Initial commit
Browse files- .gitattributes +1 -0
- README.md +72 -0
- args.yml +81 -0
- config.yml +24 -0
- ddpg-BipedalWalker-v3.zip +3 -0
- ddpg-BipedalWalker-v3/_stable_baselines3_version +1 -0
- ddpg-BipedalWalker-v3/actor.optimizer.pth +3 -0
- ddpg-BipedalWalker-v3/critic.optimizer.pth +3 -0
- ddpg-BipedalWalker-v3/data +127 -0
- ddpg-BipedalWalker-v3/policy.pth +3 -0
- ddpg-BipedalWalker-v3/pytorch_variables.pth +3 -0
- ddpg-BipedalWalker-v3/system_info.txt +7 -0
- env_kwargs.yml +1 -0
- results.json +1 -0
- train_eval_metrics.zip +3 -0
.gitattributes
CHANGED
@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
32 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
33 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
34 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
32 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
33 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
34 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
35 |
+
*.mp4 filter=lfs diff=lfs merge=lfs -text
|
README.md
ADDED
@@ -0,0 +1,72 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 |
+
- task:
|
12 |
+
type: reinforcement-learning
|
13 |
+
name: reinforcement-learning
|
14 |
+
dataset:
|
15 |
+
name: BipedalWalker-v3
|
16 |
+
type: BipedalWalker-v3
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: 223.18 +/- 101.52
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **DDPG** Agent playing **BipedalWalker-v3**
|
25 |
+
This is a trained model of a **DDPG** agent playing **BipedalWalker-v3**
|
26 |
+
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
|
27 |
+
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
|
28 |
+
|
29 |
+
The RL Zoo is a training framework for Stable Baselines3
|
30 |
+
reinforcement learning agents,
|
31 |
+
with hyperparameter optimization and pre-trained agents included.
|
32 |
+
|
33 |
+
## Usage (with SB3 RL Zoo)
|
34 |
+
|
35 |
+
RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
|
36 |
+
SB3: https://github.com/DLR-RM/stable-baselines3<br/>
|
37 |
+
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
|
38 |
+
|
39 |
+
```
|
40 |
+
# Download model and save it into the logs/ folder
|
41 |
+
python -m rl_zoo3.load_from_hub --algo ddpg --env BipedalWalker-v3 -orga RayanRen -f logs/
|
42 |
+
python enjoy.py --algo ddpg --env BipedalWalker-v3 -f logs/
|
43 |
+
```
|
44 |
+
|
45 |
+
If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
|
46 |
+
```
|
47 |
+
python -m rl_zoo3.load_from_hub --algo ddpg --env BipedalWalker-v3 -orga RayanRen -f logs/
|
48 |
+
rl_zoo3 enjoy --algo ddpg --env BipedalWalker-v3 -f logs/
|
49 |
+
```
|
50 |
+
|
51 |
+
## Training (with the RL Zoo)
|
52 |
+
```
|
53 |
+
python train.py --algo ddpg --env BipedalWalker-v3 -f logs/
|
54 |
+
# Upload the model and generate video (when possible)
|
55 |
+
python -m rl_zoo3.push_to_hub --algo ddpg --env BipedalWalker-v3 -f logs/ -orga RayanRen
|
56 |
+
```
|
57 |
+
|
58 |
+
## Hyperparameters
|
59 |
+
