23:37:53 - r - INFO: - Episode: 45/200, Reward: 13.000, Step: 13
-2023-03-31 23:37:53 - r - INFO: - Episode: 46/200, Reward: 12.000, Step: 12
-2023-03-31 23:37:53 - r - INFO: - Episode: 47/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:53 - r - INFO: - Episode: 48/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:53 - r - INFO: - Episode: 49/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:53 - r - INFO: - Episode: 50/200, Reward: 13.000, Step: 13
-2023-03-31 23:37:53 - r - INFO: - Episode: 51/200, Reward: 10.000, Step: 10
-2023-03-31 23:37:53 - r - INFO: - Episode: 52/200, Reward: 15.000, Step: 15
-2023-03-31 23:37:53 - r - INFO: - Episode: 53/200, Reward: 18.000, Step: 18
-2023-03-31 23:37:53 - r - INFO: - Episode: 54/200, Reward: 18.000, Step: 18
-2023-03-31 23:37:53 - r - INFO: - Episode: 55/200, Reward: 16.000, Step: 16
-2023-03-31 23:37:53 - r - INFO: - Current episode 55 has the best eval reward: 28.000
-2023-03-31 23:37:53 - r - INFO: - Episode: 56/200, Reward: 47.000, Step: 47
-2023-03-31 23:37:54 - r - INFO: - Episode: 57/200, Reward: 87.000, Step: 87
-2023-03-31 23:37:54 - r - INFO: - Episode: 58/200, Reward: 20.000, Step: 20
-2023-03-31 23:37:54 - r - INFO: - Episode: 59/200, Reward: 47.000, Step: 47
-2023-03-31 23:37:54 - r - INFO: - Episode: 60/200, Reward: 17.000, Step: 17
-2023-03-31 23:37:54 - r - INFO: - Episode: 61/200, Reward: 37.000, Step: 37
-2023-03-31 23:37:54 - r - INFO: - Episode: 62/200, Reward: 43.000, Step: 43
-2023-03-31 23:37:54 - r - INFO: - Episode: 63/200, Reward: 33.000, Step: 33
-2023-03-31 23:37:55 - r - INFO: - Episode: 64/200, Reward: 18.000, Step: 18
-2023-03-31 23:37:55 - r - INFO: - Episode: 65/200, Reward: 29.000, Step: 29
-2023-03-31 23:37:55 - r - INFO: - Current episode 65 has the best eval reward: 30.700
-2023-03-31 23:37:55 - r - INFO: - Episode: 66/200, Reward: 30.000, Step: 30
-2023-03-31 23:37:55 - r - INFO: - Episode: 67/200, Reward: 23.000, Step: 23
-2023-03-31 23:37:55 - r - INFO: - Episode: 68/200, Reward: 26.000, Step: 26
-2023-03-31 23:37:55 - r - INFO: - Episode: 69/200, Reward: 18.000, Step: 18
-2023-03-31 23:37:55 - r - INFO: - Episode: 70/200, Reward: 20.000, Step: 20
-2023-03-31 23:37:55 - r - INFO: - Episode: 71/200, Reward: 26.000, Step: 26
-2023-03-31 23:37:55 - r - INFO: - Episode: 72/200, Reward: 16.000, Step: 16
-2023-03-31 23:37:55 - r - INFO: - Episode: 73/200, Reward: 23.000, Step: 23
-2023-03-31 23:37:56 - r - INFO: - Episode: 74/200, Reward: 30.000, Step: 30
-2023-03-31 23:37:56 - r - INFO: - Episode: 75/200, Reward: 23.000, Step: 23
-2023-03-31 23:37:56 - r - INFO: - Episode: 76/200, Reward: 26.000, Step: 26
-2023-03-31 23:37:56 - r - INFO: - Episode: 77/200, Reward: 34.000, Step: 34
-2023-03-31 23:37:56 - r - INFO: - Episode: 78/200, Reward: 29.000, Step: 29
-2023-03-31 23:37:56 - r - INFO: - Episode: 79/200, Reward: 32.000, Step: 32
-2023-03-31 23:37:56 - r - INFO: - Episode: 80/200, Reward: 23.000, Step: 23
-2023-03-31 23:37:57 - r - INFO: - Episode: 81/200, Reward: 32.000, Step: 32
-2023-03-31 23:37:57 - r - INFO: - Episode: 82/200, Reward: 72.000, Step: 72
-2023-03-31 23:37:57 - r - INFO: - Episode: 83/200, Reward: 105.000, Step: 105
-2023-03-31 23:37:58 - r - INFO: - Episode: 84/200, Reward: 63.000, Step: 63
-2023-03-31 23:37:58 - r - INFO: - Episode: 85/200, Reward: 119.000, Step: 119
-2023-03-31 23:37:59 - r - INFO: - Current episode 85 has the best eval reward: 86.500
-2023-03-31 23:37:59 - r - INFO: - Episode: 86/200, Reward: 52.000, Step: 52
-2023-03-31 23:37:59 - r - INFO: - Episode: 87/200, Reward: 155.000, Step: 155
-2023-03-31 23:38:00 - r - INFO: - Episode: 88/200, Reward: 79.000, Step: 79
-2023-03-31 23:38:00 - r - INFO: - Episode: 89/200, Reward: 44.000, Step: 44
-2023-03-31 23:38:00 - r - INFO: - Episode: 90/200, Reward: 140.000, Step: 140
-2023-03-31 23:38:01 - r - INFO: - Episode: 91/200, Reward: 86.000, Step: 86
-2023-03-31 23:38:01 - r - INFO: - Episode: 92/200, Reward: 183.000, Step: 183
-2023-03-31 23:38:02 - r - INFO: - Episode: 93/200, Reward: 112.000, Step: 112
-2023-03-31 23:38:03 - r - INFO: - Episode: 94/200, Reward: 190.000, Step: 190
-2023-03-31 23:38:03 - r - INFO: - Episode: 95/200, Reward: 200.000, Step: 200
-2023-03-31 23:38:04 - r - INFO: - Current episode 95 has the best eval reward: 164.200
-2023-03-31 23:38:05 - r - INFO: - Episode: 96/200, Reward: 157.000, Step: 157
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-2023-03-31 23:39:37 - r - INFO: - Current episode 175 has the best eval reward: 200.000
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-2023-03-31 23:39:52 - r - INFO: - Current episode 185 has the best eval reward: 200.000
-2023-03-31 23:39:54 - r - INFO: - Episode: 186/200, Reward: 200.000, Step: 200
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-2023-03-31 23:40:00 - r - INFO: - Current episode 190 has the best eval reward: 200.000
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-2023-03-31 23:40:09 - r - INFO: - Current episode 195 has the best eval reward: 200.000
-2023-03-31 23:40:10 - r - INFO: - Episode: 196/200, Reward: 200.000, Step: 200
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-2023-03-31 23:40:32 - r - INFO: - Current episode 200 has the best eval reward: 200.000
-2023-03-31 23:40:32 - r - INFO: - Finish training!

