Add files using upload-large-folder tool

training/marl/Airfoil3D-easy-v0/PPO/3/config.yaml

@@ -3,7 +3,7 @@ env_kwargs: {}
 eval_env_kwargs: {}
 seed: 3
 rl_mode: marl
-total_timesteps: 20000
+total_timesteps: 50000.0
 n_eval_steps: 10
 eval_freq: ${eval:${total_timesteps} // ${n_eval_steps}}
 n_eval_episodes: 1
@@ -49,3 +49,10 @@ algorithm:
     device: ${rl_device}
     _init_setup_model: true
 cluster: {}
+test_env_id: ${env_id}
+test_env_kwargs: ${env_kwargs}
+test_rl_mode: ${rl_mode}
+n_test_episodes: 10
+deterministic: true
+save_frames: true
+render_3d: true

training/marl/Airfoil3D-easy-v0/PPO/3/eval_sequence_12000.csv

@@ -0,0 +1,201 @@
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training/marl/Airfoil3D-easy-v0/PPO/3/hydra.yaml

@@ -115,15 +115,14 @@ hydra:
     - env_id=Airfoil3D-easy-v0
     - algorithm=sb3_ppo
     - rl_mode=marl
-    - total_timesteps=20000
     - seed=3
   job:
-    name: train_sb3
+    name: test_sb3
     chdir: true
-    override_dirname: algorithm=sb3_ppo,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=3,total_timesteps=20000
+    override_dirname: algorithm=sb3_ppo,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=3
     id: '0'
     num: 0
-    config_name: train_sb3
+    config_name: test_sb3
     env_set: {}
     env_copy: []
     config:

training/marl/Airfoil3D-easy-v0/PPO/3/multirun.yaml

@@ -115,15 +115,14 @@ hydra:
     - env_id=Airfoil3D-easy-v0
     - algorithm=sb3_ppo
     - rl_mode=marl
-    - total_timesteps=20000
     - seed=3
   job:
-    name: train_sb3
+    name: test_sb3
     chdir: true
-    override_dirname: algorithm=sb3_ppo,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=3,total_timesteps=20000
+    override_dirname: algorithm=sb3_ppo,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=3
     id: ???
     num: ???
-    config_name: train_sb3
+    config_name: test_sb3
     env_set: {}
     env_copy: []
     config:
@@ -167,7 +166,7 @@ env_kwargs: {}
 eval_env_kwargs: {}
 seed: 3
 rl_mode: marl
-total_timesteps: 20000
+total_timesteps: 50000.0
 n_eval_steps: 10
 eval_freq: ${eval:${total_timesteps} // ${n_eval_steps}}
 n_eval_episodes: 1
@@ -213,3 +212,10 @@ algorithm:
     device: ${rl_device}
     _init_setup_model: true
 cluster: {}
+test_env_id: ${env_id}
+test_env_kwargs: ${env_kwargs}
+test_rl_mode: ${rl_mode}
+n_test_episodes: 10
+deterministic: true
+save_frames: true
+render_3d: true

training/marl/Airfoil3D-easy-v0/PPO/3/overrides.yaml

@@ -1,5 +1,4 @@
 - env_id=Airfoil3D-easy-v0
 - algorithm=sb3_ppo
 - rl_mode=marl
-- total_timesteps=20000
 - seed=3

training/marl/Airfoil3D-easy-v0/PPO/3/test/test_eval_episode_0.csv

@@ -0,0 +1,201 @@
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training/marl/Airfoil3D-easy-v0/PPO/4/config.yaml

@@ -3,7 +3,7 @@ env_kwargs: {}
 eval_env_kwargs: {}
 seed: 4
 rl_mode: marl
-total_timesteps: 20000
+total_timesteps: 50000.0
 n_eval_steps: 10
 eval_freq: ${eval:${total_timesteps} // ${n_eval_steps}}
 n_eval_episodes: 1
@@ -49,3 +49,10 @@ algorithm:
     device: ${rl_device}
     _init_setup_model: true
 cluster: {}
+test_env_id: ${env_id}
+test_env_kwargs: ${env_kwargs}
+test_rl_mode: ${rl_mode}
+n_test_episodes: 10
+deterministic: true
+save_frames: true
+render_3d: true

training/marl/Airfoil3D-easy-v0/PPO/4/eval_sequence_12000.csv

@@ -0,0 +1,201 @@
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training/marl/Airfoil3D-easy-v0/PPO/4/hydra.yaml

