Quentin Gallouédec
commited on
Commit
·
e238683
1
Parent(s):
c33d4ec
Initial commit
Browse files- .gitattributes +1 -0
- README.md +75 -0
- args.yml +83 -0
- config.yml +17 -0
- ddpg-CartpoleTwoPolesDMC-v0.zip +3 -0
- ddpg-CartpoleTwoPolesDMC-v0/_stable_baselines3_version +1 -0
- ddpg-CartpoleTwoPolesDMC-v0/actor.optimizer.pth +3 -0
- ddpg-CartpoleTwoPolesDMC-v0/critic.optimizer.pth +3 -0
- ddpg-CartpoleTwoPolesDMC-v0/data +137 -0
- ddpg-CartpoleTwoPolesDMC-v0/policy.pth +3 -0
- ddpg-CartpoleTwoPolesDMC-v0/pytorch_variables.pth +3 -0
- ddpg-CartpoleTwoPolesDMC-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 +1,75 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: stable-baselines3
|
3 |
+
tags:
|
4 |
+
- CartpoleTwoPolesDMC-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: CartpoleTwoPolesDMC-v0
|
16 |
+
type: CartpoleTwoPolesDMC-v0
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: 274.78 +/- 23.12
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **DDPG** Agent playing **CartpoleTwoPolesDMC-v0**
|
25 |
+
This is a trained model of a **DDPG** agent playing **CartpoleTwoPolesDMC-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 CartpoleTwoPolesDMC-v0 -orga qgallouedec -f logs/
|
47 |
+
python -m rl_zoo3.enjoy --algo ddpg --env CartpoleTwoPolesDMC-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 CartpoleTwoPolesDMC-v0 -orga qgallouedec -f logs/
|
53 |
+
python -m rl_zoo3.enjoy --algo ddpg --env CartpoleTwoPolesDMC-v0 -f logs/
|
54 |
+
```
|
55 |
+
|
56 |
+
## Training (with the RL Zoo)
|
57 |
+
```
|
58 |
+
python -m rl_zoo3.train --algo ddpg --env CartpoleTwoPolesDMC-v0 -f logs/
|
59 |
+
# Upload the model and generate video (when possible)
|
60 |
+
python -m rl_zoo3.push_to_hub --algo ddpg --env CartpoleTwoPolesDMC-v0 -f logs/ -orga qgallouedec
|
61 |
+
```
|
62 |
+
|
63 |
+
## Hyperparameters
|
64 |
+
```python
|
65 |
+
OrderedDict([('batch_size', 64),
|
66 |
+
('gamma', 0.99),
|
67 |
+
('learning_rate', 0.0001),
|
68 |
+
('n_timesteps', 1000000.0),
|
69 |
+
('noise_std', 0.3),
|
70 |
+
('noise_type', 'ornstein-uhlenbeck'),
|
71 |
+
('policy', 'MlpPolicy'),
|
72 |
+
('policy_kwargs',
|
73 |
+
'dict(net_arch=dict(pi=[300, 200], qf=[400, 300]))'),
|
74 |
+
('normalize', False)])
|
75 |
+
```
|
args.yml
ADDED
@@ -0,0 +1,83 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
!!python/object/apply:collections.OrderedDict
|
2 |
+
- - - algo
|
3 |
+
- ddpg
|
4 |
+
- - conf_file
|
5 |
+
- null
|
6 |
+
- - device
|
7 |
+
- auto
|
8 |
+
- - env
|
9 |
+
- CartpoleTwoPolesDMC-v0
|
10 |
+
- - env_kwargs
|
11 |
+
- null
|
12 |
+
- - eval_episodes
|
13 |
+
- 20
|
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 |
+
- 5
|
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 |
+
- 1214259640
|
58 |
+
- - storage
|
59 |
+
- null
|
60 |
+
- - study_name
|
61 |
+
- null
|
62 |
+
- - tensorboard_log
|
63 |
+
- runs/CartpoleTwoPolesDMC-v0__ddpg__1214259640__1673811016
|
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 |
+
- qgallouedec
|
78 |
+
- - wandb_project_name
|
79 |
+
- dmc
|
80 |
+
- - wandb_tags
|
81 |
+
- []
|
82 |
+
- - yaml_file
|
83 |
+
- null
|
config.yml
ADDED
@@ -0,0 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
!!python/object/apply:collections.OrderedDict
|
2 |
+
- - - batch_size
|
3 |
+
- 64
|
4 |
+
- - gamma
|
5 |
+
- 0.99
|
6 |
+
- - learning_rate
|
7 |
+
- 0.0001
|
8 |
+
- - n_timesteps
|
9 |
+
- 1000000.0
|
10 |
+
- - noise_std
|
11 |
+
- 0.3
|
12 |
+
- - noise_type
|
13 |
+
- ornstein-uhlenbeck
|
14 |
+
- - policy
|
15 |
+
- MlpPolicy
|
16 |
+
- - policy_kwargs
|
17 |
+