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-  device: cuda
-  env_name: CartPole-v1
-  eval_eps: 10
-  eval_per_episode: 5
-  load_checkpoint: false
-  load_path: Train_CartPole-v1_PER_DQN
-  max_steps: 200
-  mode: train
-  new_step_api: true
-  render: false
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-  wrapper: null
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-  lr: 0.0001
-  per_alpha: 0.6
-  per_beta: 0.4
-  per_beta_annealing: 0.001
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-  target_update: 4
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@@ -1,267 +0,0 @@
-2023-03-31 22:58:15 - r - INFO: - Hyperparameters:
-2023-03-31 22:58:15 - r - INFO: - ================================================================================
-2023-03-31 22:58:15 - r - INFO: -         Name        	       Value        	        Type
-2023-03-31 22:58:15 - r - INFO: -       env_name      	    CartPole-v1     	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -     new_step_api    	         1          	   <class 'bool'>
-2023-03-31 22:58:15 - r - INFO: -       wrapper       	        None        	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -        render       	         0          	   <class 'bool'>
-2023-03-31 22:58:15 - r - INFO: -      algo_name      	      PER_DQN       	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -         mode        	       train        	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -         seed        	         1          	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -        device       	        cuda        	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -      train_eps      	        200         	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -       test_eps      	         10         	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -       eval_eps      	         10         	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -   eval_per_episode  	         5          	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -      max_steps      	        200         	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -   load_checkpoint   	         0          	   <class 'bool'>
-2023-03-31 22:58:15 - r - INFO: -      load_path      	Train_CartPole-v1_PER_DQN	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -       show_fig      	         0          	   <class 'bool'>
-2023-03-31 22:58:15 - r - INFO: -       save_fig      	         1          	   <class 'bool'>
-2023-03-31 22:58:15 - r - INFO: -    epsilon_start    	        0.95        	  <class 'float'>
-2023-03-31 22:58:15 - r - INFO: -     epsilon_end     	        0.01        	  <class 'float'>
-2023-03-31 22:58:15 - r - INFO: -    epsilon_decay    	        500         	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -      hidden_dim     	        256         	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -        gamma        	        0.99        	  <class 'float'>
-2023-03-31 22:58:15 - r - INFO: -          lr         	       0.0001       	  <class 'float'>
-2023-03-31 22:58:15 - r - INFO: -     buffer_size     	       100000       	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -      per_alpha      	        0.6         	  <class 'float'>
-2023-03-31 22:58:15 - r - INFO: -       per_beta      	        0.4         	  <class 'float'>
-2023-03-31 22:58:15 - r - INFO: -  per_beta_annealing 	       0.001        	  <class 'float'>
-2023-03-31 22:58:15 - r - INFO: -     per_epsilon     	        0.01        	  <class 'float'>
-2023-03-31 22:58:15 - r - INFO: -      batch_size     	         64         	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -    target_update    	         4          	   <class 'int'>
-2023-03-31 22:58:15 - r - INFO: -     value_layers    	[{'layer_type': 'linear', 'layer_dim': ['n_states', 256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_dim': [256, 256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_dim': [256, 'n_actions'], 'activation': 'none'}]	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -       task_dir      	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-225815	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -       res_dir       	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-225815/results	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -       log_dir       	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-225815/logs	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -       traj_dir      	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-225815/traj	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: -        tb_dir       	C:\Users\24438\Desktop\joyrl-offline/tasks/Train_CartPole-v1_PER_DQN_20230331-225815/tb_logs	   <class 'str'>
-2023-03-31 22:58:15 - r - INFO: - ================================================================================
-2023-03-31 22:58:15 - r - INFO: - n_states: 4, n_actions: 2
-2023-03-31 22:58:16 - r - INFO: - Start training!
