Initial commit
Browse files- .gitattributes +1 -0
- README.md +65 -0
- args.yml +75 -0
- config.yml +21 -0
- env_kwargs.yml +1 -0
- replay.mp4 +3 -0
- results.json +1 -0
- sac-seals-Walker2d-v0.zip +3 -0
- sac-seals-Walker2d-v0/_stable_baselines3_version +1 -0
- sac-seals-Walker2d-v0/actor.optimizer.pth +3 -0
- sac-seals-Walker2d-v0/critic.optimizer.pth +3 -0
- sac-seals-Walker2d-v0/data +120 -0
- sac-seals-Walker2d-v0/ent_coef_optimizer.pth +3 -0
- sac-seals-Walker2d-v0/policy.pth +3 -0
- sac-seals-Walker2d-v0/pytorch_variables.pth +3 -0
- sac-seals-Walker2d-v0/system_info.txt +7 -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 +1,65 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: stable-baselines3
|
3 |
+
tags:
|
4 |
+
- seals/Walker2d-v0
|
5 |
+
- deep-reinforcement-learning
|
6 |
+
- reinforcement-learning
|
7 |
+
- stable-baselines3
|
8 |
+
model-index:
|
9 |
+
- name: SAC
|
10 |
+
results:
|
11 |
+
- metrics:
|
12 |
+
- type: mean_reward
|
13 |
+
value: 2271.04 +/- 496.40
|
14 |
+
name: mean_reward
|
15 |
+
task:
|
16 |
+
type: reinforcement-learning
|
17 |
+
name: reinforcement-learning
|
18 |
+
dataset:
|
19 |
+
name: seals/Walker2d-v0
|
20 |
+
type: seals/Walker2d-v0
|
21 |
+
---
|
22 |
+
|
23 |
+
# **SAC** Agent playing **seals/Walker2d-v0**
|
24 |
+
This is a trained model of a **SAC** agent playing **seals/Walker2d-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 sac --env seals/Walker2d-v0 -orga ernestumorga -f logs/
|
41 |
+
python enjoy.py --algo sac --env seals/Walker2d-v0 -f logs/
|
42 |
+
```
|
43 |
+
|
44 |
+
## Training (with the RL Zoo)
|
45 |
+
```
|
46 |
+
python train.py --algo sac --env seals/Walker2d-v0 -f logs/
|
47 |
+
# Upload the model and generate video (when possible)
|
48 |
+
python -m utils.push_to_hub --algo sac --env seals/Walker2d-v0 -f logs/ -orga ernestumorga
|
49 |
+
```
|
50 |
+
|
51 |
+
## Hyperparameters
|
52 |
+
```python
|
53 |
+
OrderedDict([('batch_size', 128),
|
54 |
+
('buffer_size', 100000),
|
55 |
+
('gamma', 0.99),
|
56 |
+
('learning_rate', 0.0005845844772048097),
|
57 |
+
('learning_starts', 1000),
|
58 |
+
('n_timesteps', 1000000.0),
|
59 |
+
('policy', 'MlpPolicy'),
|
60 |
+
('policy_kwargs',
|
61 |
+
'dict(net_arch=[400, 300], log_std_init=0.1955317469998743)'),
|
62 |
+
('tau', 0.02),
|
63 |
+
('train_freq', 1),
|
64 |
+
('normalize', False)])
|
65 |
+
```
|
args.yml
ADDED
@@ -0,0 +1,75 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
!!python/object/apply:collections.OrderedDict
|
2 |
+
- - - algo
|
3 |
+
- sac
|
4 |
+
- - device
|
5 |
+
- cpu
|
6 |
+
- - env
|
7 |
+
- seals/Walker2d-v0
|
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 |
+
- seals_experts
|
20 |
+
- - log_interval
|
21 |
+
- -1
|
22 |
+
- - n_eval_envs
|
23 |
+
- 1
|
24 |
+
- - n_evaluations
|
25 |
+
- null
|
26 |
+
- - n_jobs
|
27 |
+
- 1
|
28 |
+
- - n_startup_trials
|
29 |
+
- 10
|
30 |
+
- - n_timesteps
|
31 |
+
- -1
|
32 |
+
- - n_trials
|
33 |
+
- 500
|
34 |
+
- - no_optim_plots
|
35 |
+
- false
|
36 |
+
- - num_threads
|
37 |
+
- 4
|
38 |
+
- - optimization_log_path
|
39 |
+
- null
|
40 |
+
- - optimize_hyperparameters
|
41 |
+
- false
|
42 |
+
- - pruner
|
43 |
+
- median
|
44 |
+
- - sampler
|
45 |
+
- tpe
|
46 |
+
- - save_freq
|
47 |
+
- -1
|
48 |
+
- - save_replay_buffer
|
49 |
+
- false
|
50 |
+
- - seed
|
51 |
+
- 4294322045
|
52 |
+
- - storage
|
53 |
+
- null
|
54 |
+
- - study_name
|
55 |
+
- null
|
56 |
+
- - tensorboard_log
|
57 |
+
- ''
|
58 |
+
- - total_n_trials
|
59 |
+
- null
|
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 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
!!python/object/apply:collections.OrderedDict
|
2 |
+
- - - batch_size
|
3 |
+
- 128
|
4 |
+
- - buffer_size
|
5 |
+
- 100000
|
6 |
+
- - gamma
|
7 |
+
- 0.99
|
8 |
+
- - learning_rate
|
9 |
+
- 0.0005845844772048097
|
10 |
+
- - learning_starts
|
11 |
+
- 1000
|
12 |
+
- - n_timesteps
|
13 |
+
- 1000000.0
|
14 |
+
- - policy
|
15 |
+
- MlpPolicy
|
16 |
+
- - policy_kwargs
