jackoyoungblood commited on
Commit
e2ae392
·
1 Parent(s): 5716f8c

Initial commit

Browse files
.gitattributes CHANGED
@@ -29,3 +29,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
29
  *.zip filter=lfs diff=lfs merge=lfs -text
30
  *.zst filter=lfs diff=lfs merge=lfs -text
31
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
29
  *.zip filter=lfs diff=lfs merge=lfs -text
30
  *.zst filter=lfs diff=lfs merge=lfs -text
31
  *tfevents* filter=lfs diff=lfs merge=lfs -text
32
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,65 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - BipedalWalker-v3
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: DDPG
10
+ results:
11
+ - metrics:
12
+ - type: mean_reward
13
+ value: 287.74 +/- 81.94
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: BipedalWalker-v3
20
+ type: BipedalWalker-v3
21
+ ---
22
+
23
+ # **DDPG** Agent playing **BipedalWalker-v3**
24
+ This is a trained model of a **DDPG** agent playing **BipedalWalker-v3**
25
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
26
+ and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
27
+
28
+ The RL Zoo is a training framework for Stable Baselines3
29
+ reinforcement learning agents,
30
+ with hyperparameter optimization and pre-trained agents included.
31
+
32
+ ## Usage (with SB3 RL Zoo)
33
+
34
+ RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
35
+ SB3: https://github.com/DLR-RM/stable-baselines3<br/>
36
+ SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
37
+
38
+ ```
39
+ # Download model and save it into the logs/ folder
40
+ python -m utils.load_from_hub --algo ddpg --env BipedalWalker-v3 -orga jackoyoungblood -f logs/
41
+ python enjoy.py --algo ddpg --env BipedalWalker-v3 -f logs/
42
+ ```
43
+
44
+ ## Training (with the RL Zoo)
45
+ ```
46
+ python train.py --algo ddpg --env BipedalWalker-v3 -f logs/
47
+ # Upload the model and generate video (when possible)
48
+ python -m utils.push_to_hub --algo ddpg --env BipedalWalker-v3 -f logs/ -orga jackoyoungblood
49
+ ```
50
+
51
+ ## Hyperparameters
52
+ ```python
53
+ OrderedDict([('buffer_size', 200000),
54
+ ('gamma', 0.98),
55
+ ('gradient_steps', -1),
56
+ ('learning_rate', 0.0001),
57
+ ('learning_starts', 10000),
58
+ ('n_timesteps', 1000000.0),
59
+ ('noise_std', 0.1),
60
+ ('noise_type', 'normal'),
61
+ ('policy', 'MlpPolicy'),
62
+ ('policy_kwargs', 'dict(net_arch=[400, 300])'),
63
+ ('train_freq', [1, 'episode']),
64
+ ('normalize', False)])
65
+ ```
args.yml ADDED
@@ -0,0 +1,75 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ !!python/object/apply:collections.OrderedDict
2
+ - - - algo
3
+ - ddpg
4
+ - - device
5
+ - auto
6
+ - - env
7
+ - BipedalWalker-v3
8
+ - - env_kwargs
9
+ - null
10
+ - - eval_episodes
11
+ - 5
12
+ - - eval_freq
13
+ - 25000
14
+ - - gym_packages
15
+ - []
16
+ - - hyperparams
17
+ - null
18
+ - - log_folder
19
+ - logs/
20
+ - - log_interval
21
+ - -1
22
+ - - max_total_trials
23
+ - null
24
+ - - n_eval_envs
25
+ - 1
26
+ - - n_evaluations
27
+ - null
28
+ - - n_jobs
29
+ - 1
30
+ - - n_startup_trials
31
+ - 10
32
+ - - n_timesteps
33
+ - -1
34
+ - - n_trials
35
+ - 500
36
+ - - no_optim_plots
37
+ - false
38
+ - - num_threads
39
+ - -1
40
+ - - optimization_log_path
41
+ - null
42
+ - - optimize_hyperparameters
43
+ - false
44
+ - - pruner
45
+ - median
46
+ - - sampler
47
+ - tpe
48
+ - - save_freq
49
+ - -1
50
+ - - save_replay_buffer
51
+ - false
52
+ - - seed
53
+ - 3246674232
54
+ - - storage
55
+ - null
56
+ - - study_name
57
+ - null
58
+ - - tensorboard_log
59
+ - ''
60
+ - - track
61
+ - false
62
+ - - trained_agent
63
+ - ''
64
+ - - truncate_last_trajectory
65
+ - true
66
+ - - uuid
67
+ - false
68
+ - - vec_env
69
+ - dummy
70
+ - - verbose
71
+ - 1
72
+ - - wandb_entity
73
+ - null
74
+ - - wandb_project_name
75
+ - sb3
config.yml ADDED
@@ -0,0 +1,24 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ !!python/object/apply:collections.OrderedDict
2
+ - - - buffer_size
3
+ - 200000
4
+ - - gamma
5
+ - 0.98
6
+ - - gradient_steps
7
+ - -1
8
+ - - learning_rate
9
+ - 0.0001
10
+ - - learning_starts
11
+ - 10000
12
+ - - n_timesteps
13
+ - 1000000.0
14
+ - - noise_std
15
+ - 0.1
16
+ - - noise_type
17
+ - normal
18
+ - - policy
19
+ - MlpPolicy
20
+ - - policy_kwargs
21
+ - dict(net_arch=[400, 300])
22
+ - - train_freq
23
+ - - 1