-2023-03-31 22:58:16 - r - INFO: - Env: CartPole-v1, Algorithm: PER_DQN, Device: cuda
-2023-03-31 22:58:17 - r - INFO: - Episode: 1/200, Reward: 15.000, Step: 15
-2023-03-31 22:58:17 - r - INFO: - Episode: 2/200, Reward: 29.000, Step: 29
-2023-03-31 22:58:17 - r - INFO: - Episode: 3/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:17 - r - INFO: - Episode: 4/200, Reward: 14.000, Step: 14
-2023-03-31 22:58:17 - r - INFO: - Episode: 5/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:17 - r - INFO: - Current episode 5 has the best eval reward: 9.600
-2023-03-31 22:58:17 - r - INFO: - Episode: 6/200, Reward: 39.000, Step: 39
-2023-03-31 22:58:18 - r - INFO: - Episode: 7/200, Reward: 35.000, Step: 35
-2023-03-31 22:58:18 - r - INFO: - Episode: 8/200, Reward: 16.000, Step: 16
-2023-03-31 22:58:18 - r - INFO: - Episode: 9/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:18 - r - INFO: - Episode: 10/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:18 - r - INFO: - Episode: 11/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:18 - r - INFO: - Episode: 12/200, Reward: 34.000, Step: 34
-2023-03-31 22:58:18 - r - INFO: - Episode: 13/200, Reward: 15.000, Step: 15
-2023-03-31 22:58:18 - r - INFO: - Episode: 14/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:18 - r - INFO: - Episode: 15/200, Reward: 9.000, Step: 9
-2023-03-31 22:58:19 - r - INFO: - Episode: 16/200, Reward: 19.000, Step: 19
-2023-03-31 22:58:19 - r - INFO: - Episode: 17/200, Reward: 9.000, Step: 9
-2023-03-31 22:58:19 - r - INFO: - Episode: 18/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:19 - r - INFO: - Episode: 19/200, Reward: 16.000, Step: 16
-2023-03-31 22:58:19 - r - INFO: - Episode: 20/200, Reward: 19.000, Step: 19
-2023-03-31 22:58:19 - r - INFO: - Current episode 20 has the best eval reward: 9.700
-2023-03-31 22:58:19 - r - INFO: - Episode: 21/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:19 - r - INFO: - Episode: 22/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:19 - r - INFO: - Episode: 23/200, Reward: 14.000, Step: 14
-2023-03-31 22:58:19 - r - INFO: - Episode: 24/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:19 - r - INFO: - Episode: 25/200, Reward: 16.000, Step: 16
-2023-03-31 22:58:19 - r - INFO: - Episode: 26/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:19 - r - INFO: - Episode: 27/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:19 - r - INFO: - Episode: 28/200, Reward: 16.000, Step: 16
-2023-03-31 22:58:19 - r - INFO: - Episode: 29/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:20 - r - INFO: - Episode: 30/200, Reward: 16.000, Step: 16
-2023-03-31 22:58:20 - r - INFO: - Episode: 31/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:20 - r - INFO: - Episode: 32/200, Reward: 8.000, Step: 8
-2023-03-31 22:58:20 - r - INFO: - Episode: 33/200, Reward: 8.000, Step: 8
-2023-03-31 22:58:20 - r - INFO: - Episode: 34/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:20 - r - INFO: - Episode: 35/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:20 - r - INFO: - Episode: 36/200, Reward: 9.000, Step: 9
-2023-03-31 22:58:20 - r - INFO: - Episode: 37/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:20 - r - INFO: - Episode: 38/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:20 - r - INFO: - Episode: 39/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:20 - r - INFO: - Episode: 40/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:20 - r - INFO: - Episode: 41/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:20 - r - INFO: - Episode: 42/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:20 - r - INFO: - Episode: 43/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:20 - r - INFO: - Episode: 44/200, Reward: 9.000, Step: 9
-2023-03-31 22:58:20 - r - INFO: - Episode: 45/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:21 - r - INFO: - Current episode 45 has the best eval reward: 10.600
-2023-03-31 22:58:21 - r - INFO: - Episode: 46/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:21 - r - INFO: - Episode: 47/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:21 - r - INFO: - Episode: 48/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:21 - r - INFO: - Episode: 49/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:21 - r - INFO: - Episode: 50/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:21 - r - INFO: - Episode: 51/200, Reward: 18.000, Step: 18
-2023-03-31 22:58:21 - r - INFO: - Episode: 52/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:21 - r - INFO: - Episode: 53/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:21 - r - INFO: - Episode: 54/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:21 - r - INFO: - Episode: 55/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:21 - r - INFO: - Episode: 56/200, Reward: 8.000, Step: 8
-2023-03-31 22:58:21 - r - INFO: - Episode: 57/200, Reward: 16.000, Step: 16
-2023-03-31 22:58:21 - r - INFO: - Episode: 58/200, Reward: 11.000, Step: 11
-2023-03-31 22:58:21 - r - INFO: - Episode: 59/200, Reward: 9.000, Step: 9
-2023-03-31 22:58:22 - r - INFO: - Episode: 60/200, Reward: 9.000, Step: 9
-2023-03-31 22:58:22 - r - INFO: - Episode: 61/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:22 - r - INFO: - Episode: 62/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:22 - r - INFO: - Episode: 63/200, Reward: 9.000, Step: 9
-2023-03-31 22:58:22 - r - INFO: - Episode: 64/200, Reward: 8.000, Step: 8
-2023-03-31 22:58:22 - r - INFO: - Episode: 65/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:22 - r - INFO: - Episode: 66/200, Reward: 9.000, Step: 9