@@ -115,15 +115,14 @@ hydra:
     - env_id=Airfoil3D-easy-v0
     - algorithm=sb3_ppo
     - rl_mode=marl
-    - total_timesteps=20000
     - seed=4
   job:
-    name: train_sb3
+    name: test_sb3
     chdir: true
-    override_dirname: algorithm=sb3_ppo,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=4,total_timesteps=20000
+    override_dirname: algorithm=sb3_ppo,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=4
     id: '0'
     num: 0
-    config_name: train_sb3
+    config_name: test_sb3
     env_set: {}
     env_copy: []
     config:

training/marl/Airfoil3D-easy-v0/PPO/4/multirun.yaml

@@ -115,15 +115,14 @@ hydra:
     - env_id=Airfoil3D-easy-v0
     - algorithm=sb3_ppo
     - rl_mode=marl
-    - total_timesteps=20000
     - seed=4
   job:
-    name: train_sb3
+    name: test_sb3
     chdir: true
-    override_dirname: algorithm=sb3_ppo,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=4,total_timesteps=20000
+    override_dirname: algorithm=sb3_ppo,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=4
     id: ???
     num: ???
-    config_name: train_sb3
+    config_name: test_sb3
     env_set: {}
     env_copy: []
     config:
@@ -167,7 +166,7 @@ env_kwargs: {}
 eval_env_kwargs: {}
 seed: 4
 rl_mode: marl
-total_timesteps: 20000
+total_timesteps: 50000.0
 n_eval_steps: 10
 eval_freq: ${eval:${total_timesteps} // ${n_eval_steps}}
 n_eval_episodes: 1
@@ -213,3 +212,10 @@ algorithm:
     device: ${rl_device}
     _init_setup_model: true
 cluster: {}
+test_env_id: ${env_id}
+test_env_kwargs: ${env_kwargs}
+test_rl_mode: ${rl_mode}
+n_test_episodes: 10
+deterministic: true
+save_frames: true
+render_3d: true

training/marl/Airfoil3D-easy-v0/PPO/4/overrides.yaml

@@ -1,5 +1,4 @@
 - env_id=Airfoil3D-easy-v0
 - algorithm=sb3_ppo
 - rl_mode=marl
-- total_timesteps=20000
 - seed=4

training/marl/Airfoil3D-easy-v0/PPO/4/test/test_eval_episode_0.csv

@@ -0,0 +1,201 @@
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training/marl/Airfoil3D-easy-v0/SAC/3/config.yaml

@@ -3,7 +3,7 @@ env_kwargs: {}
 eval_env_kwargs: {}
 seed: 3
 rl_mode: marl
-total_timesteps: 20000
+total_timesteps: 50000.0
 n_eval_steps: 10
 eval_freq: ${eval:${total_timesteps} // ${n_eval_steps}}
 n_eval_episodes: 1
@@ -26,7 +26,7 @@ algorithm:
     _target_: stable_baselines3.sac.sac.SAC
     policy: MlpPolicy
     learning_rate: 0.0003
-    buffer_size: 1000000
+    buffer_size: 50000
     learning_starts: 100
     batch_size: 256
     tau: 0.005
@@ -51,3 +51,10 @@ algorithm:
     device: cuda
     _init_setup_model: true
 cluster: {}
+test_env_id: ${env_id}
+test_env_kwargs: ${env_kwargs}
+test_rl_mode: ${rl_mode}
+n_test_episodes: 10
+deterministic: true
+save_frames: true
+render_3d: true

training/marl/Airfoil3D-easy-v0/SAC/3/eval_sequence_10000.csv

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training/marl/Airfoil3D-easy-v0/SAC/3/hydra.yaml