- dict(net_arch=dict(pi=[300, 200], qf=[400, 300]))
|
ddpg-CartpoleTwoPolesDMC-v0.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ab9fbee24263715cc1fff964e798779fea32842274a8744b9413e87754b8df84
|
3 |
+
size 3045715
|
ddpg-CartpoleTwoPolesDMC-v0/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
ddpg-CartpoleTwoPolesDMC-v0/actor.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d0977b53862f1e85149687341ef24c4247e1e4cdf37a1b11b1fca3901c4b12b1
|
3 |
+
size 509551
|
ddpg-CartpoleTwoPolesDMC-v0/critic.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:a5bd67b41749e2951814c6e528c7626c201c2d3b382305305cce2b6c349352d6
|
3 |
+
size 1001455
|
ddpg-CartpoleTwoPolesDMC-v0/data
ADDED
@@ -0,0 +1,137 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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 0x12a098280>",
|
8 |
+
"_build": "<function TD3Policy._build at 0x12a098310>",
|
9 |
+
"_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x12a0983a0>",
|
10 |
+
"make_actor": "<function TD3Policy.make_actor at 0x12a098430>",
|
11 |
+
"make_critic": "<function TD3Policy.make_critic at 0x12a0984c0>",
|
12 |
+
"forward": "<function TD3Policy.forward at 0x12a098550>",
|
13 |
+
"_predict": "<function TD3Policy._predict at 0x12a0985e0>",
|
14 |
+
"set_training_mode": "<function TD3Policy.set_training_mode at 0x12a098670>",
|
15 |
+
"__abstractmethods__": "frozenset()",
|
16 |
+
"_abc_impl": "<_abc._abc_data object at 0x12a084cc0>"
|
17 |
+
},
|
18 |
+
"verbose": 1,
|
19 |
+
"policy_kwargs": {
|
20 |
+
"net_arch": {
|
21 |
+
"pi": [
|
22 |
+
300,
|
23 |
+
200
|
24 |
+
],
|
25 |
+
"qf": [
|
26 |
+
400,
|
27 |
+
300
|
28 |
+
]
|
29 |
+
},
|
30 |
+
"n_critics": 1
|
31 |
+
},
|
32 |
+
"observation_space": {
|
33 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
34 |
+
":serialized:": "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",
|
35 |
+
"dtype": "float32",
|
36 |
+
"_shape": [
|
37 |
+
8
|
38 |
+
],
|
39 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
40 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
41 |
+
"bounded_below": "[False False False False False False False False]",
|
42 |
+
"bounded_above": "[False False False False False False False False]",
|
43 |
+
"_np_random": "RandomState(MT19937)"
|
44 |
+
},
|
45 |
+
"action_space": {
|
46 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
47 |
+
":serialized:": "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",
|
48 |
+
"dtype": "float32",
|
49 |
+
"_shape": [
|
50 |
+
1
|
51 |
+
],
|
52 |
+
"low": "[-1.]",
|
53 |
+
"high": "[1.]",
|
54 |
+
"bounded_below": "[ True]",
|
55 |
+
"bounded_above": "[ True]",
|
56 |
+
"_np_random": "RandomState(MT19937)"
|
57 |
+
},
|
58 |
+
"n_envs": 1,
|
59 |
+
"num_timesteps": 1000000,
|
60 |
+
"_total_timesteps": 1000000,
|
61 |
+
"_num_timesteps_at_start": 0,
|
62 |
+
"seed": 0,
|
63 |
+
"action_noise": {
|
64 |
+
":type:": "<class 'stable_baselines3.common.noise.OrnsteinUhlenbeckActionNoise'>",
|
65 |
+
":serialized:": "gAWVVQEAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5ub2lzZZSMHE9ybnN0ZWluVWhsZW5iZWNrQWN0aW9uTm9pc2WUk5QpgZR9lCiMBl90aGV0YZRHP8MzMzMzMzOMA19tdZSMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYIAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBhZSMAUOUdJRSlIwGX3NpZ21hlGgJKJYIAAAAAAAAADMzMzMzM9M/lGgQSwGFlGgUdJRSlIwDX2R0lEc/hHrhR64Ue4wNaW5pdGlhbF9ub2lzZZROjApub2lzZV9wcmV2lGgJKJYIAAAAAAAAAAAAAAAAAAAAlGgQSwGFlGgUdJRSlHViLg==",
|
66 |
+
"_theta": 0.15,
|
67 |
+
"_mu": "[0.]",
|
68 |
+
"_sigma": "[0.3]",
|
69 |
+
"_dt": 0.01,
|
70 |
+
"initial_noise": null,
|
71 |
+
"noise_prev": "[0.]"