-2023-03-31 22:58:22 - r - INFO: - Episode: 67/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:22 - r - INFO: - Episode: 68/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:22 - r - INFO: - Episode: 69/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:22 - r - INFO: - Episode: 70/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:22 - r - INFO: - Current episode 70 has the best eval reward: 12.500
-2023-03-31 22:58:22 - r - INFO: - Episode: 71/200, Reward: 10.000, Step: 10
-2023-03-31 22:58:22 - r - INFO: - Episode: 72/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:22 - r - INFO: - Episode: 73/200, Reward: 20.000, Step: 20
-2023-03-31 22:58:23 - r - INFO: - Episode: 74/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:23 - r - INFO: - Episode: 75/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:23 - r - INFO: - Current episode 75 has the best eval reward: 13.000
-2023-03-31 22:58:23 - r - INFO: - Episode: 76/200, Reward: 15.000, Step: 15
-2023-03-31 22:58:23 - r - INFO: - Episode: 77/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:23 - r - INFO: - Episode: 78/200, Reward: 19.000, Step: 19
-2023-03-31 22:58:23 - r - INFO: - Episode: 79/200, Reward: 14.000, Step: 14
-2023-03-31 22:58:23 - r - INFO: - Episode: 80/200, Reward: 12.000, Step: 12
-2023-03-31 22:58:23 - r - INFO: - Current episode 80 has the best eval reward: 15.400
-2023-03-31 22:58:23 - r - INFO: - Episode: 81/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:24 - r - INFO: - Episode: 82/200, Reward: 14.000, Step: 14
-2023-03-31 22:58:24 - r - INFO: - Episode: 83/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:24 - r - INFO: - Episode: 84/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:24 - r - INFO: - Episode: 85/200, Reward: 14.000, Step: 14
-2023-03-31 22:58:24 - r - INFO: - Current episode 85 has the best eval reward: 16.000
-2023-03-31 22:58:24 - r - INFO: - Episode: 86/200, Reward: 18.000, Step: 18
-2023-03-31 22:58:24 - r - INFO: - Episode: 87/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:24 - r - INFO: - Episode: 88/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:24 - r - INFO: - Episode: 89/200, Reward: 13.000, Step: 13
-2023-03-31 22:58:25 - r - INFO: - Episode: 90/200, Reward: 21.000, Step: 21
-2023-03-31 22:58:25 - r - INFO: - Current episode 90 has the best eval reward: 18.800
-2023-03-31 22:58:25 - r - INFO: - Episode: 91/200, Reward: 17.000, Step: 17
-2023-03-31 22:58:25 - r - INFO: - Episode: 92/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:25 - r - INFO: - Episode: 93/200, Reward: 16.000, Step: 16
-2023-03-31 22:58:25 - r - INFO: - Episode: 94/200, Reward: 22.000, Step: 22
-2023-03-31 22:58:25 - r - INFO: - Episode: 95/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:26 - r - INFO: - Current episode 95 has the best eval reward: 22.000
-2023-03-31 22:58:26 - r - INFO: - Episode: 96/200, Reward: 14.000, Step: 14
-2023-03-31 22:58:26 - r - INFO: - Episode: 97/200, Reward: 20.000, Step: 20
-2023-03-31 22:58:26 - r - INFO: - Episode: 98/200, Reward: 24.000, Step: 24
-2023-03-31 22:58:26 - r - INFO: - Episode: 99/200, Reward: 21.000, Step: 21
-2023-03-31 22:58:26 - r - INFO: - Episode: 100/200, Reward: 22.000, Step: 22
-2023-03-31 22:58:27 - r - INFO: - Episode: 101/200, Reward: 21.000, Step: 21
-2023-03-31 22:58:27 - r - INFO: - Episode: 102/200, Reward: 19.000, Step: 19
-2023-03-31 22:58:27 - r - INFO: - Episode: 103/200, Reward: 18.000, Step: 18
-2023-03-31 22:58:27 - r - INFO: - Episode: 104/200, Reward: 18.000, Step: 18
-2023-03-31 22:58:27 - r - INFO: - Episode: 105/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:27 - r - INFO: - Episode: 106/200, Reward: 16.000, Step: 16
-2023-03-31 22:58:27 - r - INFO: - Episode: 107/200, Reward: 19.000, Step: 19
-2023-03-31 22:58:28 - r - INFO: - Episode: 108/200, Reward: 18.000, Step: 18
-2023-03-31 22:58:28 - r - INFO: - Episode: 109/200, Reward: 21.000, Step: 21
-2023-03-31 22:58:28 - r - INFO: - Episode: 110/200, Reward: 24.000, Step: 24
-2023-03-31 22:58:28 - r - INFO: - Current episode 110 has the best eval reward: 23.300
-2023-03-31 22:58:28 - r - INFO: - Episode: 111/200, Reward: 24.000, Step: 24
-2023-03-31 22:58:28 - r - INFO: - Episode: 112/200, Reward: 27.000, Step: 27
-2023-03-31 22:58:29 - r - INFO: - Episode: 113/200, Reward: 35.000, Step: 35
-2023-03-31 22:58:29 - r - INFO: - Episode: 114/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:29 - r - INFO: - Episode: 115/200, Reward: 29.000, Step: 29
-2023-03-31 22:58:29 - r - INFO: - Current episode 115 has the best eval reward: 24.100
-2023-03-31 22:58:29 - r - INFO: - Episode: 116/200, Reward: 25.000, Step: 25
-2023-03-31 22:58:29 - r - INFO: - Episode: 117/200, Reward: 20.000, Step: 20
-2023-03-31 22:58:30 - r - INFO: - Episode: 118/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:30 - r - INFO: - Episode: 119/200, Reward: 21.000, Step: 21
-2023-03-31 22:58:30 - r - INFO: - Episode: 120/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:30 - r - INFO: - Current episode 120 has the best eval reward: 24.500
-2023-03-31 22:58:30 - r - INFO: - Episode: 121/200, Reward: 17.000, Step: 17
-2023-03-31 22:58:30 - r - INFO: - Episode: 122/200, Reward: 19.000, Step: 19
-2023-03-31 22:58:30 - r - INFO: - Episode: 123/200, Reward: 19.000, Step: 19
-2023-03-31 22:58:31 - r - INFO: - Episode: 124/200, Reward: 21.000, Step: 21
-2023-03-31 22:58:31 - r - INFO: - Episode: 125/200, Reward: 24.000, Step: 24
-2023-03-31 22:58:31 - r - INFO: - Current episode 125 has the best eval reward: 25.600
