Quentin Gallouédec
commited on
Commit
•
7a55651
1
Parent(s):
d1817a7
Initial commit
Browse files- .gitattributes +1 -0
- README.md +77 -0
- args.yml +81 -0
- config.yml +23 -0
- ddpg-ReacherBulletEnv-v0.zip +3 -0
- ddpg-ReacherBulletEnv-v0/_stable_baselines3_version +1 -0
- ddpg-ReacherBulletEnv-v0/actor.optimizer.pth +3 -0
- ddpg-ReacherBulletEnv-v0/critic.optimizer.pth +3 -0
- ddpg-ReacherBulletEnv-v0/data +135 -0
- ddpg-ReacherBulletEnv-v0/policy.pth +3 -0
- ddpg-ReacherBulletEnv-v0/pytorch_variables.pth +3 -0
- ddpg-ReacherBulletEnv-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
@@ -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 +1,77 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: stable-baselines3
|
3 |
+
tags:
|
4 |
+
- ReacherBulletEnv-v0
|
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: ReacherBulletEnv-v0
|
16 |
+
type: ReacherBulletEnv-v0
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: 17.35 +/- 10.49
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **DDPG** Agent playing **ReacherBulletEnv-v0**
|
25 |
+
This is a trained model of a **DDPG** agent playing **ReacherBulletEnv-v0**
|
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 |
+
Install the RL Zoo (with SB3 and SB3-Contrib):
|
40 |
+
```bash
|
41 |
+
pip install rl_zoo3
|
42 |
+
```
|
43 |
+
|
44 |
+
```
|
45 |
+
# Download model and save it into the logs/ folder
|
46 |
+
python -m rl_zoo3.load_from_hub --algo ddpg --env ReacherBulletEnv-v0 -orga qgallouedec -f logs/
|
47 |
+
python -m rl_zoo3.enjoy --algo ddpg --env ReacherBulletEnv-v0 -f logs/
|
48 |
+
```
|
49 |
+
|
50 |
+
If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
|
51 |
+
```
|
52 |
+
python -m rl_zoo3.load_from_hub --algo ddpg --env ReacherBulletEnv-v0 -orga qgallouedec -f logs/
|
53 |
+
python -m rl_zoo3.enjoy --algo ddpg --env ReacherBulletEnv-v0 -f logs/
|
54 |
+
```
|
55 |
+
|
56 |
+
## Training (with the RL Zoo)
|
57 |
+
```
|
58 |
+
python -m rl_zoo3.train --algo ddpg --env ReacherBulletEnv-v0 -f logs/
|
59 |
+
# Upload the model and generate video (when possible)
|
60 |
+
python -m rl_zoo3.push_to_hub --algo ddpg --env ReacherBulletEnv-v0 -f logs/ -orga qgallouedec
|
61 |
+
```
|
62 |
+
|
63 |
+
## Hyperparameters
|
64 |
+
```python
|
65 |
+
OrderedDict([('buffer_size', 200000),
|
66 |
+
('gamma', 0.98),
|
67 |
+
('gradient_steps', 1),
|
68 |
+
('learning_rate', 0.001),
|
69 |
+
('learning_starts', 10000),
|
70 |
+
('n_timesteps', 300000.0),
|
71 |
+
('noise_std', 0.1),
|
72 |
+
('noise_type', 'normal'),
|
73 |
+
('policy', 'MlpPolicy'),
|
74 |
+
('policy_kwargs', 'dict(net_arch=[400, 300])'),
|
75 |
+
('train_freq', 1),
|
76 |
+
('normalize', False)])
|
77 |
+
```
|
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 |
+
- ReacherBulletEnv-v0
|
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 |
+
- 4032213828
|
58 |
+
- - storage
|
59 |
+
- null
|
60 |
+
- - study_name
|
61 |
+
- null
|
62 |
+
- - tensorboard_log
|
63 |
+
- runs/ReacherBulletEnv-v0__ddpg__4032213828__1671827787
|
64 |
+
- - track
|
65 |
+
- true
|
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 |
+
- openrlbenchmark
|
78 |
+
- - wandb_project_name
|
79 |
+
- sb3
|
80 |
+
- - yaml_file
|
81 |
+
- null
|
config.yml
ADDED
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 |
+
- 300000.0
|
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
|
ddpg-ReacherBulletEnv-v0.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e5aef921add0c9f43bc6c15ae6736f604ef6dd9adb996c845eb9fd1e4ac2b8f1
|
3 |
+
size 4042609
|
ddpg-ReacherBulletEnv-v0/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.8.0a6
|
ddpg-ReacherBulletEnv-v0/actor.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d93c49a568d563e79d7ea6ea7508acb171f477c23d4320bc9786ee5e2fd4c29c
|
3 |
+
size 1004079
|
ddpg-ReacherBulletEnv-v0/critic.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ec2078ffa3c406c7d45f81317b2ef721bfbe4b8cbec83643d5718e7f306a1713
|
3 |
+
size 1008047
|
ddpg-ReacherBulletEnv-v0/data
ADDED
@@ -0,0 +1,135 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x7f9bab8ed940>",
|
8 |
+
"_build": "<function TD3Policy._build at 0x7f9bab8ed9d0>",
|
9 |
+
"_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7f9bab8eda60>",
|
10 |
+
"make_actor": "<function TD3Policy.make_actor at 0x7f9bab8edaf0>",
|
11 |
+
"make_critic": "<function TD3Policy.make_critic at 0x7f9bab8edb80>",
|
12 |
+
"forward": "<function TD3Policy.forward at 0x7f9bab8edc10>",
|
13 |
+
"_predict": "<function TD3Policy._predict at 0x7f9bab8edca0>",
|
14 |
+
"set_training_mode": "<function TD3Policy.set_training_mode at 0x7f9bab8edd30>",
|
15 |
+
"__abstractmethods__": "frozenset()",
|
16 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f9bab8f0800>"
|