@@ -115,15 +115,14 @@ hydra:
     - env_id=Airfoil3D-easy-v0
     - algorithm=sb3_sac
     - rl_mode=marl
-    - total_timesteps=20000
     - seed=3
   job:
-    name: train_sb3
+    name: test_sb3
     chdir: true
-    override_dirname: algorithm=sb3_sac,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=3,total_timesteps=20000
+    override_dirname: algorithm=sb3_sac,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=3
     id: '0'
     num: 0
-    config_name: train_sb3
+    config_name: test_sb3
     env_set: {}
     env_copy: []
     config:

training/marl/Airfoil3D-easy-v0/SAC/3/multirun.yaml

@@ -115,15 +115,14 @@ hydra:
     - env_id=Airfoil3D-easy-v0
     - algorithm=sb3_sac
     - rl_mode=marl
-    - total_timesteps=20000
     - seed=3
   job:
-    name: train_sb3
+    name: test_sb3
     chdir: true
-    override_dirname: algorithm=sb3_sac,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=3,total_timesteps=20000
+    override_dirname: algorithm=sb3_sac,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=3
     id: ???
     num: ???
-    config_name: train_sb3
+    config_name: test_sb3
     env_set: {}
     env_copy: []
     config:
@@ -167,7 +166,7 @@ env_kwargs: {}
 eval_env_kwargs: {}
 seed: 3
 rl_mode: marl
-total_timesteps: 20000
+total_timesteps: 50000.0
 n_eval_steps: 10
 eval_freq: ${eval:${total_timesteps} // ${n_eval_steps}}
 n_eval_episodes: 1
@@ -190,7 +189,7 @@ algorithm:
     _target_: stable_baselines3.sac.sac.SAC
     policy: MlpPolicy
     learning_rate: 0.0003
-    buffer_size: 1000000
+    buffer_size: 50000
     learning_starts: 100
     batch_size: 256
     tau: 0.005
@@ -215,3 +214,10 @@ algorithm:
     device: cuda
     _init_setup_model: true
 cluster: {}
+test_env_id: ${env_id}
+test_env_kwargs: ${env_kwargs}
+test_rl_mode: ${rl_mode}
+n_test_episodes: 10
+deterministic: true
+save_frames: true
+render_3d: true

training/marl/Airfoil3D-easy-v0/SAC/3/overrides.yaml

@@ -1,5 +1,4 @@
 - env_id=Airfoil3D-easy-v0
 - algorithm=sb3_sac
 - rl_mode=marl
-- total_timesteps=20000
 - seed=3

training/marl/Airfoil3D-easy-v0/SAC/3/test/test_eval_episode_0.csv

@@ -0,0 +1,201 @@
+drag,lift,action_0,action_1,action_2,action_3,action_4,action_5,action_6,action_7,action_8,action_9,action_10,action_11,local_reward,reward
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training/marl/Airfoil3D-easy-v0/SAC/3/training_log.csv

@@ -43,3 +43,69 @@ step,training/mean_reward,training/mean_global_reward,training/mean_drag,trainin
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training/marl/Airfoil3D-easy-v0/SAC/4/config.yaml

@@ -3,7 +3,7 @@ env_kwargs: {}
 eval_env_kwargs: {}
 seed: 4
 rl_mode: marl
-total_timesteps: 20000
+total_timesteps: 50000.0
 n_eval_steps: 10
 eval_freq: ${eval:${total_timesteps} // ${n_eval_steps}}
 n_eval_episodes: 1
@@ -26,7 +26,7 @@ algorithm:
     _target_: stable_baselines3.sac.sac.SAC
     policy: MlpPolicy
     learning_rate: 0.0003
-    buffer_size: 1000000
+    buffer_size: 50000
     learning_starts: 100
     batch_size: 256
     tau: 0.005
@@ -51,3 +51,10 @@ algorithm:
     device: cuda
     _init_setup_model: true
 cluster: {}
+test_env_id: ${env_id}
+test_env_kwargs: ${env_kwargs}
+test_rl_mode: ${rl_mode}
+n_test_episodes: 10
+deterministic: true
+save_frames: true
+render_3d: true

training/marl/Airfoil3D-easy-v0/SAC/4/eval_sequence_12000.csv

@@ -0,0 +1,201 @@
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training/marl/Airfoil3D-easy-v0/SAC/4/hydra.yaml