-2023-03-31 22:58:31 - r - INFO: - Episode: 126/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:31 - r - INFO: - Episode: 127/200, Reward: 22.000, Step: 22
-2023-03-31 22:58:31 - r - INFO: - Episode: 128/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:31 - r - INFO: - Episode: 129/200, Reward: 22.000, Step: 22
-2023-03-31 22:58:32 - r - INFO: - Episode: 130/200, Reward: 28.000, Step: 28
-2023-03-31 22:58:32 - r - INFO: - Current episode 130 has the best eval reward: 29.800
-2023-03-31 22:58:32 - r - INFO: - Episode: 131/200, Reward: 32.000, Step: 32
-2023-03-31 22:58:32 - r - INFO: - Episode: 132/200, Reward: 35.000, Step: 35
-2023-03-31 22:58:32 - r - INFO: - Episode: 133/200, Reward: 27.000, Step: 27
-2023-03-31 22:58:33 - r - INFO: - Episode: 134/200, Reward: 24.000, Step: 24
-2023-03-31 22:58:33 - r - INFO: - Episode: 135/200, Reward: 37.000, Step: 37
-2023-03-31 22:58:33 - r - INFO: - Current episode 135 has the best eval reward: 35.700
-2023-03-31 22:58:33 - r - INFO: - Episode: 136/200, Reward: 33.000, Step: 33
-2023-03-31 22:58:34 - r - INFO: - Episode: 137/200, Reward: 39.000, Step: 39
-2023-03-31 22:58:34 - r - INFO: - Episode: 138/200, Reward: 24.000, Step: 24
-2023-03-31 22:58:34 - r - INFO: - Episode: 139/200, Reward: 24.000, Step: 24
-2023-03-31 22:58:34 - r - INFO: - Episode: 140/200, Reward: 40.000, Step: 40
-2023-03-31 22:58:35 - r - INFO: - Current episode 140 has the best eval reward: 40.200
-2023-03-31 22:58:35 - r - INFO: - Episode: 141/200, Reward: 31.000, Step: 31
-2023-03-31 22:58:35 - r - INFO: - Episode: 142/200, Reward: 30.000, Step: 30
-2023-03-31 22:58:35 - r - INFO: - Episode: 143/200, Reward: 25.000, Step: 25
-2023-03-31 22:58:35 - r - INFO: - Episode: 144/200, Reward: 23.000, Step: 23
-2023-03-31 22:58:35 - r - INFO: - Episode: 145/200, Reward: 29.000, Step: 29
-2023-03-31 22:58:36 - r - INFO: - Current episode 145 has the best eval reward: 58.500
-2023-03-31 22:58:36 - r - INFO: - Episode: 146/200, Reward: 51.000, Step: 51
-2023-03-31 22:58:37 - r - INFO: - Episode: 147/200, Reward: 73.000, Step: 73
-2023-03-31 22:58:37 - r - INFO: - Episode: 148/200, Reward: 38.000, Step: 38
-2023-03-31 22:58:37 - r - INFO: - Episode: 149/200, Reward: 37.000, Step: 37
-2023-03-31 22:58:37 - r - INFO: - Episode: 150/200, Reward: 32.000, Step: 32
-2023-03-31 22:58:38 - r - INFO: - Episode: 151/200, Reward: 43.000, Step: 43
-2023-03-31 22:58:38 - r - INFO: - Episode: 152/200, Reward: 29.000, Step: 29
-2023-03-31 22:58:38 - r - INFO: - Episode: 153/200, Reward: 33.000, Step: 33
-2023-03-31 22:58:38 - r - INFO: - Episode: 154/200, Reward: 31.000, Step: 31
-2023-03-31 22:58:39 - r - INFO: - Episode: 155/200, Reward: 41.000, Step: 41
-2023-03-31 22:58:39 - r - INFO: - Episode: 156/200, Reward: 79.000, Step: 79
-2023-03-31 22:58:40 - r - INFO: - Episode: 157/200, Reward: 47.000, Step: 47
-2023-03-31 22:58:40 - r - INFO: - Episode: 158/200, Reward: 32.000, Step: 32
-2023-03-31 22:58:40 - r - INFO: - Episode: 159/200, Reward: 36.000, Step: 36
-2023-03-31 22:58:41 - r - INFO: - Episode: 160/200, Reward: 76.000, Step: 76
-2023-03-31 22:58:41 - r - INFO: - Current episode 160 has the best eval reward: 75.000
-2023-03-31 22:58:41 - r - INFO: - Episode: 161/200, Reward: 73.000, Step: 73
-2023-03-31 22:58:42 - r - INFO: - Episode: 162/200, Reward: 59.000, Step: 59
-2023-03-31 22:58:42 - r - INFO: - Episode: 163/200, Reward: 102.000, Step: 102
-2023-03-31 22:58:43 - r - INFO: - Episode: 164/200, Reward: 87.000, Step: 87
-2023-03-31 22:58:44 - r - INFO: - Episode: 165/200, Reward: 94.000, Step: 94
-2023-03-31 22:58:44 - r - INFO: - Current episode 165 has the best eval reward: 143.300
-2023-03-31 22:58:45 - r - INFO: - Episode: 166/200, Reward: 116.000, Step: 116
-2023-03-31 22:58:46 - r - INFO: - Episode: 167/200, Reward: 135.000, Step: 135
-2023-03-31 22:58:47 - r - INFO: - Episode: 168/200, Reward: 140.000, Step: 140
-2023-03-31 22:58:48 - r - INFO: - Episode: 169/200, Reward: 167.000, Step: 167
-2023-03-31 22:58:49 - r - INFO: - Episode: 170/200, Reward: 128.000, Step: 128
-2023-03-31 22:58:50 - r - INFO: - Current episode 170 has the best eval reward: 157.400
-2023-03-31 22:58:51 - r - INFO: - Episode: 171/200, Reward: 200.000, Step: 200
-2023-03-31 22:58:52 - r - INFO: - Episode: 172/200, Reward: 135.000, Step: 135
-2023-03-31 22:58:53 - r - INFO: - Episode: 173/200, Reward: 163.000, Step: 163
-2023-03-31 22:58:54 - r - INFO: - Episode: 174/200, Reward: 180.000, Step: 180
-2023-03-31 22:58:56 - r - INFO: - Episode: 175/200, Reward: 185.000, Step: 185
-2023-03-31 22:58:56 - r - INFO: - Current episode 175 has the best eval reward: 165.700
-2023-03-31 22:58:57 - r - INFO: - Episode: 176/200, Reward: 200.000, Step: 200
-2023-03-31 22:58:59 - r - INFO: - Episode: 177/200, Reward: 200.000, Step: 200
-2023-03-31 22:59:00 - r - INFO: - Episode: 178/200, Reward: 200.000, Step: 200
-2023-03-31 22:59:01 - r - INFO: - Episode: 179/200, Reward: 200.000, Step: 200
-2023-03-31 22:59:03 - r - INFO: - Episode: 180/200, Reward: 200.000, Step: 200
-2023-03-31 22:59:04 - r - INFO: - Current episode 180 has the best eval reward: 200.000
-2023-03-31 22:59:05 - r - INFO: - Episode: 181/200, Reward: 200.000, Step: 200
-2023-03-31 22:59:06 - r - INFO: - Episode: 182/200, Reward: 200.000, Step: 200
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-2023-03-31 22:59:09 - r - INFO: - Episode: 184/200, Reward: 200.000, Step: 200
-2023-03-31 22:59:10 - r - INFO: - Episode: 185/200, Reward: 200.000, Step: 200