24
+ - episode
ddpg-BipedalWalker-v3.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a240b62dfdfa801ca07e11d0e3a6ca89f00ef01eb82b717bd3dcee4696034a5f
3
+ size 4258764
ddpg-BipedalWalker-v3/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.6.0
ddpg-BipedalWalker-v3/actor.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6471271c6e91edad869f4ab0d0db5c3908db0b57e978695739da9a73209960a5
3
+ size 1056879
ddpg-BipedalWalker-v3/critic.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:74ad8027f2b6dfeaf74dfc70e924204790e1768ce78350ae865e5ab70eb3c4ef
3
+ size 1062383
ddpg-BipedalWalker-v3/data ADDED
@@ -0,0 +1,123 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gASVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMCVREM1BvbGljeZSTlC4=",
5
+ "__module__": "stable_baselines3.td3.policies",
6
+ "__doc__": "\n Policy class (with both actor and critic) for TD3.\n\n :param observation_space: Observation space\n :param action_space: Action space\n :param lr_schedule: Learning rate schedule (could be constant)\n :param net_arch: The specification of the policy and value networks.\n :param activation_fn: Activation function\n :param features_extractor_class: Features extractor to use.\n :param features_extractor_kwargs: Keyword arguments\n to pass to the features extractor.\n :param normalize_images: Whether to normalize images or not,\n dividing by 255.0 (True by default)\n :param optimizer_class: The optimizer to use,\n ``th.optim.Adam`` by default\n :param optimizer_kwargs: Additional keyword arguments,\n excluding the learning rate, to pass to the optimizer\n :param n_critics: Number of critic networks to create.\n :param share_features_extractor: Whether to share or not the features extractor\n between the actor and the critic (this saves computation time)\n ",
7
+ "__init__": "<function TD3Policy.__init__ at 0x7f996e3e9290>",
8
+ "_build": "<function TD3Policy._build at 0x7f996e3e9320>",
9
+ "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7f996e3e93b0>",
10
+ "make_actor": "<function TD3Policy.make_actor at 0x7f996e3e9440>",
11
+ "make_critic": "<function TD3Policy.make_critic at 0x7f996e3e94d0>",
12
+ "forward": "<function TD3Policy.forward at 0x7f996e3e9560>",
13
+ "_predict": "<function TD3Policy._predict at 0x7f996e3e95f0>",
14
+ "set_training_mode": "<function TD3Policy.set_training_mode at 0x7f996e3e9680>",
15
+ "__abstractmethods__": "frozenset()",
16
+ "_abc_impl": "<_abc_data object at 0x7f996e3dc450>"
17
+ },
18
+ "verbose": 1,
19
+ "policy_kwargs": {
20
+ "net_arch": [
21
+ 400,
22
+ 300
23
+ ],
24
+ "n_critics": 1
25
+ },
26
+ "observation_space": {
27
+ ":type:": "<class 'gym.spaces.box.Box'>",
28
+ ":serialized:": "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",
29
+ "dtype": "float32",
30
+ "_shape": [
31
+ 24
32
+ ],
33
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
34
+ "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf inf inf]",
35
+ "bounded_below": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]",
36
+ "bounded_above": "[False False False False False False False False False False False False\n False False False False False False False False False False False False]",
37
+ "_np_random": null
38
+ },
39
+ "action_space": {
40
+ ":type:": "<class 'gym.spaces.box.Box'>",
41
+ ":serialized:": "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",
42
+ "dtype": "float32",
43
+ "_shape": [
44
+ 4
45
+ ],
46
+ "low": "[-1. -1. -1. -1.]",
47
+ "high": "[1. 1. 1. 1.]",
48
+ "bounded_below": "[ True True True True]",
49
+ "bounded_above": "[ True True True True]",
50
+ "_np_random": "RandomState(MT19937)"
51
+ },
52
+ "n_envs": 1,
53
+ "num_timesteps": 1000737,
54
+ "_total_timesteps": 1000000,
55
+ "_num_timesteps_at_start": 0,
56
+ "seed": 0,
57
+ "action_noise": {
58
+ ":type:": "<class 'stable_baselines3.common.noise.NormalActionNoise'>",
59
+ ":serialized:": "gASVNAEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMEU5vcm1hbEFjdGlvbk5vaXNllJOUKYGUfZQojANfbXWUjBVudW1weS5jb3JlLm11bHRpYXJyYXmUjAxfcmVjb25zdHJ1Y3SUk5SMBW51bXB5lIwHbmRhcnJheZSTlEsAhZRDAWKUh5RSlChLAUsEhZRoCYwFZHR5cGWUk5SMAmY4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKJQyAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJR0lGKMBl9zaWdtYZRoCGgLSwCFlGgNh5RSlChLAUsEhZRoFYlDIJqZmZmZmbk/mpmZmZmZuT+amZmZmZm5P5qZmZmZmbk/lHSUYnViLg==",
60
