johnjim0816 commited on May 15, 2023

Commit

62e03a2

•

1 Parent(s): 52c5852

add all benchmarks

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Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/config.yaml +40 -0
Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/logs/log.txt +14 -0
Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/models/checkpoint.pt +3 -0
Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/results/learning_curve.png +0 -0
Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/results/res.csv +11 -0
Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/config.yaml +40 -0
Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/logs/log.txt +110 -0
Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/models/checkpoint.pt +3 -0
Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/results/learning_curve.png +0 -0
Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/results/res.csv +101 -0
BipedalWalker-v3/Test_BipedalWalker-v3_DDPG_20230415-184448/config.yaml +30 -0
BipedalWalker-v3/Test_BipedalWalker-v3_DDPG_20230415-184448/logs/log.txt +45 -0
BipedalWalker-v3/Test_BipedalWalker-v3_DDPG_20230415-184448/models/actor_checkpoint.pt +3 -0
BipedalWalker-v3/Test_BipedalWalker-v3_DDPG_20230415-184448/results/learning_curve.png +0 -0
BipedalWalker-v3/Test_BipedalWalker-v3_DDPG_20230415-184448/results/res.csv +4 -0
BipedalWalker-v3/Test_BipedalWalker-v3_DDPG_20230415-184448/videos/video.gif +3 -0
BipedalWalker-v3/Test_gym_SAC_20230416-022652/config.yaml +38 -0
BipedalWalker-v3/Test_gym_SAC_20230416-022652/logs/log.txt +67 -0
BipedalWalker-v3/Test_gym_SAC_20230416-022652/models/checkpoint.pt +3 -0
BipedalWalker-v3/Test_gym_SAC_20230416-022652/results/learning_curve.png +0 -0
BipedalWalker-v3/Test_gym_SAC_20230416-022652/results/res.csv +21 -0
BipedalWalker-v3/Train_BipedalWalker-v3_DDPG_20230414-214211/config.yaml +30 -0
BipedalWalker-v3/Train_BipedalWalker-v3_DDPG_20230414-214211/logs/log.txt +0 -0
BipedalWalker-v3/Train_BipedalWalker-v3_DDPG_20230414-214211/models/actor_checkpoint.pt +3 -0
BipedalWalker-v3/Train_BipedalWalker-v3_DDPG_20230414-214211/results/learning_curve.png +0 -0
BipedalWalker-v3/Train_BipedalWalker-v3_DDPG_20230414-214211/results/res.csv +2001 -0
BipedalWalker-v3/Train_gym_SAC_20230415-140928/config.yaml +38 -0
BipedalWalker-v3/Train_gym_SAC_20230415-140928/logs/log.txt +0 -0
BipedalWalker-v3/Train_gym_SAC_20230415-140928/models/checkpoint.pt +3 -0
BipedalWalker-v3/Train_gym_SAC_20230415-140928/results/learning_curve.png +0 -0
BipedalWalker-v3/Train_gym_SAC_20230415-140928/results/res.csv +2001 -0
Breakout-v4/Test_Breakout-v4_DQN_CNN_20221208-101545/config.yaml +27 -0
Breakout-v4/Test_Breakout-v4_DQN_CNN_20221208-101545/logs/log.txt +53 -0
Breakout-v4/Test_Breakout-v4_DQN_CNN_20221208-101545/models/checkpoint.pt +3 -0
Breakout-v4/Test_Breakout-v4_DQN_CNN_20221208-101545/results/learning_curve.png +0 -0
Breakout-v4/Test_Breakout-v4_DQN_CNN_20221208-101545/results/res.csv +21 -0
Breakout-v4/Test_Breakout-v4_mp_DQN_CNN_20230320-134730/config.yaml +28 -0
Breakout-v4/Test_Breakout-v4_mp_DQN_CNN_20230320-134730/logs/log.txt +49 -0
Breakout-v4/Test_Breakout-v4_mp_DQN_CNN_20230320-134730/models/checkpoint.pt +3 -0
Breakout-v4/Test_Breakout-v4_mp_DQN_CNN_20230320-134730/results/learning_curve.png +0 -0
Breakout-v4/Test_Breakout-v4_mp_DQN_CNN_20230320-134730/results/res.csv +11 -0
Breakout-v4/Test_Breakout-v4_mp_DQN_CNN_20230320-134730/tb_logs/events.out.tfevents.1679291250.ML3090.652699.0 +3 -0
Breakout-v4/Train_Breakout-v4_DQN_CNN_20221207-214917/config.yaml +27 -0
Breakout-v4/Train_Breakout-v4_DQN_CNN_20221207-214917/logs/log.txt +242 -0
Breakout-v4/Train_Breakout-v4_DQN_CNN_20221207-214917/models/checkpoint.pt +3 -0
Breakout-v4/Train_Breakout-v4_DQN_CNN_20221207-214917/results/learning_curve.png +0 -0
Breakout-v4/Train_Breakout-v4_DQN_CNN_20221207-214917/results/res.csv +201 -0
Breakout-v4/Train_Breakout-v4_mp_DQN_CNN_20230320-084801/config.yaml +28 -0
Breakout-v4/Train_Breakout-v4_mp_DQN_CNN_20230320-084801/logs/log.txt +39 -0
Breakout-v4/Train_Breakout-v4_mp_DQN_CNN_20230320-084801/models/checkpoint.pt +3 -0

Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/config.yaml ADDED Viewed

	@@ -0,0 +1,40 @@

+general_cfg:
+  algo_name: DQN
+  device: cuda
+  env_name: Acrobot-v1
+  eval_eps: 10
+  eval_per_episode: 5
+  load_checkpoint: true
+  load_path: Train_Acrobot-v1_DQN_20221122-120436
+  max_steps: 100000
+  mode: test
+  save_fig: true
+  seed: 1
+  show_fig: false
+  test_eps: 10
+  train_eps: 100
+algo_cfg:
+  batch_size: 64
+  buffer_size: 100000
+  epsilon_decay: 500
+  epsilon_end: 0.01
+  epsilon_start: 0.95
+  gamma: 0.95
+  lr: 0.002
+  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

Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/logs/log.txt ADDED Viewed

	@@ -0,0 +1,14 @@

+2022-11-22 12:06:10 - r - INFO: - n_states: 6, n_actions: 3
+2022-11-22 12:06:13 - r - INFO: - Start testing!
+2022-11-22 12:06:13 - r - INFO: - Env: Acrobot-v1, Algorithm: DQN, Device: cuda
+2022-11-22 12:06:13 - r - INFO: - Episode: 1/10, Reward: -90.000, Step: 91
+2022-11-22 12:06:13 - r - INFO: - Episode: 2/10, Reward: -116.000, Step: 117
+2022-11-22 12:06:13 - r - INFO: - Episode: 3/10, Reward: -120.000, Step: 121
+2022-11-22 12:06:13 - r - INFO: - Episode: 4/10, Reward: -110.000, Step: 111
+2022-11-22 12:06:13 - r - INFO: - Episode: 5/10, Reward: -71.000, Step: 72
+2022-11-22 12:06:13 - r - INFO: - Episode: 6/10, Reward: -72.000, Step: 73
+2022-11-22 12:06:13 - r - INFO: - Episode: 7/10, Reward: -96.000, Step: 97
+2022-11-22 12:06:13 - r - INFO: - Episode: 8/10, Reward: -106.000, Step: 107
+2022-11-22 12:06:13 - r - INFO: - Episode: 9/10, Reward: -100.000, Step: 101
+2022-11-22 12:06:13 - r - INFO: - Episode: 10/10, Reward: -87.000, Step: 88
+2022-11-22 12:06:13 - r - INFO: - Finish testing!

Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/models/checkpoint.pt ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:ca574bc347296936e61d7a259d139825d1809a3332b5f9725e5ca72c87efbbfa
+size 275543

Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/results/learning_curve.png ADDED Viewed

Acrobot-v1/Test_Acrobot-v1_DQN_20221122-120610/results/res.csv ADDED Viewed

	@@ -0,0 +1,11 @@

+episodes,rewards,steps
+0,-90.0,91
+1,-116.0,117
+2,-120.0,121
+3,-110.0,111
+4,-71.0,72
+5,-72.0,73
+6,-96.0,97
+7,-106.0,107
+8,-100.0,101
+9,-87.0,88

Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/config.yaml ADDED Viewed

	@@ -0,0 +1,40 @@

+general_cfg:
+  algo_name: DQN
+  device: cuda
+  env_name: Acrobot-v1
+  eval_eps: 10
+  eval_per_episode: 5
+  load_checkpoint: false
+  load_path: Train_CartPole-v1_DQN_20221026-054757
+  max_steps: 200
+  mode: train
+  save_fig: true
+  seed: 1
+  show_fig: false
+  test_eps: 10
+  train_eps: 100
+algo_cfg:
+  batch_size: 64
+  buffer_size: 100000
+  epsilon_decay: 500
+  epsilon_end: 0.01
+  epsilon_start: 0.95
+  gamma: 0.99
+  lr: 0.0001
+  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

Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/logs/log.txt ADDED Viewed

	@@ -0,0 +1,110 @@

+2022-11-22 12:04:36 - r - INFO: - n_states: 6, n_actions: 3
+2022-11-22 12:04:39 - r - INFO: - Start training!
+2022-11-22 12:04:39 - r - INFO: - Env: Acrobot-v1, Algorithm: DQN, Device: cuda
+2022-11-22 12:04:39 - r - INFO: - Episode: 1/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:40 - r - INFO: - Episode: 2/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:40 - r - INFO: - Episode: 3/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:40 - r - INFO: - Episode: 4/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:41 - r - INFO: - Episode: 5/100, Reward: -189.000, Step: 190
+2022-11-22 12:04:41 - r - INFO: - Current episode 5 has the best eval reward: -200.000
+2022-11-22 12:04:42 - r - INFO: - Episode: 6/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:42 - r - INFO: - Episode: 7/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:42 - r - INFO: - Episode: 8/100, Reward: -132.000, Step: 133
+2022-11-22 12:04:43 - r - INFO: - Episode: 9/100, Reward: -101.000, Step: 102
+2022-11-22 12:04:43 - r - INFO: - Episode: 10/100, Reward: -148.000, Step: 149
+2022-11-22 12:04:44 - r - INFO: - Current episode 10 has the best eval reward: -200.000
+2022-11-22 12:04:44 - r - INFO: - Episode: 11/100, Reward: -188.000, Step: 189
+2022-11-22 12:04:44 - r - INFO: - Episode: 12/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:45 - r - INFO: - Episode: 13/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:45 - r - INFO: - Episode: 14/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:45 - r - INFO: - Episode: 15/100, Reward: -181.000, Step: 182
+2022-11-22 12:04:46 - r - INFO: - Current episode 15 has the best eval reward: -193.900
+2022-11-22 12:04:46 - r - INFO: - Episode: 16/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:47 - r - INFO: - Episode: 17/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:47 - r - INFO: - Episode: 18/100, Reward: -184.000, Step: 185
+2022-11-22 12:04:47 - r - INFO: - Episode: 19/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:48 - r - INFO: - Episode: 20/100, Reward: -180.000, Step: 181
+2022-11-22 12:04:48 - r - INFO: - Current episode 20 has the best eval reward: -151.000
+2022-11-22 12:04:49 - r - INFO: - Episode: 21/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:49 - r - INFO: - Episode: 22/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:49 - r - INFO: - Episode: 23/100, Reward: -139.000, Step: 140
+2022-11-22 12:04:50 - r - INFO: - Episode: 24/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:50 - r - INFO: - Episode: 25/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:51 - r - INFO: - Episode: 26/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:51 - r - INFO: - Episode: 27/100, Reward: -159.000, Step: 160
+2022-11-22 12:04:52 - r - INFO: - Episode: 28/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:52 - r - INFO: - Episode: 29/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:52 - r - INFO: - Episode: 30/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:53 - r - INFO: - Episode: 31/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:54 - r - INFO: - Episode: 32/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:54 - r - INFO: - Episode: 33/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:55 - r - INFO: - Episode: 34/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:55 - r - INFO: - Episode: 35/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:56 - r - INFO: - Episode: 36/100, Reward: -165.000, Step: 166
+2022-11-22 12:04:56 - r - INFO: - Episode: 37/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:57 - r - INFO: - Episode: 38/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:57 - r - INFO: - Episode: 39/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:57 - r - INFO: - Episode: 40/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:58 - r - INFO: - Current episode 40 has the best eval reward: -141.800
+2022-11-22 12:04:58 - r - INFO: - Episode: 41/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:58 - r - INFO: - Episode: 42/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:59 - r - INFO: - Episode: 43/100, Reward: -200.000, Step: 200
+2022-11-22 12:04:59 - r - INFO: - Episode: 44/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:00 - r - INFO: - Episode: 45/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:01 - r - INFO: - Episode: 46/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:01 - r - INFO: - Episode: 47/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:01 - r - INFO: - Episode: 48/100, Reward: -186.000, Step: 187
+2022-11-22 12:05:02 - r - INFO: - Episode: 49/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:02 - r - INFO: - Episode: 50/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:03 - r - INFO: - Episode: 51/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:03 - r - INFO: - Episode: 52/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:04 - r - INFO: - Episode: 53/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:04 - r - INFO: - Episode: 54/100, Reward: -156.000, Step: 157
+2022-11-22 12:05:04 - r - INFO: - Episode: 55/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:05 - r - INFO: - Episode: 56/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:06 - r - INFO: - Episode: 57/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:06 - r - INFO: - Episode: 58/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:06 - r - INFO: - Episode: 59/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:07 - r - INFO: - Episode: 60/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:08 - r - INFO: - Episode: 61/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:08 - r - INFO: - Episode: 62/100, Reward: -191.000, Step: 192
+2022-11-22 12:05:08 - r - INFO: - Episode: 63/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:09 - r - INFO: - Episode: 64/100, Reward: -187.000, Step: 188
+2022-11-22 12:05:09 - r - INFO: - Episode: 65/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:10 - r - INFO: - Episode: 66/100, Reward: -158.000, Step: 159
+2022-11-22 12:05:10 - r - INFO: - Episode: 67/100, Reward: -164.000, Step: 165
+2022-11-22 12:05:11 - r - INFO: - Episode: 68/100, Reward: -134.000, Step: 135
+2022-11-22 12:05:11 - r - INFO: - Episode: 69/100, Reward: -200.000, Step: 200
+2022-11-22 12:05:11 - r - INFO: - Episode: 70/100, Reward: -144.000, Step: 145
+2022-11-22 12:05:12 - r - INFO: - Episode: 71/100, Reward: -193.000, Step: 194
+2022-11-22 12:05:13 - r - INFO: - Episode: 72/100, Reward: -137.000, Step: 138
+2022-11-22 12:05:13 - r - INFO: - Episode: 73/100, Reward: -183.000, Step: 184
+2022-11-22 12:05:13 - r - INFO: - Episode: 74/100, Reward: -141.000, Step: 142
+2022-11-22 12:05:14 - r - INFO: - Episode: 75/100, Reward: -163.000, Step: 164
+2022-11-22 12:05:14 - r - INFO: - Current episode 75 has the best eval reward: -93.500
+2022-11-22 12:05:14 - r - INFO: - Episode: 76/100, Reward: -71.000, Step: 72
+2022-11-22 12:05:14 - r - INFO: - Episode: 77/100, Reward: -71.000, Step: 72
+2022-11-22 12:05:14 - r - INFO: - Episode: 78/100, Reward: -154.000, Step: 155
+2022-11-22 12:05:15 - r - INFO: - Episode: 79/100, Reward: -117.000, Step: 118
+2022-11-22 12:05:15 - r - INFO: - Episode: 80/100, Reward: -175.000, Step: 176
+2022-11-22 12:05:16 - r - INFO: - Episode: 81/100, Reward: -187.000, Step: 188
+2022-11-22 12:05:16 - r - INFO: - Episode: 82/100, Reward: -111.000, Step: 112
+2022-11-22 12:05:16 - r - INFO: - Episode: 83/100, Reward: -86.000, Step: 87
+2022-11-22 12:05:16 - r - INFO: - Episode: 84/100, Reward: -85.000, Step: 86
+2022-11-22 12:05:17 - r - INFO: - Episode: 85/100, Reward: -93.000, Step: 94
+2022-11-22 12:05:17 - r - INFO: - Episode: 86/100, Reward: -131.000, Step: 132
+2022-11-22 12:05:18 - r - INFO: - Episode: 87/100, Reward: -128.000, Step: 129
+2022-11-22 12:05:18 - r - INFO: - Episode: 88/100, Reward: -194.000, Step: 195
+2022-11-22 12:05:18 - r - INFO: - Episode: 89/100, Reward: -93.000, Step: 94
+2022-11-22 12:05:18 - r - INFO: - Episode: 90/100, Reward: -91.000, Step: 92
+2022-11-22 12:05:19 - r - INFO: - Episode: 91/100, Reward: -161.000, Step: 162
+2022-11-22 12:05:19 - r - INFO: - Episode: 92/100, Reward: -103.000, Step: 104
+2022-11-22 12:05:19 - r - INFO: - Episode: 93/100, Reward: -110.000, Step: 111
+2022-11-22 12:05:20 - r - INFO: - Episode: 94/100, Reward: -191.000, Step: 192
+2022-11-22 12:05:20 - r - INFO: - Episode: 95/100, Reward: -70.000, Step: 71
+2022-11-22 12:05:20 - r - INFO: - Episode: 96/100, Reward: -71.000, Step: 72
+2022-11-22 12:05:21 - r - INFO: - Episode: 97/100, Reward: -125.000, Step: 126
+2022-11-22 12:05:21 - r - INFO: - Episode: 98/100, Reward: -109.000, Step: 110
+2022-11-22 12:05:21 - r - INFO: - Episode: 99/100, Reward: -104.000, Step: 105
+2022-11-22 12:05:21 - r - INFO: - Episode: 100/100, Reward: -93.000, Step: 94
+2022-11-22 12:05:22 - r - INFO: - Finish training!

Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/models/checkpoint.pt ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:ca574bc347296936e61d7a259d139825d1809a3332b5f9725e5ca72c87efbbfa
+size 275543

Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/results/learning_curve.png ADDED Viewed

Acrobot-v1/Train_Acrobot-v1_DQN_20221122-120436/results/res.csv ADDED Viewed

	@@ -0,0 +1,101 @@

+episodes,rewards,steps
+0,-200.0,200
+1,-200.0,200
+2,-200.0,200
+3,-200.0,200
+4,-189.0,190
+5,-200.0,200
+6,-200.0,200
+7,-132.0,133
+8,-101.0,102
+9,-148.0,149
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BipedalWalker-v3/Train_gym_SAC_20230415-140928/config.yaml ADDED Viewed

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+env_cfg:
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Breakout-v4/Test_Breakout-v4_DQN_CNN_20221208-101545/config.yaml ADDED Viewed

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+  device: cuda
+  env_name: Breakout-v4
+  eval_eps: 10
+  eval_per_episode: 5
+  load_checkpoint: true
+  load_path: Train_Breakout-v4_DQN_CNN_20221207-214917
+  max_steps: 1000
+  mode: test
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+  seed: 1
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+2022-12-08 10:16:24 - r - INFO: - Episode: 20/20, Reward: 2.000, Step: 1000
+2022-12-08 10:16:24 - r - INFO: - Finish testing!

