jackoyoungblood
commited on
Commit
•
22b1923
1
Parent(s):
299c73d
Initial commit
Browse files- .gitattributes +1 -0
- README.md +65 -0
- args.yml +75 -0
- config.yml +24 -0
- ddpg-BipedalWalkerHardcore-v3.zip +3 -0
- ddpg-BipedalWalkerHardcore-v3/_stable_baselines3_version +1 -0
- ddpg-BipedalWalkerHardcore-v3/actor.optimizer.pth +3 -0
- ddpg-BipedalWalkerHardcore-v3/critic.optimizer.pth +3 -0
- ddpg-BipedalWalkerHardcore-v3/data +123 -0
- ddpg-BipedalWalkerHardcore-v3/policy.pth +3 -0
- ddpg-BipedalWalkerHardcore-v3/pytorch_variables.pth +3 -0
- ddpg-BipedalWalkerHardcore-v3/system_info.txt +7 -0
- env_kwargs.yml +1 -0
- replay.mp4 +3 -0
- results.json +1 -0
- train_eval_metrics.zip +3 -0
.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 |
+
- BipedalWalkerHardcore-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: -132.89 +/- 24.41
|
14 |
+
name: mean_reward
|
15 |
+
task:
|
16 |
+
type: reinforcement-learning
|
17 |
+
name: reinforcement-learning
|
18 |
+
dataset:
|
19 |
+
name: BipedalWalkerHardcore-v3
|
20 |
+
type: BipedalWalkerHardcore-v3
|
21 |
+
---
|
22 |
+
|
23 |
+
# **DDPG** Agent playing **BipedalWalkerHardcore-v3**
|
24 |
+
This is a trained model of a **DDPG** agent playing **BipedalWalkerHardcore-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 BipedalWalkerHardcore-v3 -orga jackoyoungblood -f logs/
|
41 |
+
python enjoy.py --algo ddpg --env BipedalWalkerHardcore-v3 -f logs/
|
42 |
+
```
|
43 |
+
|
44 |
+
## Training (with the RL Zoo)
|
45 |
+
```
|
46 |
+
python train.py --algo ddpg --env BipedalWalkerHardcore-v3 -f logs/
|
47 |
+
# Upload the model and generate video (when possible)
|
48 |
+
python -m utils.push_to_hub --algo ddpg --env BipedalWalkerHardcore-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', 0.001),
|
57 |
+
('learning_starts', 10000),
|
58 |
+
('n_timesteps', 100000.0),
|
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 |
+
- BipedalWalkerHardcore-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 |
+
- 4012439461
|
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 |
+
- 0.001
|
10 |
+
- - learning_starts
|
11 |
+
- 10000
|
12 |
+
- - n_timesteps
|
13 |
+
- 100000.0
|
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-BipedalWalkerHardcore-v3.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4bded90827d2504cc345c39c8ca9b0d3836af3239f986657f0ae051e5c0d013d
|
3 |
+
size 4258687
|
ddpg-BipedalWalkerHardcore-v3/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.6.0
|
ddpg-BipedalWalkerHardcore-v3/actor.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c459ad050cf8c2a1a4b3fee5829fef92ffef1634d24106ab4f04e51e06d74703
|
3 |
+
size 1056879
|
ddpg-BipedalWalkerHardcore-v3/critic.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:331ff6acdd4e46b14dce47012288940b61a06be0fd231f83e411f9306591817c
|
3 |
+
size 1062383
|
ddpg-BipedalWalkerHardcore-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 0x7f2b4f6eb290>",
|
8 |
+
"_build": "<function TD3Policy._build at 0x7f2b4f6eb320>",
|
9 |
+
"_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7f2b4f6eb3b0>",
|
10 |
+
"make_actor": "<function TD3Policy.make_actor at 0x7f2b4f6eb440>",
|
11 |
+
"make_critic": "<function TD3Policy.make_critic at 0x7f2b4f6eb4d0>",
|
12 |
+
"forward": "<function TD3Policy.forward at 0x7f2b4f6eb560>",
|
13 |
+
"_predict": "<function TD3Policy._predict at 0x7f2b4f6eb5f0>",
|
14 |
+
"set_training_mode": "<function TD3Policy.set_training_mode at 0x7f2b4f6eb680>",
|
15 |
+
"__abstractmethods__": "frozenset()",
|
16 |
+
"_abc_impl": "<_abc_data object at 0x7f2b4f6de450>"
|
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": 101418,
|
54 |
+
"_total_timesteps": 100000,
|
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": 1660942318.9387212,
|
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/////0sAdJRiiUNg7i8Xvew7CDFdeyey2XSbsRR9jz8AAIAmMiAhvwAAAAAAAIA/XnlTvwAAAAAw5Ww/VVVVpwAAAAA8vbI+4cS0PnYYuz4igMY+w5DYPndI9D5sxQ8/4q8OP4DLBD8AAIA/lHSUYi4="
|
81 |
+
},
|
82 |
+
"_episode_num": 337,
|
83 |
+
"use_sde": false,
|
84 |
+
"sde_sample_freq": -1,
|
85 |
+
"_current_progress_remaining": -0.014180000000000081,
|
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": 93004,
|
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 0x7f2b4fb6d7a0>",
|
108 |
+
"add": "<function ReplayBuffer.add at 0x7f2b4fb6d830>",
|
109 |
+
"sample": "<function ReplayBuffer.sample at 0x7f2b4fb5a830>",
|
110 |
+
"_get_samples": "<function ReplayBuffer._get_samples at 0x7f2b4fb5a8c0>",
|
111 |
+
"__abstractmethods__": "frozenset()",
|
112 |
+
"_abc_impl": "<_abc_data object at 0x7f2b4fbd5060>"
|
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-BipedalWalkerHardcore-v3/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a83258854983aebdd0362d6ec33596ee2c8be0e57463ac0ef86426cbf6f14f78
|
3 |
+
size 2117597
|
ddpg-BipedalWalkerHardcore-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-BipedalWalkerHardcore-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 sha256:19d63a791779c482d7d15ef98fc62900dda66ed2bde8176441698d1b80f8f3ac
|
3 |
+
size 303471
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": -132.89436849999998, "std_reward": 24.407704192933526, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-19T21:11:47.600268"}
|
train_eval_metrics.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:7eb8071c3d6dce401d615c5491ee5d439e79037e788cfcb5440ef670b659b0ff
|
3 |
+
size 10506
|