araffin commited on
Commit
b9ea552
1 Parent(s): 15283aa

Initial commit

Browse files
.gitattributes CHANGED
@@ -25,3 +25,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
25
  *.zip filter=lfs diff=lfs merge=lfs -text
26
  *.zstandard filter=lfs diff=lfs merge=lfs -text
27
  *tfevents* filter=lfs diff=lfs merge=lfs -text
28
+ *.mp4 filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,67 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - Walker2DBulletEnv-v0
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: 1495.73 +/- 612.27
14
+ name: mean_reward
15
+ task:
16
+ type: reinforcement-learning
17
+ name: reinforcement-learning
18
+ dataset:
19
+ name: Walker2DBulletEnv-v0
20
+ type: Walker2DBulletEnv-v0
21
+ ---
22
+
23
+ # **DDPG** Agent playing **Walker2DBulletEnv-v0**
24
+ This is a trained model of a **DDPG** agent playing **Walker2DBulletEnv-v0**
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 Walker2DBulletEnv-v0 -orga sb3 -f logs/
41
+ python enjoy.py --algo ddpg --env Walker2DBulletEnv-v0 -f logs/
42
+ ```
43
+
44
+ ## Training (with the RL Zoo)
45
+ ```
46
+ python train.py --algo ddpg --env Walker2DBulletEnv-v0 -f logs/
47
+ # Upload the model and generate video (when possible)
48
+ python -m utils.push_to_hub --algo ddpg --env Walker2DBulletEnv-v0 -f logs/ -orga sb3
49
+ ```
50
+
51
+ ## Hyperparameters
52
+ ```python
53
+ OrderedDict([('batch_size', 256),
54
+ ('buffer_size', 1000000),
55
+ ('env_wrapper', 'sb3_contrib.common.wrappers.TimeFeatureWrapper'),
56
+ ('gamma', 0.98),
57
+ ('gradient_steps', -1),
58
+ ('learning_rate', 0.0007),
59
+ ('learning_starts', 10000),
60
+ ('n_timesteps', 1000000.0),
61
+ ('noise_std', 0.1),
62
+ ('noise_type', 'normal'),
63
+ ('policy', 'MlpPolicy'),
64
+ ('policy_kwargs', 'dict(net_arch=[400, 300])'),
65
+ ('train_freq', [1, 'episode']),
66
+ ('normalize', False)])
67
+ ```
args.yml ADDED
@@ -0,0 +1,59 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ !!python/object/apply:collections.OrderedDict
2
+ - - - algo
3
+ - ddpg
4
+ - - env
5
+ - Walker2DBulletEnv-v0
6
+ - - env_kwargs
7
+ - null
8
+ - - eval_episodes
9
+ - 10
10
+ - - eval_freq
11
+ - 10000
12
+ - - gym_packages
13
+ - []
14
+ - - hyperparams
15
+ - null
16
+ - - log_folder
17
+ - rl-trained-agents/
18
+ - - log_interval
19
+ - -1
20
+ - - n_evaluations
21
+ - 20
22
+ - - n_jobs
23
+ - 1
24
+ - - n_startup_trials
25
+ - 10
26
+ - - n_timesteps
27
+ - -1
28
+ - - n_trials
29
+ - 10
30
+ - - num_threads
31
+ - -1
32
+ - - optimize_hyperparameters
33
+ - false
34
+ - - pruner
35
+ - median
36
+ - - sampler
37
+ - tpe
38
+ - - save_freq
39
+ - -1
40
+ - - save_replay_buffer
41
+ - false
42
+ - - seed
43
+ - 3648079718
44
+ - - storage
45
+ - null
46
+ - - study_name
47
+ - null
48
+ - - tensorboard_log
49
+ - ''
50
+ - - trained_agent
51
+ - ''
52
+ - - truncate_last_trajectory
53
+ - true
54
+ - - uuid
55
+ - true
56
+ - - vec_env
57
+ - dummy
58
+ - - verbose
59
+ - 1
config.yml ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ !!python/object/apply:collections.OrderedDict
2
+ - - - batch_size
3
+ - 256
4
+ - - buffer_size
5
+ - 1000000
6
+ - - env_wrapper
7
+ - sb3_contrib.common.wrappers.TimeFeatureWrapper
8
+ - - gamma
9
+ - 0.98
10
+ - - gradient_steps
11
+ - -1
12
+ - - learning_rate
13
+ - 0.0007
14
+ - - learning_starts
15