|
72 |
+
},
|
73 |
+
"start_time": 1673811020517902764,
|
74 |
+
"learning_rate": {
|
75 |
+
":type:": "<class 'function'>",
|
76 |
+
":serialized:": "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"
|
77 |
+
},
|
78 |
+
"tensorboard_log": "runs/CartpoleTwoPolesDMC-v0__ddpg__1214259640__1673811016/CartpoleTwoPolesDMC-v0",
|
79 |
+
"lr_schedule": {
|
80 |
+
":type:": "<class 'function'>",
|
81 |
+
":serialized:": "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"
|
82 |
+
},
|
83 |
+
"_last_obs": null,
|
84 |
+
"_last_episode_starts": {
|
85 |
+
":type:": "<class 'numpy.ndarray'>",
|
86 |
+
":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
|
87 |
+
},
|
88 |
+
"_last_original_obs": {
|
89 |
+
":type:": "<class 'numpy.ndarray'>",
|
90 |
+
":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAHNieb4aC+W+s/Rkv/NzVz/CQgq/s/lkPtBTTMC+jYRAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
|
91 |
+
},
|
92 |
+
"_episode_num": 1000,
|
93 |
+
"use_sde": false,
|
94 |
+
"sde_sample_freq": -1,
|
95 |
+
"_current_progress_remaining": 0.0,
|
96 |
+
"ep_info_buffer": {
|
97 |
+
":type:": "<class 'collections.deque'>",
|
98 |
+
":serialized:": "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"
|
99 |
+
},
|
100 |
+
"ep_success_buffer": {
|
101 |
+
":type:": "<class 'collections.deque'>",
|
102 |
+
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
103 |
+
},
|
104 |
+
"_n_updates": 1000000,
|
105 |
+
"buffer_size": 1,
|
106 |
+
"batch_size": 64,
|
107 |
+
"learning_starts": 100,
|
108 |
+
"tau": 0.005,
|
109 |
+
"gamma": 0.99,
|
110 |
+
"gradient_steps": -1,
|
111 |
+
"optimize_memory_usage": false,
|
112 |
+
"replay_buffer_class": {
|
113 |
+
":type:": "<class 'abc.ABCMeta'>",
|
114 |
+
":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
|
115 |
+
"__module__": "stable_baselines3.common.buffers",
|
116 |
+
"__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 ",
|
117 |
+
"__init__": "<function ReplayBuffer.__init__ at 0x12a096dd0>",
|
118 |
+
"add": "<function ReplayBuffer.add at 0x12a096e60>",
|
119 |
+
"sample": "<function ReplayBuffer.sample at 0x12a096ef0>",
|
120 |
+
"_get_samples": "<function ReplayBuffer._get_samples at 0x12a096f80>",
|
121 |
+
"__abstractmethods__": "frozenset()",
|
122 |
+
"_abc_impl": "<_abc._abc_data object at 0x129bc6ac0>"
|
123 |
+
},
|
124 |
+
"replay_buffer_kwargs": {},
|
125 |
+
"train_freq": {
|
126 |
+
":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
|
127 |
+
":serialized:": "gAWVZAAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMB2VwaXNvZGWUhZRSlIaUgZQu"
|
128 |
+
},
|
129 |
+
"use_sde_at_warmup": false,
|
130 |
+
"policy_delay": 1,
|
131 |
+
"target_noise_clip": 0.0,
|
132 |
+
"target_policy_noise": 0.1,
|
133 |
+
"actor_batch_norm_stats": [],
|
134 |
+
"critic_batch_norm_stats": [],
|
135 |
+
"actor_batch_norm_stats_target": [],
|
136 |
+
"critic_batch_norm_stats_target": []
|
137 |
+
}
|
ddpg-CartpoleTwoPolesDMC-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:adeb0c0b3a51b420e1ee58ceb8069fe52904807d3e2246561bf1bdef8e73707c
|
3 |
+
size 1509277
|
ddpg-CartpoleTwoPolesDMC-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-CartpoleTwoPolesDMC-v0/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
- OS: macOS-13.0.1-arm64-arm-64bit Darwin Kernel Version 22.1.0: Sun Oct 9 20:14:30 PDT 2022; root:xnu-8792.41.9~2/RELEASE_ARM64_T8103
|
2 |
+
- Python: 3.10.9
|
3 |
+
- Stable-Baselines3: 1.7.0
|
4 |
+
- PyTorch: 1.13.1
|
5 |
+
- GPU Enabled: False
|
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:ec0bdad66f21c4853df39ad14aa125f2f9aa8c0657c9626d3554bb9e7b6352e7
|
3 |
+
size 284378
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 274.77902489999997, "std_reward": 23.121173462690777, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-16T08:53:27.265919"}
|
train_eval_metrics.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9c73b0d8308f04f98504116094454928883e26733dff79556ed7e85b0a56a42b
|
3 |
+
size 42859
|