```python
|
60 |
+
OrderedDict([('buffer_size', 200000),
|
61 |
+
('gamma', 0.98),
|
62 |
+
('gradient_steps', -1),
|
63 |
+
('learning_rate', 0.001),
|
64 |
+
('learning_starts', 10000),
|
65 |
+
('n_timesteps', 1000000.0),
|
66 |
+
('noise_std', 0.1),
|
67 |
+
('noise_type', 'normal'),
|
68 |
+
('policy', 'MlpPolicy'),
|
69 |
+
('policy_kwargs', 'dict(net_arch=[400, 300])'),
|
70 |
+
('train_freq', [1, 'episode']),
|
71 |
+
('normalize', False)])
|
72 |
+
```
|
args.yml
ADDED
@@ -0,0 +1,81 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
!!python/object/apply:collections.OrderedDict
|
2 |
+
- - - algo
|
3 |
+
- ddpg
|
4 |
+
- - conf_file
|
5 |
+
- null
|
6 |
+
- - device
|
7 |
+
- auto
|
8 |
+
- - env
|
9 |
+
- BipedalWalker-v3
|
10 |
+
- - env_kwargs
|
11 |
+
- null
|
12 |
+
- - eval_episodes
|
13 |
+
- 5
|
14 |
+
- - eval_freq
|
15 |
+
- 25000
|
16 |
+
- - gym_packages
|
17 |
+
- []
|
18 |
+
- - hyperparams
|
19 |
+
- null
|
20 |
+
- - log_folder
|
21 |
+
- logs/
|
22 |
+
- - log_interval
|
23 |
+
- -1
|
24 |
+
- - max_total_trials
|
25 |
+
- null
|
26 |
+
- - n_eval_envs
|
27 |
+
- 1
|
28 |
+
- - n_evaluations
|
29 |
+
- null
|
30 |
+
- - n_jobs
|
31 |
+
- 1
|
32 |
+
- - n_startup_trials
|
33 |
+
- 10
|
34 |
+
- - n_timesteps
|
35 |
+
- -1
|
36 |
+
- - n_trials
|
37 |
+
- 500
|
38 |
+
- - no_optim_plots
|
39 |
+
- false
|
40 |
+
- - num_threads
|
41 |
+
- -1
|
42 |
+
- - optimization_log_path
|
43 |
+
- null
|
44 |
+
- - optimize_hyperparameters
|
45 |
+
- false
|
46 |
+
- - progress
|
47 |
+
- false
|
48 |
+
- - pruner
|
49 |
+
- median
|
50 |
+
- - sampler
|
51 |
+
- tpe
|
52 |
+
- - save_freq
|
53 |
+
- -1
|
54 |
+
- - save_replay_buffer
|
55 |
+
- false
|
56 |
+
- - seed
|
57 |
+
- 3543050334
|
58 |
+
- - storage
|
59 |
+
- null
|
60 |
+
- - study_name
|
61 |
+
- null
|
62 |
+
- - tensorboard_log
|
63 |
+
- ''
|
64 |
+
- - track
|
65 |
+
- false
|
66 |
+
- - trained_agent
|
67 |
+
- ''
|
68 |
+
- - truncate_last_trajectory
|
69 |
+
- true
|
70 |
+
- - uuid
|
71 |
+
- false
|
72 |
+
- - vec_env
|
73 |
+
- dummy
|
74 |
+
- - verbose
|
75 |
+
- 1
|
76 |
+
- - wandb_entity
|
77 |
+
- null
|
78 |
+
- - wandb_project_name
|
79 |
+
- sb3
|
80 |
+
- - yaml_file
|
81 |
+
- null
|
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 |
+
- 0.001
|
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:b53287a4d869c112329473a3a0d8943b340dc76f028e8bc6ba13dd64282ba196
|
3 |
+
size 4258741
|
ddpg-BipedalWalker-v3/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.2
|
ddpg-BipedalWalker-v3/actor.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:33f885ae30715373f10e394d2818fbc1953ea1e4540ea8712a12fe5826c4066f
|
3 |
+
size 1056943
|
ddpg-BipedalWalker-v3/critic.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:7b8448f169c3d0048f7ef8ec69051467037eee85d6eba09caf1a6357d19c3da9
|
3 |
+
size 1062447
|
ddpg-BipedalWalker-v3/data
ADDED
@@ -0,0 +1,127 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"policy_class": {