|
17 |
+
- dict(net_arch=[400, 300], log_std_init=0.1955317469998743)
|
18 |
+
- - tau
|
19 |
+
- 0.02
|
20 |
+
- - train_freq
|
21 |
+
- 1
|
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 sha256:91f0ab68de1f3d3d9a0db27d973f81af7f9d837479cd95f57ebb8bd42697877e
|
3 |
+
size 1339160
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"mean_reward": 2271.0352822, "std_reward": 496.3968423991559, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-11T14:33:24.793782"}
|
sac-seals-Walker2d-v0.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5af4325d09db0200ab057314517dff9ef2bc014ba30378a545f239d853b8257e
|
3 |
+
size 5801427
|
sac-seals-Walker2d-v0/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
1.5.1a8
|
sac-seals-Walker2d-v0/actor.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c2a697b3da93a10c45d907fda5f4490445076466c2b5f8ac6a895c6edb15e3b9
|
3 |
+
size 1056245
|
sac-seals-Walker2d-v0/critic.optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:1d23a9fb6bb3d39fd716bf95db5b0e02f0c5a1deaf4c7ed26df1cb5f410bb246
|
3 |
+
size 2095773
|
sac-seals-Walker2d-v0/data
ADDED
@@ -0,0 +1,120 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"policy_class": {
|
3 |
+
":type:": "<class 'abc.ABCMeta'>",
|
4 |
+
":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnNhYy5wb2xpY2llc5SMCVNBQ1BvbGljeZSTlC4=",
|
5 |
+
"__module__": "stable_baselines3.sac.policies",
|
6 |
+
"__doc__": "\n Policy class (with both actor and critic) for SAC.\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 use_sde: Whether to use State Dependent Exploration or not\n :param log_std_init: Initial value for the log standard deviation\n :param sde_net_arch: Network architecture for extracting features\n when using gSDE. If None, the latent features from the policy will be used.\n Pass an empty list to use the states as features.\n :param use_expln: Use ``expln()`` function instead of ``exp()`` when using gSDE to ensure\n a positive standard deviation (cf paper). It allows to keep variance\n above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n :param clip_mean: Clip the mean output when using gSDE to avoid numerical instability.\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 SACPolicy.__init__ at 0x7fd18c480e50>",
|
8 |
+
"_build": "<function SACPolicy._build at 0x7fd18c480ee0>",
|
9 |
+
"_get_constructor_parameters": "<function SACPolicy._get_constructor_parameters at 0x7fd18c480f70>",
|
10 |
+
"reset_noise": "<function SACPolicy.reset_noise at 0x7fd18c48b040>",
|
11 |
+
"make_actor": "<function SACPolicy.make_actor at 0x7fd18c48b0d0>",
|
12 |
+
"make_critic": "<function SACPolicy.make_critic at 0x7fd18c48b160>",
|
13 |
+
"forward": "<function SACPolicy.forward at 0x7fd18c48b1f0>",
|
14 |
+
"_predict": "<function SACPolicy._predict at 0x7fd18c48b280>",
|
15 |
+
"set_training_mode": "<function SACPolicy.set_training_mode at 0x7fd18c48b310>",
|
16 |
+
"__abstractmethods__": "frozenset()",
|
17 |
+
"_abc_impl": "<_abc_data object at 0x7fd18c47fc90>"
|
18 |
+
},
|
19 |
+
"verbose": 1,
|
20 |
+
"policy_kwargs": {
|
21 |
+
"net_arch": [
|
22 |
+
400,
|
23 |
+
300
|
24 |
+
],
|
25 |
+
"log_std_init": 0.1955317469998743,
|
26 |
+
"use_sde": false
|
27 |
+
},
|
28 |
+
"observation_space": {
|
29 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
30 |
+
":serialized:": "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",
|
31 |
+
"dtype": "float64",
|
32 |
+
"_shape": [
|
33 |
+
18
|
34 |
+
],
|
35 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf -inf]",
|
36 |
+
"high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf]",
|
37 |
+
"bounded_below": "[False False False False False False False False False False False False\n False False False False False False]",
|
38 |
+
"bounded_above": "[False False False False False False False False False False False False\n False False False False False False]",
|
39 |
+
"_np_random": null
|
40 |
+
},
|
41 |
+
"action_space": {
|
42 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
