Quentin Gallouédec
commited on
Commit
·
39014d1
1
Parent(s):
ee52f60
Initial commit
Browse files- .gitattributes +1 -0
- README.md +75 -0
- args.yml +83 -0
- config.yml +17 -0
- ddpg-CartpoleThreePolesDMC-v0.zip +3 -0
- ddpg-CartpoleThreePolesDMC-v0/_stable_baselines3_version +1 -0
- ddpg-CartpoleThreePolesDMC-v0/actor.optimizer.pth +3 -0
- ddpg-CartpoleThreePolesDMC-v0/critic.optimizer.pth +3 -0
- ddpg-CartpoleThreePolesDMC-v0/data +137 -0
- ddpg-CartpoleThreePolesDMC-v0/policy.pth +3 -0
- ddpg-CartpoleThreePolesDMC-v0/pytorch_variables.pth +3 -0
- ddpg-CartpoleThreePolesDMC-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 |
+
- CartpoleThreePolesDMC-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: CartpoleThreePolesDMC-v0
|
16 |
+
type: CartpoleThreePolesDMC-v0
|
17 |
+
metrics:
|
18 |
+
- type: mean_reward
|
19 |
+
value: 161.39 +/- 18.53
|
20 |
+
name: mean_reward
|
21 |
+
verified: false
|
22 |
+
---
|
23 |
+
|
24 |
+
# **DDPG** Agent playing **CartpoleThreePolesDMC-v0**
|
25 |
+
This is a trained model of a **DDPG** agent playing **CartpoleThreePolesDMC-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 CartpoleThreePolesDMC-v0 -orga qgallouedec -f logs/
|
47 |
+
python -m rl_zoo3.enjoy --algo ddpg --env CartpoleThreePolesDMC-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 CartpoleThreePolesDMC-v0 -orga qgallouedec -f logs/
|
53 |
+
python -m rl_zoo3.enjoy --algo ddpg --env CartpoleThreePolesDMC-v0 -f logs/
|
54 |
+
```
|
55 |
+
|
56 |
+
## Training (with the RL Zoo)
|
57 |
+
```
|
58 |
+
python -m rl_zoo3.train --algo ddpg --env CartpoleThreePolesDMC-v0 -f logs/
|
59 |
+
# Upload the model and generate video (when possible)
|
60 |
+
python -m rl_zoo3.push_to_hub --algo ddpg --env CartpoleThreePolesDMC-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 |
+
- CartpoleThreePolesDMC-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 |
+
- 2863243049
|
58 |
+
- - storage
|
59 |
+
- null
|
60 |
+
- - study_name
|
61 |
+
- null
|
62 |
+
- - tensorboard_log
|
63 |
+
- runs/CartpoleThreePolesDMC-v0__ddpg__2863243049__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-CartpoleThreePolesDMC-v0.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6682fc9f8c74a0c2f0c4791f49a7f451986143ccc3a285f25a969c9a1c5afff1
|
3 |
+
size 3079567
|
ddpg-CartpoleThreePolesDMC-v0/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.7.0
|
ddpg-CartpoleThreePolesDMC-v0/actor.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5fdad91fdbb843d83ad5415132b803d8e163739f1b601ed41f915e35e2bf6276
|
3 |
+
size 516783
|
ddpg-CartpoleThreePolesDMC-v0/critic.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b6ac71a173d12300725f31f62573c3c051fa8d48b4095b06531ce0999da42313
|
3 |
+
size 1011055
|
ddpg-CartpoleThreePolesDMC-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 0x13b298280>",
|
8 |
+
"_build": "<function TD3Policy._build at 0x13b298310>",
|
9 |
+
"_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x13b2983a0>",
|
10 |
+
"make_actor": "<function TD3Policy.make_actor at 0x13b298430>",
|
11 |
+
"make_critic": "<function TD3Policy.make_critic at 0x13b2984c0>",
|
12 |
+
"forward": "<function TD3Policy.forward at 0x13b298550>",
|
13 |
+
"_predict": "<function TD3Policy._predict at 0x13b2985e0>",
|
14 |
+
"set_training_mode": "<function TD3Policy.set_training_mode at 0x13b298670>",
|
15 |
+
"__abstractmethods__": "frozenset()",
|
16 |
+
"_abc_impl": "<_abc._abc_data object at 0x13b293300>"
|
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 |
+
11
|
38 |
+
],
|
39 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf]",
|
40 |
+
"high": "[inf inf inf inf inf inf inf inf inf inf inf]",
|
41 |
+
"bounded_below": "[False False False False False False False False False False False]",
|
42 |
+
"bounded_above": "[False False False 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": 1673811020512674722,
|
74 |
+
"learning_rate": {
|
75 |
+
":type:": "<class 'function'>",
|
76 |
+
":serialized:": "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"
|
77 |
+
},
|
78 |
+
"tensorboard_log": "runs/CartpoleThreePolesDMC-v0__ddpg__4058568227__1673811016/CartpoleThreePolesDMC-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:": "gAWVoQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYsAAAAAAAAAJMjy78G7WW/fx/hvtqMjD5YKnY/LAVHP70EIT/3co2/e3m0wMikBr8OGr88lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwuGlIwBQ5R0lFKULg=="
|
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 0x13b296dd0>",
|
118 |
+
"add": "<function ReplayBuffer.add at 0x13b296e60>",
|
119 |
+
"sample": "<function ReplayBuffer.sample at 0x13b296ef0>",
|
120 |
+
"_get_samples": "<function ReplayBuffer._get_samples at 0x13b296f80>",
|
121 |
+
"__abstractmethods__": "frozenset()",
|
122 |
+
"_abc_impl": "<_abc._abc_data object at 0x13b232c40>"
|
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-CartpoleThreePolesDMC-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:dc2f3ecdb0a39256f91c4cd3611fcbd01204e8d655bcd3c102c2d20f14d4abdb
|
3 |
+
size 1526173
|
ddpg-CartpoleThreePolesDMC-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-CartpoleThreePolesDMC-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 sha256:9d6c947385e563a0373e0234a8a42613595d5ff7c09bcb56132c11bcc62b3727
|
3 |
+
size 307839
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 161.3868718, "std_reward": 18.531300157185605, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-01-16T08:54:18.855099"}
|
train_eval_metrics.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:96b7c99d885a4f30483955e58ea170452c6d5dfb2ef65117bdf5ed7a070628b0
|
3 |
+
size 42832
|