+ - 10000
16
+ - - n_timesteps
17
+ - 1000000.0
18
+ - - noise_std
19
+ - 0.1
20
+ - - noise_type
21
+ - normal
22
+ - - policy
23
+ - MlpPolicy
24
+ - - policy_kwargs
25
+ - dict(net_arch=[400, 300])
26
+ - - train_freq
27
+ - - 1
28
+ - episode
ddpg-Walker2DBulletEnv-v0.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1f2815db16c566d613a465ca63c9aa1f4f3a683375409c6e08507f239101d9ca
3
+ size 4264061
ddpg-Walker2DBulletEnv-v0/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.5.1a8
ddpg-Walker2DBulletEnv-v0/actor.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4fdca4a9d9e2c7f1c472b1b2f98e5d04a32fd46bc3ee40eafe006a8a9c157d17
3
+ size 1056961
ddpg-Walker2DBulletEnv-v0/critic.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8c63da047140b55624cf7298c1a63288b0e6677711e41b9be69f789ee3c304c3
3
+ size 1064129
ddpg-Walker2DBulletEnv-v0/data ADDED
@@ -0,0 +1,125 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7ff2ceb79170>",
8
+ "_build": "<function TD3Policy._build at 0x7ff2ceb79200>",
9
+ "_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7ff2ceb79290>",
10
+ "make_actor": "<function TD3Policy.make_actor at 0x7ff2ceb79320>",
11
+ "make_critic": "<function TD3Policy.make_critic at 0x7ff2ceb793b0>",
12
+ "forward": "<function TD3Policy.forward at 0x7ff2ceb79440>",
13
+ "_predict": "<function TD3Policy._predict at 0x7ff2ceb794d0>",
14
+ "set_training_mode": "<function TD3Policy.set_training_mode at 0x7ff2ceb79560>",
15
+ "__abstractmethods__": "frozenset()",
16
+ "_abc_impl": "<_abc_data object at 0x7ff2ceb771b0>"
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
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf -inf -inf -inf -inf 0.]",
31
+ "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf\n inf inf inf inf 1.]",
32
+ "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 True]",
33
+ "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 True]",
34
+ "_np_random": null,
35
+ "_shape": [
36
+ 23
37
+ ]
38
+ },
39
+ "action_space": {
40
+ ":type:": "<class 'gym.spaces.box.Box'>",
41
+ ":serialized:": "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",
42
+ "dtype": "float32",
43
+ "low": "[-1. -1. -1. -1. -1. -1.]",
44
+ "high": "[1. 1. 1. 1. 1. 1.]",
45
+ "bounded_below": "[ True True True True True True]",
46
+ "bounded_above": "[ True True True True True True]",
47
+ "_np_random": "RandomState(MT19937)",
48
+ "_shape": [
49
+ 6
50
+ ]
51
+ },
52
+ "n_envs": 1,
53
+ "num_timesteps": 1000715,
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:": "gASVVAEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMEU5vcm1hbEFjdGlvbk5vaXNllJOUKYGUfZQojANfbXWUjBVudW1weS5jb3JlLm11bHRpYXJyYXmUjAxfcmVjb25zdHJ1Y3SUk5SMBW51bXB5lIwHbmRhcnJheZSTlEsAhZRDAWKUh5RSlChLAUsGhZRoCYwFZHR5cGWUk5SMAmY4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKJQzAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUdJRijAZfc2lnbWGUaAhoC0sAhZRoDYeUUpQoSwFLBoWUaBWJQzCamZmZmZm5P5qZmZmZmbk/mpmZmZmZuT+amZmZmZm5P5qZmZmZmbk/mpmZmZmZuT+UdJRidWIu",
60
+ "_mu": "[0. 0. 0. 0. 0. 0.]",
61
+ "_sigma": "[0.1 0.1 0.1 0.1 0.1 0.1]"
62
+ },
63
+ "start_time": 1614628008.64267,
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": null,
75
+ "_last_original_obs": {
76
+ ":type:": "<class 'numpy.ndarray'>",
77