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-2023-04-15 21:57:38 - r - INFO: -     render_mode     	        None        	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -      algo_name      	      PER_DQN       	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -         mode        	       train        	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -      mp_backend     	        ray         	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -         seed        	         1          	   <class 'int'>
-2023-04-15 21:57:38 - r - INFO: -        device       	        cpu         	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -      train_eps      	        250         	   <class 'int'>
-2023-04-15 21:57:38 - r - INFO: -       test_eps      	         10         	   <class 'int'>
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-2023-04-15 21:57:38 - r - INFO: -      max_steps      	        200         	   <class 'int'>
-2023-04-15 21:57:38 - r - INFO: -   load_checkpoint   	         0          	   <class 'bool'>
-2023-04-15 21:57:38 - r - INFO: -      load_path      	Train_CartPole-v1_PER_DQN	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -       show_fig      	         0          	   <class 'bool'>
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-2023-04-15 21:57:38 - r - INFO: -      hidden_dim     	        256         	   <class 'int'>
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-2023-04-15 21:57:38 - r - INFO: -      per_alpha      	        0.6         	  <class 'float'>
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-2023-04-15 21:57:38 - r - INFO: -  per_beta_annealing 	       0.001        	  <class 'float'>
-2023-04-15 21:57:38 - r - INFO: -     per_epsilon     	        0.01        	  <class 'float'>
-2023-04-15 21:57:38 - r - INFO: -      batch_size     	         64         	   <class 'int'>
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-2023-04-15 21:57:38 - r - INFO: -          id         	    CartPole-v1     	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -       task_dir      	/media/disk/gsc/joyrl-offline/tasks/Train_gym_PER_DQN_20230415-215738	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -       res_dir       	/media/disk/gsc/joyrl-offline/tasks/Train_gym_PER_DQN_20230415-215738/results	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -       log_dir       	/media/disk/gsc/joyrl-offline/tasks/Train_gym_PER_DQN_20230415-215738/logs	   <class 'str'>
-2023-04-15 21:57:38 - r - INFO: -       traj_dir      	/media/disk/gsc/joyrl-offline/tasks/Train_gym_PER_DQN_20230415-215738/traj	   <class 'str'>
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-2023-04-15 21:57:38 - r - INFO: - ================================================================================
-2023-04-15 21:57:40 - r - INFO: - n_states: 4, n_actions: 2
-2023-04-15 21:57:40 - r - INFO: - Start training!
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ClassControl/CartPole-v1/Train_ray_CartPole-v1_DQN_20230515-221916/config.yaml DELETED Viewed

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-general_cfg:
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-  device: cpu
-  env_name: gym
-  load_checkpoint: false
-  load_model_step: best
-  load_path: Train_single_CartPole-v1_DQN_20230515-211721
-  max_episode: 100
-  max_step: 200
-  mode: train
-  model_save_fre: 500
-  mp_backend: ray
-  n_workers: 2
-  online_eval: true
-  online_eval_episode: 10
-  save_fig: true
-  seed: 1
-  show_fig: false
-algo_cfg:
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-  buffer_size: 100000
-  buffer_type: REPLAY_QUE
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-  epsilon_end: 0.01
-  epsilon_start: 0.95
-  gamma: 0.95
-  lr: 0.0001
-  target_update: 4
-  value_layers:
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-    layer_dim:
-    - 256
-    layer_type: linear
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-    layer_dim:
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-2023-05-15 22:19:16 - SimpleLog - INFO: - General Configs:
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-2023-05-15 22:19:16 - SimpleLog - INFO: -       env_name      	        gym         	   <class 'str'>
-2023-05-15 22:19:16 - SimpleLog - INFO: -      algo_name      	        DQN         	   <class 'str'>
-2023-05-15 22:19:16 - SimpleLog - INFO: -         mode        	       train        	   <class 'str'>
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-2023-05-15 22:19:16 - SimpleLog - INFO: -   load_checkpoint   	         0          	   <class 'bool'>
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-2023-05-15 22:19:16 - SimpleLog - INFO: - ================================================================================
-2023-05-15 22:19:16 - SimpleLog - INFO: - Algo Configs:
-2023-05-15 22:19:16 - SimpleLog - INFO: - ================================================================================
-2023-05-15 22:19:16 - SimpleLog - INFO: -         Name        	       Value        	        Type
-2023-05-15 22:19:16 - SimpleLog - INFO: -    epsilon_start    	        0.95        	  <class 'float'>
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-2023-05-15 22:19:16 - SimpleLog - INFO: -        gamma        	        0.95        	  <class 'float'>
-2023-05-15 22:19:16 - SimpleLog - INFO: -          lr         	       0.0001       	  <class 'float'>
-2023-05-15 22:19:16 - SimpleLog - INFO: -     buffer_size     	       100000       	   <class 'int'>
-2023-05-15 22:19:16 - SimpleLog - INFO: -      batch_size     	         64         	   <class 'int'>
-2023-05-15 22:19:16 - SimpleLog - INFO: -    target_update    	         4          	   <class 'int'>