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 |
+
9
|
32 |
+
],
|
33 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf]",
|
34 |
+
"high": "[inf inf inf inf inf inf inf inf inf]",
|
35 |
+
"bounded_below": "[False False False False False False False False False]",
|
36 |
+
"bounded_above": "[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 |
+
2
|
45 |
+
],
|
46 |
+
"low": "[-1. -1.]",
|
47 |
+
"high": "[1. 1.]",
|
48 |
+
"bounded_below": "[ True True]",
|
49 |
+
"bounded_above": "[ True True]",
|
50 |
+
"_np_random": "RandomState(MT19937)"
|
51 |
+
},
|
52 |
+
"n_envs": 1,
|
53 |
+
"num_timesteps": 300000,
|
54 |
+
"_total_timesteps": 300000,
|
55 |
+
"_num_timesteps_at_start": 0,
|
56 |
+
"seed": 0,
|
57 |
+
"action_noise": {
|
58 |
+
":type:": "<class 'stable_baselines3.common.noise.NormalActionNoise'>",
|
59 |
+
":serialized:": "gAWV+gAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMEU5vcm1hbEFjdGlvbk5vaXNllJOUKYGUfZQojANfbXWUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksChZSMAUOUdJRSlIwGX3NpZ21hlGgIKJYQAAAAAAAAAJqZmZmZmbk/mpmZmZmZuT+UaA9LAoWUaBN0lFKUdWIu",
|
60 |
+
"_mu": "[0. 0.]",
|
61 |
+
"_sigma": "[0.1 0.1]"
|
62 |
+
},
|
63 |
+
"start_time": 1671827789478869069,
|
64 |
+
"learning_rate": {
|
65 |
+
":type:": "<class 'function'>",
|
66 |
+
":serialized:": "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"
|
67 |
+
},
|
68 |
+
"tensorboard_log": "runs/ReacherBulletEnv-v0__ddpg__4032213828__1671827787/ReacherBulletEnv-v0",
|
69 |
+
"lr_schedule": {
|
70 |
+
":type:": "<class 'function'>",
|
71 |
+
":serialized:": "gAWVvQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMRS9ob21lL3FnYWxsb3VlZGVjL3N0YWJsZS1iYXNlbGluZXMzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMRS9ob21lL3FnYWxsb3VlZGVjL3N0YWJsZS1iYXNlbGluZXMzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/UGJN0vGp/IWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
|
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:": "gAWVmQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYkAAAAAAAAAAS0Mr6L3wI++mWYPOSV07qHOH2/VXoWPhBKqLvrsEw+AYxkvJSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsJhpSMAUOUdJRSlC4="
|
81 |
+
},
|
82 |
+
"_episode_num": 2000,
|
83 |
+
"use_sde": false,
|
84 |
+
"sde_sample_freq": -1,
|
85 |
+
"_current_progress_remaining": 0.0,
|
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": 290000,
|
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 0x7f9bab8ea430>",
|
108 |
+
"add": "<function ReplayBuffer.add at 0x7f9bab8ea4c0>",
|
109 |
+
"sample": "<function ReplayBuffer.sample at 0x7f9bab8ea550>",
|
110 |
+
"_get_samples": "<function ReplayBuffer._get_samples at 0x7f9bab8ea5e0>",
|
111 |
+
"__abstractmethods__": "frozenset()",
|
112 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f9bab8e4680>"
|
113 |
+
},
|
114 |
+
"replay_buffer_kwargs": {},
|
115 |
+
"train_freq": {
|
116 |
+
":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
|
117 |
+
":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
|
118 |
+
},
|
119 |
+
"use_sde_at_warmup": false,
|
120 |
+
"policy_delay": 1,
|
121 |
+
"target_noise_clip": 0.0,
|
122 |
+
"target_policy_noise": 0.1,
|
123 |
+
"_action_repeat": [
|
124 |
+
null
|
125 |
+
],
|
126 |
+
"surgeon": null,
|
127 |
+
"actor_batch_norm_stats": [],
|
128 |
+
"critic_batch_norm_stats": [],
|
129 |
+
"actor_batch_norm_stats_target": [],
|
130 |
+
"critic_batch_norm_stats_target": [],
|
131 |
+
"_last_action": {
|
132 |
+
":type:": "<class 'numpy.ndarray'>",
|
133 |
+
":serialized:": "gAWVfQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAKiSQj5A6Ye8lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwKGlIwBQ5R0lFKULg=="
|
134 |
+
}
|
135 |
+
}
|
ddpg-ReacherBulletEnv-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6e631da334ecb4341105133f781d7ed5f595746f2de8d2971c68edb3c1405d9f
|
3 |
+
size 2010397
|
ddpg-ReacherBulletEnv-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-ReacherBulletEnv-v0/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: Linux-5.19.0-32-generic-x86_64-with-glibc2.35 # 33~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Mon Jan 30 17:03:34 UTC 2
|
2 |
+
- Python: 3.9.12
|
3 |
+
- Stable-Baselines3: 1.8.0a6
|
4 |
+
- PyTorch: 1.13.1+cu117
|
5 |
+
- GPU Enabled: True
|
6 |
+
- Numpy: 1.24.1
|
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 sha256:88d056c7b271f0cab4695488e73947cafb8f33074d7c3d157e67c94bbe2b5b52
|
3 |
+
size 63169
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 17.345257600000004, "std_reward": 10.490832482100657, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-02-27T17:18:00.775021"}
|
train_eval_metrics.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:f83c0b98b679b54b0d7dfed52a1b1fafdc80a4f609db1ac63ee854b1d2073c4f
|
3 |
+
size 53369
|