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Breakout-v4/Test_Breakout-v4_mp_DQN_CNN_20230320-134730/config.yaml ADDED Viewed

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+general_cfg:
+  algo_name: DQN_CNN
+  device: cpu
+  env_name: Breakout-v4
+  eval_eps: 10
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+  load_checkpoint: true
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+  render: false
+  save_fig: true
+  seed: 1
+  show_fig: false
+  test_eps: 10
+  train_eps: 500
+  wrapper: envs.wrappers.MarioWrappers
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+  buffer_size: 100000
+  epsilon_decay: 500
+  epsilon_end: 0.01
+  epsilon_start: 0.95
+  gamma: 0.99
+  lr: 0.0001
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+2023-03-20 13:47:30 - r - INFO: - Hyperparameters:
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+2023-03-20 13:48:04 - r - INFO: - Episode: 10/10, Reward: 6.000, Step: 500
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Breakout-v4/Train_Breakout-v4_DQN_CNN_20221207-214917/config.yaml ADDED Viewed

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+  algo_name: DQN_CNN
+  device: cuda
+  env_name: Breakout-v4
+  eval_eps: 10
+  eval_per_episode: 5
+  load_checkpoint: false
+  load_path: Train_Mario_DQN_CNN_20221205-205203
+  max_steps: 1000
+  mode: train
+  new_step_api: true
+  render: false
+  save_fig: true
+  seed: 1
+  show_fig: false
+  test_eps: 10
+  train_eps: 200
+  wrapper: envs.wrappers.MarioWrappers
+algo_cfg:
+  batch_size: 64
+  buffer_size: 100000
+  epsilon_decay: 500
+  epsilon_end: 0.01
+  epsilon_start: 0.95
+  gamma: 0.99
+  lr: 0.0001
+  target_update: 4