-2023-05-15 22:19:16 - SimpleLog - INFO: -     value_layers    	[{'layer_type': 'linear', 'layer_dim': [256], 'activation': 'relu'}, {'layer_type': 'linear', 'layer_dim': [256], 'activation': 'relu'}]	   <class 'str'>
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-2023-05-15 22:19:16 - SimpleLog - INFO: - ================================================================================
-2023-05-15 22:19:16 - SimpleLog - INFO: - Env Configs:
-2023-05-15 22:19:16 - SimpleLog - INFO: - ================================================================================
-2023-05-15 22:19:16 - SimpleLog - INFO: -         Name        	       Value        	        Type
-2023-05-15 22:19:16 - SimpleLog - INFO: -          id         	    CartPole-v1     	   <class 'str'>
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-2023-05-15 22:19:24 - RayLog - INFO: - Worker 0 finished episode 0 with reward 12.0 in 12 steps
-2023-05-15 22:19:24 - RayLog - INFO: - Worker 1 finished episode 0 with reward 22.0 in 22 steps
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-2023-05-15 22:19:25 - RayLog - INFO: - Worker 0 finished episode 3 with reward 18.0 in 18 steps
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-2023-05-15 22:19:27 - RayLog - INFO: - Worker 1 finished episode 18 with reward 9.0 in 9 steps
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-2023-05-15 22:19:29 - RayLog - INFO: - Worker 1 finished episode 28 with reward 16.0 in 16 steps
-2023-05-15 22:19:29 - RayLog - INFO: - Worker 0 finished episode 27 with reward 38.0 in 38 steps
-2023-05-15 22:19:29 - RayLog - INFO: - Worker 1 finished episode 29 with reward 11.0 in 11 steps
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-2023-05-15 22:19:30 - RayLog - INFO: - Worker 0 finished episode 32 with reward 14.0 in 14 steps
-2023-05-15 22:19:30 - RayLog - INFO: - Worker 0 finished episode 35 with reward 9.0 in 9 steps
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-2023-05-15 22:19:32 - RayLog - INFO: - update_step: 500, online_eval_reward: 9.000
-2023-05-15 22:19:32 - RayLog - INFO: - current update step obtain a better online_eval_reward: 9.000, save the best model!
-2023-05-15 22:19:32 - RayLog - INFO: - Worker 0 finished episode 36 with reward 11.0 in 11 steps
-2023-05-15 22:19:32 - RayLog - INFO: - Worker 1 finished episode 37 with reward 14.0 in 14 steps
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-2023-05-15 22:19:34 - RayLog - INFO: - Worker 0 finished episode 46 with reward 36.0 in 36 steps
-2023-05-15 22:19:34 - RayLog - INFO: - Worker 1 finished episode 47 with reward 30.0 in 30 steps
-2023-05-15 22:19:34 - RayLog - INFO: - Worker 1 finished episode 49 with reward 19.0 in 19 steps
-2023-05-15 22:19:34 - RayLog - INFO: - Worker 0 finished episode 48 with reward 28.0 in 28 steps
-2023-05-15 22:19:35 - RayLog - INFO: - Worker 1 finished episode 50 with reward 17.0 in 17 steps
-2023-05-15 22:19:35 - RayLog - INFO: - Worker 0 finished episode 51 with reward 28.0 in 28 steps
-2023-05-15 22:19:35 - RayLog - INFO: - Worker 1 finished episode 52 with reward 23.0 in 23 steps
-2023-05-15 22:19:36 - RayLog - INFO: - Worker 0 finished episode 53 with reward 46.0 in 46 steps
-2023-05-15 22:19:36 - RayLog - INFO: - Worker 1 finished episode 54 with reward 37.0 in 37 steps
-2023-05-15 22:19:36 - RayLog - INFO: - Worker 1 finished episode 56 with reward 27.0 in 27 steps
-2023-05-15 22:19:37 - RayLog - INFO: - Worker 0 finished episode 55 with reward 56.0 in 56 steps
-2023-05-15 22:19:37 - RayLog - INFO: - update_step: 1000, online_eval_reward: 94.000
-2023-05-15 22:19:37 - RayLog - INFO: - current update step obtain a better online_eval_reward: 94.000, save the best model!
-2023-05-15 22:19:37 - RayLog - INFO: - Worker 1 finished episode 57 with reward 35.0 in 35 steps
-2023-05-15 22:19:38 - RayLog - INFO: - Worker 1 finished episode 59 with reward 29.0 in 29 steps
-2023-05-15 22:19:38 - RayLog - INFO: - Worker 0 finished episode 58 with reward 65.0 in 65 steps
-2023-05-15 22:19:39 - RayLog - INFO: - Worker 1 finished episode 60 with reward 37.0 in 37 steps
-2023-05-15 22:19:39 - RayLog - INFO: - Worker 1 finished episode 62 with reward 34.0 in 34 steps
-2023-05-15 22:19:40 - RayLog - INFO: - Worker 0 finished episode 61 with reward 70.0 in 70 steps
-2023-05-15 22:19:40 - RayLog - INFO: - Worker 1 finished episode 63 with reward 39.0 in 39 steps
-2023-05-15 22:19:41 - RayLog - INFO: - Worker 1 finished episode 65 with reward 35.0 in 35 steps
-2023-05-15 22:19:41 - RayLog - INFO: - Worker 0 finished episode 64 with reward 55.0 in 55 steps
-2023-05-15 22:19:42 - RayLog - INFO: - Worker 1 finished episode 66 with reward 37.0 in 37 steps
-2023-05-15 22:19:42 - RayLog - INFO: - Worker 0 finished episode 67 with reward 53.0 in 53 steps
-2023-05-15 22:19:42 - RayLog - INFO: - Worker 1 finished episode 68 with reward 32.0 in 32 steps
-2023-05-15 22:19:42 - RayLog - INFO: - update_step: 1500, online_eval_reward: 57.000
-2023-05-15 22:19:43 - RayLog - INFO: - Worker 1 finished episode 70 with reward 51.0 in 51 steps
-2023-05-15 22:19:44 - RayLog - INFO: - Worker 0 finished episode 69 with reward 67.0 in 67 steps
-2023-05-15 22:19:44 - RayLog - INFO: - Worker 1 finished episode 71 with reward 40.0 in 40 steps
-2023-05-15 22:19:45 - RayLog - INFO: - Worker 0 finished episode 72 with reward 68.0 in 68 steps
-2023-05-15 22:19:46 - RayLog - INFO: - Worker 1 finished episode 73 with reward 79.0 in 79 steps
-2023-05-15 22:19:48 - RayLog - INFO: - update_step: 2000, online_eval_reward: 138.000
-2023-05-15 22:19:48 - RayLog - INFO: - current update step obtain a better online_eval_reward: 138.000, save the best model!