|
3 |
+
":type:": "<class 'abc.ABCMeta'>",
|
4 |
+
":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMCVREM1BvbGljeZSTlC4=",
|
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 0x000001C126FC3E50>",
|
8 |
+
"_build": "<function TD3Policy._build at 0x000001C126FC3EE0>",
|
9 |
+
"_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x000001C126FC3F70>",
|
10 |
+
"make_actor": "<function TD3Policy.make_actor at 0x000001C126FCE040>",
|
11 |
+
"make_critic": "<function TD3Policy.make_critic at 0x000001C126FCE0D0>",
|
12 |
+
"forward": "<function TD3Policy.forward at 0x000001C126FCE160>",
|
13 |
+
"_predict": "<function TD3Policy._predict at 0x000001C126FCE1F0>",
|
14 |
+
"set_training_mode": "<function TD3Policy.set_training_mode at 0x000001C126FCE280>",
|
15 |
+
"__abstractmethods__": "frozenset()",
|
16 |
+
"_abc_impl": "<_abc_data object at 0x000001C126FC7870>"
|
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:": "gAWVIgwAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLBIWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAIC/AACAvwAAgL8AAIC/lGgKSwSFlIwBQ5R0lFKUjARoaWdolGgSKJYQAAAAAAAAAAAAgD8AAIA/AACAPwAAgD+UaApLBIWUaBV0lFKUjA1ib3VuZGVkX2JlbG93lGgSKJYEAAAAAAAAAAEBAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLBIWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYEAAAAAAAAAAEBAQGUaCFLBIWUaBV0lFKUjApfbnBfcmFuZG9tlIwUbnVtcHkucmFuZG9tLl9waWNrbGWUjBJfX3JhbmRvbXN0YXRlX2N0b3KUk5SMB01UMTk5MzeUaC2MFF9fYml0X2dlbmVyYXRvcl9jdG9ylJOUhpRSlH2UKIwNYml0X2dlbmVyYXRvcpSMB01UMTk5MzeUjAVzdGF0ZZR9lCiMA2tleZRoEiiWwAkAAAAAAAAAAACAU8KznIcDtZNy7Ktb6Oay8s+2gdrVBu9hoTFNoGu1zNkT5hifdJx5L8ilG4DEeQFJng9D5F3gGJOSE1XM1EopZNIIlb400J5EcnoD8K2/CnObez7pYLEG2nUDRQtufdYWausENGaDt/P1pS9p70JjQ7Vc98J3UsxGRDctCIlu0I6ud/sYtoBPe575TzLsEti5jl6FqRnKrj12LWcrQoCexe7HH/UiAV1LzyQPzBlSZERXmHCdCvUSF7XpWt47xP9BzzqxX7aH3TPYWImqos1/ez/JlLdsD0MfMZl9G2CQq7cHHRlM3sj7jroA9c+pGt4l/iAGpRb80HbjwU71ykPTAVp531BXrc2qmIU6z9Fh4TAPx7fZ1kVF+L1Irlou+4Ckky7Ys59nB7KkciTI+N5jlb62ybZt0+ZWgIA6LKLvdx/mTQtB4k1aplT/C7L9/ybKCFn2quN/7YlIkxoH1U0xdabG6rgOrR+SHMmvUwvtKB+19Ibb07mSgVQyjNAvnyADPJf3pkxylZtn7f/OVpWEaWfl6BcLwy0grrEgUK+H+8P8XWMuBginXgwzn3sy4+ZOlr45op6TtuqX0Knz/SySGDlBIK8JqKObzB6fGt+ovJHEM8KlL4veKwkLkuuMWBaex3FBdWskry5qhslxMgnk2thh8DaXmAfbuI8j0SqHMW1kleITi9ekfXx/eSi5hX1GjA/M62Zixuay1H8zH9VjsTRcGacyJ0vh1hNReDFoNsXFbLfLqaIvbLDQjY7T289ZXsupvAxu2GVTbqWst+ckPPzwH7vLikULC+weAKwxarqm+ugAXgyz774meHOsvQYuu18nvrrunjZWDvwaKuYohEwUfSnpotE9XhX99yUTc8sGPQidTfXkzm/t8MWP8it4l4VSEgDLn8GW8t2DAh8EwFa/KOGoZEGjYqZ2IMA70E+F2LqgaZlQLFMONTIx3yuN5F2e1MT4v2wdBRK9R+lGMpxIiNldyOwwxLDBTRDMhd7APidmDwQBnvaIecKFa95btwHkRBEUT5g++/I0DDg685EX4OMO2YtTPqM3PQluS4puEhAQRVukNGSh4gYDgcBPKZl4ThNf+G+E7El9fmWJcP39Sifw6Mn+GEisM1RhHY05XZHUv5W4r8kD2jSLMY+IIL2+LtQrW7it7y28+sEicLoEfYOky9ZJF6l0fR+sXEawf+REH9LvtRJ4yzfxr7KisNpr1axv1ae5CDXS+XTzuOG/BJnHvt8arnY1XWH9SdkCOeok6MI8GBCtjTCxJ5JbpI5J0i0A66mJaRW9LMfP6Cil3/cVRQ9uN2KTtV3o7rJwY4XCnj7DJmqrUwofDDl7Ek0PoN7w0Hh8YHOy8qhPw7V8ALdjZn7eYtjCQIldQvHbM1I73RtCLQvQGFMXUCJ022