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+2022-12-07 21:49:22 - r - INFO: - Episode: 1/200, Reward: 0.000, Step: 54
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+2022-12-07 21:49:29 - r - INFO: - Episode: 4/200, Reward: 4.000, Step: 110
+2022-12-07 21:49:31 - r - INFO: - Episode: 5/200, Reward: 1.000, Step: 87
+2022-12-07 21:50:08 - r - INFO: - Current episode 5 has the best eval reward: 0.000
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+2022-12-07 21:50:12 - r - INFO: - Episode: 7/200, Reward: 0.000, Step: 73
+2022-12-07 21:50:15 - r - INFO: - Episode: 8/200, Reward: 2.000, Step: 113
+2022-12-07 21:50:18 - r - INFO: - Episode: 9/200, Reward: 2.000, Step: 98
+2022-12-07 21:50:19 - r - INFO: - Episode: 10/200, Reward: 1.000, Step: 57
+2022-12-07 21:50:56 - r - INFO: - Current episode 10 has the best eval reward: 0.000
+2022-12-07 21:51:00 - r - INFO: - Episode: 11/200, Reward: 1.000, Step: 123
+2022-12-07 21:51:02 - r - INFO: - Episode: 12/200, Reward: 1.000, Step: 69
+2022-12-07 21:51:08 - r - INFO: - Episode: 13/200, Reward: 0.000, Step: 235
+2022-12-07 21:51:10 - r - INFO: - Episode: 14/200, Reward: 2.000, Step: 111
+2022-12-07 21:51:13 - r - INFO: - Episode: 15/200, Reward: 0.000, Step: 100
+2022-12-07 21:51:15 - r - INFO: - Current episode 15 has the best eval reward: 0.000
+2022-12-07 21:51:17 - r - INFO: - Episode: 16/200, Reward: 1.000, Step: 87
+2022-12-07 21:51:23 - r - INFO: - Episode: 17/200, Reward: 3.000, Step: 231
+2022-12-07 21:51:26 - r - INFO: - Episode: 18/200, Reward: 2.000, Step: 105
+2022-12-07 21:51:29 - r - INFO: - Episode: 19/200, Reward: 0.000, Step: 113
+2022-12-07 21:51:31 - r - INFO: - Episode: 20/200, Reward: 3.000, Step: 97
+2022-12-07 21:51:33 - r - INFO: - Current episode 20 has the best eval reward: 1.000
+2022-12-07 21:51:35 - r - INFO: - Episode: 21/200, Reward: 1.000, Step: 71
+2022-12-07 21:51:40 - r - INFO: - Episode: 22/200, Reward: 2.000, Step: 161
+2022-12-07 21:51:43 - r - INFO: - Episode: 23/200, Reward: 1.000, Step: 129
+2022-12-07 21:51:45 - r - INFO: - Episode: 24/200, Reward: 1.000, Step: 80
+2022-12-07 21:51:48 - r - INFO: - Episode: 25/200, Reward: 2.000, Step: 91
+2022-12-07 21:52:27 - r - INFO: - Episode: 26/200, Reward: 1.000, Step: 493
+2022-12-07 21:52:34 - r - INFO: - Episode: 27/200, Reward: 1.000, Step: 266
+2022-12-07 21:52:38 - r - INFO: - Episode: 28/200, Reward: 2.000, Step: 140
+2022-12-07 21:52:42 - r - INFO: - Episode: 29/200, Reward: 1.000, Step: 169
+2022-12-07 21:52:46 - r - INFO: - Episode: 30/200, Reward: 2.000, Step: 139
+2022-12-07 21:53:28 - r - INFO: - Episode: 31/200, Reward: 1.000, Step: 175
+2022-12-07 21:53:34 - r - INFO: - Episode: 32/200, Reward: 2.000, Step: 256
+2022-12-07 21:53:41 - r - INFO: - Episode: 33/200, Reward: 0.000, Step: 256
+2022-12-07 21:53:43 - r - INFO: - Episode: 34/200, Reward: 1.000, Step: 70
+2022-12-07 21:53:51 - r - INFO: - Episode: 35/200, Reward: 0.000, Step: 295
+2022-12-07 21:54:43 - r - INFO: - Episode: 36/200, Reward: 0.000, Step: 554
+2022-12-07 21:54:46 - r - INFO: - Episode: 37/200, Reward: 2.000, Step: 126
+2022-12-07 21:54:49 - r - INFO: - Episode: 38/200, Reward: 1.000, Step: 95
+2022-12-07 21:54:51 - r - INFO: - Episode: 39/200, Reward: 1.000, Step: 83
+2022-12-07 21:54:53 - r - INFO: - Episode: 40/200, Reward: 1.000, Step: 89
+2022-12-07 21:55:33 - r - INFO: - Episode: 41/200, Reward: 4.000, Step: 110
+2022-12-07 21:55:35 - r - INFO: - Episode: 42/200, Reward: 2.000, Step: 73
+2022-12-07 21:55:37 - r - INFO: - Episode: 43/200, Reward: 1.000, Step: 72
+2022-12-07 21:55:40 - r - INFO: - Episode: 44/200, Reward: 4.000, Step: 121
+2022-12-07 21:55:43 - r - INFO: - Episode: 45/200, Reward: 2.000, Step: 117
+2022-12-07 21:56:17 - r - INFO: - Current episode 45 has the best eval reward: 1.000
+2022-12-07 21:56:19 - r - INFO: - Episode: 46/200, Reward: 3.000, Step: 74
+2022-12-07 21:56:21 - r - INFO: - Episode: 47/200, Reward: 1.000, Step: 85
+2022-12-07 21:56:25 - r - INFO: - Episode: 48/200, Reward: 2.000, Step: 131
+2022-12-07 21:56:26 - r - INFO: - Episode: 49/200, Reward: 2.000, Step: 66