-2023-05-15 22:19:48 - RayLog - INFO: - Worker 0 finished episode 74 with reward 124.0 in 124 steps
-2023-05-15 22:19:49 - RayLog - INFO: - Worker 1 finished episode 75 with reward 133.0 in 133 steps
-2023-05-15 22:19:52 - RayLog - INFO: - Worker 0 finished episode 76 with reward 200.0 in 200 steps
-2023-05-15 22:19:53 - RayLog - INFO: - update_step: 2500, online_eval_reward: 200.000
-2023-05-15 22:19:53 - RayLog - INFO: - current update step obtain a better online_eval_reward: 200.000, save the best model!
-2023-05-15 22:19:53 - RayLog - INFO: - Worker 1 finished episode 77 with reward 200.0 in 200 steps
-2023-05-15 22:19:56 - RayLog - INFO: - Worker 0 finished episode 78 with reward 187.0 in 187 steps
-2023-05-15 22:19:57 - RayLog - INFO: - Worker 1 finished episode 79 with reward 200.0 in 200 steps
-2023-05-15 22:19:58 - RayLog - INFO: - update_step: 3000, online_eval_reward: 200.000
-2023-05-15 22:20:00 - RayLog - INFO: - Worker 0 finished episode 80 with reward 200.0 in 200 steps
-2023-05-15 22:20:02 - RayLog - INFO: - Worker 1 finished episode 81 with reward 200.0 in 200 steps
-2023-05-15 22:20:04 - RayLog - INFO: - update_step: 3500, online_eval_reward: 165.000
-2023-05-15 22:20:04 - RayLog - INFO: - Worker 0 finished episode 82 with reward 200.0 in 200 steps
-2023-05-15 22:20:06 - RayLog - INFO: - Worker 1 finished episode 83 with reward 200.0 in 200 steps
-2023-05-15 22:20:08 - RayLog - INFO: - Worker 0 finished episode 84 with reward 200.0 in 200 steps
-2023-05-15 22:20:09 - RayLog - INFO: - update_step: 4000, online_eval_reward: 200.000
-2023-05-15 22:20:10 - RayLog - INFO: - Worker 1 finished episode 85 with reward 200.0 in 200 steps
-2023-05-15 22:20:12 - RayLog - INFO: - Worker 0 finished episode 86 with reward 200.0 in 200 steps
-2023-05-15 22:20:14 - RayLog - INFO: - update_step: 4500, online_eval_reward: 200.000
-2023-05-15 22:20:14 - RayLog - INFO: - Worker 1 finished episode 87 with reward 200.0 in 200 steps
-2023-05-15 22:20:16 - RayLog - INFO: - Worker 0 finished episode 88 with reward 200.0 in 200 steps
-2023-05-15 22:20:18 - RayLog - INFO: - Worker 1 finished episode 89 with reward 200.0 in 200 steps
-2023-05-15 22:20:19 - RayLog - INFO: - update_step: 5000, online_eval_reward: 200.000
-2023-05-15 22:20:20 - RayLog - INFO: - Worker 0 finished episode 90 with reward 200.0 in 200 steps
-2023-05-15 22:20:22 - RayLog - INFO: - Worker 1 finished episode 91 with reward 200.0 in 200 steps
-2023-05-15 22:20:24 - RayLog - INFO: - update_step: 5500, online_eval_reward: 200.000
-2023-05-15 22:20:24 - RayLog - INFO: - Worker 0 finished episode 92 with reward 200.0 in 200 steps
-2023-05-15 22:20:26 - RayLog - INFO: - Worker 1 finished episode 93 with reward 200.0 in 200 steps
-2023-05-15 22:20:28 - RayLog - INFO: - Worker 0 finished episode 94 with reward 200.0 in 200 steps
-2023-05-15 22:20:29 - RayLog - INFO: - update_step: 6000, online_eval_reward: 200.000
-2023-05-15 22:20:30 - RayLog - INFO: - Worker 1 finished episode 95 with reward 200.0 in 200 steps
-2023-05-15 22:20:32 - RayLog - INFO: - Worker 0 finished episode 96 with reward 200.0 in 200 steps
-2023-05-15 22:20:34 - RayLog - INFO: - update_step: 6500, online_eval_reward: 200.000
-2023-05-15 22:20:34 - RayLog - INFO: - Worker 1 finished episode 97 with reward 200.0 in 200 steps
-2023-05-15 22:20:37 - RayLog - INFO: - Worker 0 finished episode 98 with reward 200.0 in 200 steps
-2023-05-15 22:20:38 - RayLog - INFO: - Worker 1 finished episode 99 with reward 200.0 in 200 steps
-2023-05-15 22:20:40 - RayLog - INFO: - update_step: 7000, online_eval_reward: 200.000
-2023-05-15 22:20:40 - RayLog - INFO: - Worker 0 finished episode 100 with reward 200.0 in 200 steps
-2023-05-15 22:20:43 - SimpleLog - INFO: - Finish training! total time consumed: 87.42s

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