@@ -115,15 +115,14 @@ hydra:
     - env_id=Airfoil3D-easy-v0
     - algorithm=sb3_sac
     - rl_mode=marl
-    - total_timesteps=20000
     - seed=4
   job:
-    name: train_sb3
+    name: test_sb3
     chdir: true
-    override_dirname: algorithm=sb3_sac,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=4,total_timesteps=20000
+    override_dirname: algorithm=sb3_sac,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=4
     id: '0'
     num: 0
-    config_name: train_sb3
+    config_name: test_sb3
     env_set: {}
     env_copy: []
     config:

training/marl/Airfoil3D-easy-v0/SAC/4/multirun.yaml

@@ -115,15 +115,14 @@ hydra:
     - env_id=Airfoil3D-easy-v0
     - algorithm=sb3_sac
     - rl_mode=marl
-    - total_timesteps=20000
     - seed=4
   job:
-    name: train_sb3
+    name: test_sb3
     chdir: true
-    override_dirname: algorithm=sb3_sac,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=4,total_timesteps=20000
+    override_dirname: algorithm=sb3_sac,env_id=Airfoil3D-easy-v0,rl_mode=marl,seed=4
     id: ???
     num: ???
-    config_name: train_sb3
+    config_name: test_sb3
     env_set: {}
     env_copy: []
     config:
@@ -167,7 +166,7 @@ env_kwargs: {}
 eval_env_kwargs: {}
 seed: 4
 rl_mode: marl
-total_timesteps: 20000
+total_timesteps: 50000.0
 n_eval_steps: 10
 eval_freq: ${eval:${total_timesteps} // ${n_eval_steps}}
 n_eval_episodes: 1
@@ -190,7 +189,7 @@ algorithm:
     _target_: stable_baselines3.sac.sac.SAC
     policy: MlpPolicy
     learning_rate: 0.0003
-    buffer_size: 1000000
+    buffer_size: 50000
     learning_starts: 100
     batch_size: 256
     tau: 0.005
@@ -215,3 +214,10 @@ algorithm:
     device: cuda
     _init_setup_model: true
 cluster: {}
+test_env_id: ${env_id}
+test_env_kwargs: ${env_kwargs}
+test_rl_mode: ${rl_mode}
+n_test_episodes: 10
+deterministic: true
+save_frames: true
+render_3d: true

training/marl/Airfoil3D-easy-v0/SAC/4/overrides.yaml

@@ -1,5 +1,4 @@
 - env_id=Airfoil3D-easy-v0
 - algorithm=sb3_sac
 - rl_mode=marl
-- total_timesteps=20000
 - seed=4

training/marl/Airfoil3D-easy-v0/SAC/4/test/test_eval_episode_0.csv

@@ -0,0 +1,201 @@
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training/marl/Airfoil3D-easy-v0/SAC/4/training_log.csv

@@ -54,3 +54,58 @@ step,training/mean_reward,training/mean_global_reward,training/mean_drag,trainin
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training/marl/Airfoil3D-medium-v0/SAC/0/config.yaml

@@ -0,0 +1,53 @@
+env_id: Airfoil3D-medium-v0
+env_kwargs: {}
+eval_env_kwargs: {}
+seed: 0
+rl_mode: marl
+total_timesteps: 20000
+n_eval_steps: 10
+eval_freq: ${eval:${total_timesteps} // ${n_eval_steps}}
+n_eval_episodes: 1
+continue_training: false
+checkpoint_latest: true
+rl_device: cpu
+eval_callback:
+  _target_: fluidgym.integration.sb3.EvalCallback
+  eval_freq: ${eval_freq}
+  n_eval_episodes: ${n_eval_episodes}
+  use_wandb: ${wandb.enable}
+  checkpoint_latest: ${checkpoint_latest}
+wandb:
+  enable: true
+  entity: safe-autonomous-systems
+  project: jbecktepe-fluidgym
+algorithm:
+  name: SAC
+  obj:
+    _target_: stable_baselines3.sac.sac.SAC
+    policy: MlpPolicy
+    learning_rate: 0.0003
+    buffer_size: 50000
+    learning_starts: 100
+    batch_size: 256
+    tau: 0.005
+    gamma: 0.99
+    train_freq: 1
+    gradient_steps: -1
+    action_noise: null
+    replay_buffer_class: null
+    replay_buffer_kwargs: null
+    optimize_memory_usage: false
+    ent_coef: auto
+    target_update_interval: 1
+    target_entropy: auto
+    use_sde: false
+    sde_sample_freq: -1
+    use_sde_at_warmup: false
+    stats_window_size: 100
+    tensorboard_log: null
+    policy_kwargs: {}
+    verbose: 0
+    seed: ${seed}
+    device: cuda
+    _init_setup_model: true
+cluster: {}