pGRqTvZX5XWSizqbgX6TJmI6LDF9wcpYealB7cDwelfqdpzHRmyjRbIX9b+w4uj//aDRgP2SgiOAq/D/9/0SbgK/E0FQyclhNVAkbKwXhAxKGczpvJow0mFFUAt/5fT5KAsmQTAt8p0FsrGMDTfk4RzZgqZSm+ihVRS371Tx3twpGA1goo/AIfJh8slJC3hkR1OGCN7LAPGCwbM9rHlKSU4uuhJiff196h9q1kPMld6989MfKLVkvCl7ofCRurPUW46ceJKE951sQD1v8cK0HK1JmuBTCXAelCUCIFNLGk3tMXNVmuuFF3o3xb4V4T1IAYIfBdyEVHhIIZOE/JEY79daQw8njYEtQ6YwZ6kNCBYfrjq2OglITcRdwDmINL42ro6HnbWgLZQ8Ce/EiPVBtWHwhvGUHK1FNONzRzXgT1zKEg+WAigeuK4QVIxdITM4YvUyYvpQJuJd+xGD1no7BYIKXdV4aDlsRnWSMmS+zTyTvC0+TgBMCNpMvdChjaB/XTrMVsm0vgPmCYswn067MTYWfm5oCqqmNciqoRfFL2O2mxFT1VMcKDrxHBdBUhSG5UmAerx86KAEytbsCbn6OOj8Y02VwVynzXd0WJfLioeGMZISM1eneWfTc1mQ6CpdDxJqUmU86/KsBL3Bb0S2NAqFysFJZKxDwLej8xz+xH8IxEHzlkiiNH+2IIq0663FAwi6wg6dgcryDqQ+lNDwn898nylrcYShigDrtrFBNezKx3ZjpkPCnPUeQB4hJUrYCUJy5CyytC/x1UsByKez/aSNEWnlWnzYdJf2PoKL0YfmaR3KpXzi9ax3BHPgk1cdmgdVkqevFJ0DUdTBFQj/mhaKqcaT0rKJLgy/11AhWW4nX7+kAdgR0b1iAseI0TbMDtohBuqqUZfqMfUKsdI8v2aeUd0+IqOjPBFe7TZRC7OUYmf789SRTpw9gst4tzx7tLap8JnFt2keKhqd3vBgqpvlsxvx0DcPC+bo/qIldKiAn5D7TPjeWLzJ1gmpk1mVKOyWOv/ZzlRTfe8yEsMsRcgdPxbOuxLjlOwo1uFh9NjHoOz/xbnI62I49ZzT59GUCNtAL74UqjlRoyXZ5ELEjhTn+F5fYfEkY2TnSsgKO4Wwb/xD41S4mBL7LcUyF76ybV7Yx0L6V2QGoSfyhHFqMQJs/haLPPW18mWJb/UDl90ZN9TEzcdXvZsmCeqzCagC6YDHp3fop+5nAQSnT/Byt2j7z+6cnl/aZh6oKs5xrEMmuzpLFbXNVof9hNmX5E0DQ2M8uBqqeW95p6z8ySnOxURAO28oYWsbVyeYaNlWLZrOtIMZDRjjbecSSwMLlrBhw4mZVht4DgOQxI1+P7sPHZLMf89U+5ctf1rD0r1AXgyXjzOxKvCxWMhrz6Ah19+zal/bAIpw+0V7Pq85PRQO4UeScmMwODR8jcOfILuMmo7xXhemY/JqtOncklEaGapMeGlkiefvQkx9L5EWvLn6stI4zRP4pZXx9iOz17IKJmKOVHgCIAOiheb0bwkjNkItlfYO3LzeLLPuBDNLFg7tQu5NPWy28a4nBsE/gsyEteRvF2ECYFIOJg06dzc77IWw7o+z1Q5APxLg9uvyFniYWNuJyk7rflLCmYcg1gN657CWff8YfPr0ukKOamco94X1nFdyroxHiQlRXaP91DOqMueI1pCasyRQt0jtbWwxdEVyzP3GzUZXBWqa0xXCzwe29cxg2aiwKuuAAVfaCE/Pt1cJXq8wvliF81sMDPMbowd9+uyWuExq/e+2W3wWeV3hVofoiEySjBrJPWVJW9++UocJbC0ppNw5mtHktkZqUk6kVtUgVQ4Cj4udj/bluZzcqWjIvOCJO52M+xcQY808Ei8T/lwwS9TguuzQ3e0KR7hptgNcX1/XhCvAuUaAeMAnU0lImIh5RSlChLA2gLTk5OSv////9K/////0sAdJRiTXAChZRoFXSUUpSMA3Bvc5RNcAJ1jAloYXNfZ2F1c3OUSwCMBWdhdXNzlEcAAAAAAAAAAHVidWIu",
|
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": 300000,
|
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:": "gAWVGgEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMEU5vcm1hbEFjdGlvbk5vaXNllJOUKYGUfZQojANfbXWUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJSMBW51bXB5lIwFZHR5cGWUk5SMAmY4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLBIWUjAFDlHSUUpSMBl9zaWdtYZRoCCiWIAAAAAAAAACamZmZmZm5P5qZmZmZmbk/mpmZmZmZuT+amZmZmZm5P5RoD0sEhZRoE3SUUpR1Yi4=",
|
60 |
+
"_mu": "[0. 0. 0. 0.]",
|
61 |
+
"_sigma": "[0.1 0.1 0.1 0.1]"
|
62 |
+
},
|
63 |
+
"start_time": 1672260973557532400,
|
64 |
+
"learning_rate": {
|
65 |
+
":type:": "<class 'function'>",
|
66 |
+
":serialized:": "gAWVmwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMaUM6XFVzZXJzXHJhaWFuXEFwcERhdGFcTG9jYWxcUHJvZ3JhbXNcUHl0aG9uXFB5dGhvbjM4XGxpYlxzaXRlLXBhY2thZ2VzXHN0YWJsZV9iYXNlbGluZXMzXGNvbW1vblx1dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5RoDHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB59lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz9QYk3S8an8hZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