+ "_mu": "[0. 0. 0. 0.]",
61
+ "_sigma": "[0.1 0.1 0.1 0.1]"
62
+ },
63
+ "start_time": 1660944672.4608638,
64
+ "learning_rate": {
65
+ ":type:": "<class 'function'>",
66
+ ":serialized:": "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"
67
+ },
68
+ "tensorboard_log": null,
69
+ "lr_schedule": {
70
+ ":type:": "<class 'function'>",
71
+ ":serialized:": "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"
72
+ },
73
+ "_last_obs": null,
74
+ "_last_episode_starts": {
75
+ ":type:": "<class 'numpy.ndarray'>",
76
+ ":serialized:": "gASViQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwGFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDAQGUdJRiLg=="
77
+ },
78
+ "_last_original_obs": {
79
+ ":type:": "<class 'numpy.ndarray'>",
80
+ ":serialized:": "gASV6gAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwFLGIaUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUNgS99NPrYMCrvTwig/klI3PTRpmz6R13+/tOjnvmWRqT4AAAAAPvsTP5H3fz+MRSG/qyqfuAAAAAABZrk+N2W2Pj+utz7kob0+BM7JPh293T7JGPw+lY8ZPySlTD8AAIA/lHSUYi4="
81
+ },
82
+ "_episode_num": 1296,
83
+ "use_sde": false,
84
+ "sde_sample_freq": -1,
85
+ "_current_progress_remaining": -0.0007369999999999877,
86
+ "ep_info_buffer": {
87
+ ":type:": "<class 'collections.deque'>",
88
+ ":serialized:": "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"
89
+ },
90
+ "ep_success_buffer": {
91
+ ":type:": "<class 'collections.deque'>",
92
+ ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
93
+ },
94
+ "_n_updates": 991494,
95
+ "buffer_size": 1,
96
+ "batch_size": 100,
97
+ "learning_starts": 10000,
98
+ "tau": 0.005,
99
+ "gamma": 0.98,
100
+ "gradient_steps": -1,
101
+ "optimize_memory_usage": false,
102
+ "replay_buffer_class": {
103
+ ":type:": "<class 'abc.ABCMeta'>",
104
+ ":serialized:": "gASVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
105
+ "__module__": "stable_baselines3.common.buffers",
106
+ "__doc__": "\n Replay buffer used in off-policy algorithms like SAC/TD3.\n\n :param buffer_size: Max number of element in the buffer\n :param observation_space: Observation space\n :param action_space: Action space\n :param device:\n :param n_envs: Number of parallel environments\n :param optimize_memory_usage: Enable a memory efficient variant\n of the replay buffer which reduces by almost a factor two the memory used,\n at a cost of more complexity.\n See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n Cannot be used in combination with handle_timeout_termination.\n :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n separately and treat the task as infinite horizon task.\n https://github.com/DLR-RM/stable-baselines3/issues/284\n ",
107
+ "__init__": "<function ReplayBuffer.__init__ at 0x7f996e86b7a0>",
108
+ "add": "<function ReplayBuffer.add at 0x7f996e86b830>",
109
+ "sample": "<function ReplayBuffer.sample at 0x7f996e857830>",
110
+ "_get_samples": "<function ReplayBuffer._get_samples at 0x7f996e8578c0>",
111
+ "__abstractmethods__": "frozenset()",
112
+ "_abc_impl": "<_abc_data object at 0x7f996e8d2060>"
113
+ },
114
+ "replay_buffer_kwargs": {},
115
+ "train_freq": {
116
+ ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
117
+ ":serialized:": "gASVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"
118
+ },
119
+ "use_sde_at_warmup": false,
120
+ "policy_delay": 1,
121
+ "target_noise_clip": 0.0,
122
+ "target_policy_noise": 0.1
123
+ }
ddpg-BipedalWalker-v3/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e7e9856c22b707666ff681443d321bd7c899a1a1c24a1f66c43b5d8f0214a9b9
3
+ size 2117597
ddpg-BipedalWalker-v3/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
ddpg-BipedalWalker-v3/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
2
+ Python: 3.7.13
3
+ Stable-Baselines3: 1.6.0
4
+ PyTorch: 1.12.1+cu113
5
+ GPU Enabled: True
6
+ Numpy: 1.21.6
7
+ Gym: 0.21.0
env_kwargs.yml ADDED
@@ -0,0 +1 @@
 
 
1
+ {}
replay.mp4 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b2a05ef1a113beca32bfe37d13b7f670f7600ce1d797bd8df9dcfccbc3a30b9d
3
+ size 454059
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 287.73808399999996, "std_reward": 81.93576291275498, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-20T00:02:52.484796"}
train_eval_metrics.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6d2ef39b516856f6ab003506764248ffdc6f9f0c5fce527e153a1e3493d31e2c
3
+ size 40721