Antonin Raffin
commited on
Commit
·
b9ea552
1
Parent(s):
15283aa
Initial commit
Browse files- .gitattributes +1 -0
- README.md +67 -0
- args.yml +59 -0
- config.yml +28 -0
- ddpg-Walker2DBulletEnv-v0.zip +3 -0
- ddpg-Walker2DBulletEnv-v0/_stable_baselines3_version +1 -0
- ddpg-Walker2DBulletEnv-v0/actor.optimizer.pth +3 -0
- ddpg-Walker2DBulletEnv-v0/critic.optimizer.pth +3 -0
- ddpg-Walker2DBulletEnv-v0/data +125 -0
- ddpg-Walker2DBulletEnv-v0/policy.pth +3 -0
- ddpg-Walker2DBulletEnv-v0/pytorch_variables.pth +3 -0
- ddpg-Walker2DBulletEnv-v0/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
@@ -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
|