+ ":serialized:": "gASV5gAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwFLF4aUaAOMBWR0eXBllJOUjAJmNJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiiUNc70y8vgAAAAAAAIA/PCMQPwAAAABDfLU9AAAAAAptT79aAIA/hoW7uDfePb5lWyS+KPZxP+QCIj9x3RC+kj25PepkIj8iAia92tr1Ppxq574AAAAAAACAP28SgzqUdJRiLg=="
78
+ },
79
+ "_episode_num": 4156,
80
+ "use_sde": false,
81
+ "sde_sample_freq": -1,
82
+ "_current_progress_remaining": -0.0007150000000000212,
83
+ "ep_info_buffer": {
84
+ ":type:": "<class 'collections.deque'>",
85
+ ":serialized:": "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"
86
+ },
87
+ "ep_success_buffer": {
88
+ ":type:": "<class 'collections.deque'>",
89
+ ":serialized:": "gASVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
90
+ },
91
+ "_n_updates": 990723,
92
+ "buffer_size": 1,
93
+ "batch_size": 256,
94
+ "learning_starts": 10000,
95
+ "tau": 0.005,
96
+ "gamma": 0.98,
97
+ "gradient_steps": -1,
98
+ "optimize_memory_usage": false,
99
+ "replay_buffer_class": {
100
+ ":type:": "<class 'abc.ABCMeta'>",
101
+ ":serialized:": "gASVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
102
+ "__module__": "stable_baselines3.common.buffers",
103
+ "__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 :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 ",
104
+ "__init__": "<function ReplayBuffer.__init__ at 0x7ff2ceff6b90>",
105
+ "add": "<function ReplayBuffer.add at 0x7ff2ceff6c20>",
106
+ "sample": "<function ReplayBuffer.sample at 0x7ff2ceb5d7a0>",
107
+ "_get_samples": "<function ReplayBuffer._get_samples at 0x7ff2ceb5d830>",
108
+ "__abstractmethods__": "frozenset()",
109
+ "_abc_impl": "<_abc_data object at 0x7ff2cf04d5d0>"
110
+ },
111
+ "replay_buffer_kwargs": {},
112
+ "train_freq": {
113
+ ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
114
+ ":serialized:": "gASVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"
115
+ },
116
+ "use_sde_at_warmup": false,
117
+ "policy_delay": 1,
118
+ "target_noise_clip": 0.0,
119
+ "target_policy_noise": 0.1,
120
+ "_last_dones": {
121
+ ":type:": "<class 'numpy.ndarray'>",
122
+ ":serialized:": "gASViQAAAAAAAACMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlIwFbnVtcHmUjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwGFlGgDjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYolDAQCUdJRiLg=="
123
+ },
124
+ "remove_time_limit_termination": false
125
+ }
ddpg-Walker2DBulletEnv-v0/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:4499f9bc340e8a4c2850ea69de7b4dc1b92ac6acba2df91c48c26886d4c0d58b
3
+ size 2122397
ddpg-Walker2DBulletEnv-v0/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-Walker2DBulletEnv-v0/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ OS: Linux-5.13.0-44-generic-x86_64-with-debian-bullseye-sid #49~20.04.1-Ubuntu SMP Wed May 18 18:44:28 UTC 2022
2
+ Python: 3.7.10
3
+ Stable-Baselines3: 1.5.1a8
4
+ PyTorch: 1.11.0
5
+ GPU Enabled: True
6
+ Numpy: 1.21.2
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 sha256:7c9404a349e2422202d127ad069467d199a6d0b36b7c9d3631ce08e1e1e48256
3
+ size 982290
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 1495.7306658000002, "std_reward": 612.2714306233482, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-02T22:43:30.045076"}
train_eval_metrics.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1b55a3549375cf02a965e5e3e406bdbb2eb208afbee9f5751341a973a1db02c7
3
+ size 126154