+2022-12-07 21:56:29 - r - INFO: - Episode: 50/200, Reward: 4.000, Step: 108
+2022-12-07 21:57:09 - r - INFO: - Episode: 51/200, Reward: 2.000, Step: 101
+2022-12-07 21:57:20 - r - INFO: - Episode: 52/200, Reward: 1.000, Step: 406
+2022-12-07 21:57:22 - r - INFO: - Episode: 53/200, Reward: 0.000, Step: 86
+2022-12-07 21:57:24 - r - INFO: - Episode: 54/200, Reward: 4.000, Step: 87
+2022-12-07 21:57:26 - r - INFO: - Episode: 55/200, Reward: 1.000, Step: 66
+2022-12-07 21:58:06 - r - INFO: - Episode: 56/200, Reward: 2.000, Step: 121
+2022-12-07 21:58:08 - r - INFO: - Episode: 57/200, Reward: 3.000, Step: 77
+2022-12-07 21:58:10 - r - INFO: - Episode: 58/200, Reward: 1.000, Step: 79
+2022-12-07 21:58:14 - r - INFO: - Episode: 59/200, Reward: 4.000, Step: 142
+2022-12-07 21:58:16 - r - INFO: - Episode: 60/200, Reward: 1.000, Step: 71
+2022-12-07 21:58:53 - r - INFO: - Episode: 61/200, Reward: 5.000, Step: 126
+2022-12-07 21:58:55 - r - INFO: - Episode: 62/200, Reward: 1.000, Step: 82
+2022-12-07 21:58:58 - r - INFO: - Episode: 63/200, Reward: 3.000, Step: 97
+2022-12-07 21:59:00 - r - INFO: - Episode: 64/200, Reward: 1.000, Step: 63
+2022-12-07 21:59:01 - r - INFO: - Episode: 65/200, Reward: 2.000, Step: 74
+2022-12-07 21:59:42 - r - INFO: - Episode: 66/200, Reward: 5.000, Step: 125
+2022-12-07 21:59:43 - r - INFO: - Episode: 67/200, Reward: 0.000, Step: 55
+2022-12-07 21:59:47 - r - INFO: - Episode: 68/200, Reward: 0.000, Step: 126
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+2022-12-07 22:00:39 - r - INFO: - Episode: 73/200, Reward: 3.000, Step: 76
+2022-12-07 22:00:44 - r - INFO: - Episode: 74/200, Reward: 1.000, Step: 181
+2022-12-07 22:00:54 - r - INFO: - Episode: 75/200, Reward: 5.000, Step: 363
+2022-12-07 22:01:33 - r - INFO: - Episode: 76/200, Reward: 1.000, Step: 68
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+2022-12-07 22:01:51 - r - INFO: - Episode: 78/200, Reward: 4.000, Step: 88
+2022-12-07 22:01:54 - r - INFO: - Episode: 79/200, Reward: 1.000, Step: 120
+2022-12-07 22:01:56 - r - INFO: - Episode: 80/200, Reward: 2.000, Step: 74
+2022-12-07 22:02:35 - r - INFO: - Episode: 81/200, Reward: 1.000, Step: 65
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+2022-12-07 22:03:13 - r - INFO: - Episode: 85/200, Reward: 6.000, Step: 774
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+2022-12-07 22:05:24 - r - INFO: - Episode: 94/200, Reward: 3.000, Step: 94
+2022-12-07 22:05:28 - r - INFO: - Episode: 95/200, Reward: 3.000, Step: 165
+2022-12-07 22:06:11 - r - INFO: - Episode: 96/200, Reward: 3.000, Step: 315
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+  device: cpu
+  env_name: Breakout-v4
+  eval_eps: 10
+  eval_per_episode: 5
+  load_checkpoint: false
+  load_path: Train_Breakout-v4_DQN_CNN_20221207-214917
+  max_steps: 500
+  mode: train
+  n_workers: 4
+  new_step_api: true
+  render: false
+  save_fig: true
+  seed: 1
+  show_fig: false
+  test_eps: 10
+  train_eps: 500
+  wrapper: envs.wrappers.MarioWrappers
+algo_cfg:
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+  buffer_size: 100000
+  epsilon_decay: 500
+  epsilon_end: 0.01
+  epsilon_start: 0.95
+  gamma: 0.99
+  lr: 0.0001
+  target_update: 4

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+2023-03-20 08:48:01 - r - INFO: - ================================================================================
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+2023-03-20 08:48:01 - r - INFO: -       traj_dir      	/media/disk/gsc/joyrl-offline/tasks/Train_Breakout-v4_DQN_CNN_20230320-084801/traj	   <class 'str'>
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+2023-03-20 08:48:01 - r - INFO: - ================================================================================
+2023-03-20 08:48:02 - r - INFO: - n_states: 4, n_actions: 4
+2023-03-20 08:48:02 - r - INFO: - Start training!
+2023-03-20 08:48:02 - r - INFO: - Env: Breakout-v4, Algorithm: DQN_CNN, Device: cpu
+2023-03-20 12:32:55 - r - INFO: - Finish training!

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