|
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:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
|
77 |
+
},
|
78 |
+
"_last_original_obs": {
|
79 |
+
":type:": "<class 'numpy.ndarray'>",
|
80 |
+
":serialized:": "gAWV1QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZgAAAAAAAAACrhajwsYos8wowGP9SCEb4uHOQ+J0sYP1SaNb/9/3+/AAAAADF1hT/oRmc+ehoyv0iuBr8AAIA/t7GrPuCkrT78a7M+0ZO9PvGhzD5XFeY+SqUKP9tzMT+643Q/AACAP5SMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsYhpSMAUOUdJRSlC4="
|
81 |
+
},
|
82 |
+
"_episode_num": 792,
|
83 |
+
"use_sde": false,
|
84 |
+
"sde_sample_freq": -1,
|
85 |
+
"_current_progress_remaining": 0.700001,
|
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:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
93 |
+
},
|
94 |
+
"_n_updates": 290790,
|
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:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
|
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: PyTorch 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 0x000001C126FB6A60>",
|
108 |
+
"add": "<function ReplayBuffer.add at 0x000001C126FB6AF0>",
|
109 |
+
"sample": "<function ReplayBuffer.sample at 0x000001C126FB6B80>",
|
110 |
+
"_get_samples": "<function ReplayBuffer._get_samples at 0x000001C126FB6C10>",
|
111 |
+
"__abstractmethods__": "frozenset()",
|
112 |
+
"_abc_impl": "<_abc_data object at 0x000001C126FB97B0>"
|
113 |
+
},
|
114 |
+
"replay_buffer_kwargs": {},
|
115 |
+
"train_freq": {
|
116 |
+
":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
|
117 |
+
":serialized:": "gAWVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"
|
118 |
+
},
|
119 |
+
"use_sde_at_warmup": false,
|
120 |
+
"policy_delay": 1,
|
121 |
+
"target_noise_clip": 0.0,
|
122 |
+
"target_policy_noise": 0.1,
|
123 |
+
"actor_batch_norm_stats": [],
|
124 |
+
"critic_batch_norm_stats": [],
|
125 |
+
"actor_batch_norm_stats_target": [],
|
126 |
+
"critic_batch_norm_stats_target": []
|
127 |
+
}
|
ddpg-BipedalWalker-v3/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:2dfb6eeadb4ed563f78c0e6273a3f7c3d192472a981c1e767972aaa917f24eba
|
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: Windows-10-10.0.22621-SP0 10.0.22621
|
2 |
+
Python: 3.8.0
|
3 |
+
Stable-Baselines3: 1.6.2
|
4 |
+
PyTorch: 1.13.1+cu116
|
5 |
+
GPU Enabled: True
|
6 |
+
Numpy: 1.24.0
|
7 |
+
Gym: 0.21.0
|
env_kwargs.yml
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{}
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 223.1825629, "std_reward": 101.51688844763937, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-29T08:19:38.946939"}
|
train_eval_metrics.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3b516bc90dca05613d7ee159bafdb519af43c6091d60f7b7b16043c9cdababfc
|
3 |
+
size 82831
|