43 |
+
":serialized:": "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",
|
44 |
+
"dtype": "float32",
|
45 |
+
"_shape": [
|
46 |
+
6
|
47 |
+
],
|
48 |
+
"low": "[-1. -1. -1. -1. -1. -1.]",
|
49 |
+
"high": "[1. 1. 1. 1. 1. 1.]",
|
50 |
+
"bounded_below": "[ True True True True True True]",
|
51 |
+
"bounded_above": "[ True True True True True True]",
|
52 |
+
"_np_random": "RandomState(MT19937)"
|
53 |
+
},
|
54 |
+
"n_envs": 1,
|
55 |
+
"num_timesteps": 1000000,
|
56 |
+
"_total_timesteps": 1000000,
|
57 |
+
"_num_timesteps_at_start": 0,
|
58 |
+
"seed": 0,
|
59 |
+
"action_noise": null,
|
60 |
+
"start_time": 1651241344.563744,
|
61 |
+
"learning_rate": {
|
62 |
+
":type:": "<class 'function'>",
|
63 |
+
":serialized:": "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"
|
64 |
+
},
|
65 |
+
"tensorboard_log": null,
|
66 |
+
"lr_schedule": {
|
67 |
+
":type:": "<class 'function'>",
|
68 |
+
":serialized:": "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"
|
69 |
+
},
|
70 |
+
"_last_obs": null,
|
71 |
+
"_last_episode_starts": {
|
72 |
+
":type:": "<class 'numpy.ndarray'>",
|
73 |
+
":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
|
74 |
+
},
|
75 |
+
"_last_original_obs": {
|
76 |
+
":type:": "<class 'numpy.ndarray'>",
|
77 |
+
":serialized:": "gAWVBQEAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaQAAAAAAAAAC//w/Z8cDJAjpSZNAGt0j/NriSd3DYfQMix1T2nHwXAmmgVckMSBcCeTzo22dvoP9jMTf3l75I/RTNBWNRrkT+Q3qB5X/7pv5QIEFJCQ9Q/2G7onwr79r+gQfBkKwHzP4paArdcVpE/KB3f0JSppD+mK0y+1R8TQKDc2Hrq81q/meq9PzA0sz/Ufa1XASS5v5SMBW51bXB5lIwFZHR5cGWUk5SMAmY4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJLAUsShpSMAUOUdJRSlC4="
|
78 |
+
},
|
79 |
+
"_episode_num": 1000,
|
80 |
+
"use_sde": false,
|
81 |
+
"sde_sample_freq": -1,
|
82 |
+
"_current_progress_remaining": 0.0,
|
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:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
90 |
+
},
|
91 |
+
"_n_updates": 999000,
|
92 |
+
"buffer_size": 1,
|
93 |
+
"batch_size": 128,
|
94 |
+
"learning_starts": 1000,
|
95 |
+
"tau": 0.02,
|
96 |
+
"gamma": 0.99,
|
97 |
+
"gradient_steps": 1,
|
98 |
+
"optimize_memory_usage": false,
|
99 |
+
"replay_buffer_class": {
|
100 |
+
":type:": "<class 'abc.ABCMeta'>",
|
101 |
+
":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
|
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 0x7fd18c4d8040>",
|
105 |
+
"add": "<function ReplayBuffer.add at 0x7fd18c4d80d0>",
|
106 |
+
"sample": "<function ReplayBuffer.sample at 0x7fd18c4d8160>",
|
107 |
+
"_get_samples": "<function ReplayBuffer._get_samples at 0x7fd18c4d81f0>",
|
108 |
+
"__abstractmethods__": "frozenset()",
|
109 |
+
"_abc_impl": "<_abc_data object at 0x7fd18c559810>"
|
110 |
+
},
|
111 |
+
"replay_buffer_kwargs": {},
|
112 |
+
"train_freq": {
|
113 |
+
":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
|
114 |
+
":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLAWgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
|
115 |
+
},
|
116 |
+
"use_sde_at_warmup": false,
|
117 |
+
"target_entropy": -6.0,
|
118 |
+
"ent_coef": "auto",
|
119 |
+
"target_update_interval": 1
|
120 |
+
}
|
sac-seals-Walker2d-v0/ent_coef_optimizer.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e9798c854a970b17a108a13eda5595f22fc4b5c308bb1b1cf31ebed16257d63a
|
3 |
+
size 1191
|
sac-seals-Walker2d-v0/policy.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:66d424fa0967af24131dc4fcc1a5aae4fb20392456a641809664696a86d08ffa
|
3 |
+
size 2625861
|
sac-seals-Walker2d-v0/pytorch_variables.pth
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:ce9d404bdbb8d6b60747e399531c931d5ff79427b72feb86f672b381ca539e58
|
3 |
+
size 747
|
sac-seals-Walker2d-v0/system_info.txt
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
OS: Linux-5.4.0-121-generic-x86_64-with-glibc2.29 #137-Ubuntu SMP Wed Jun 15 13:33:07 UTC 2022
|
2 |
+
Python: 3.8.10
|
3 |
+
Stable-Baselines3: 1.5.1a8
|
4 |
+
PyTorch: 1.11.0+cu102
|
5 |
+
GPU Enabled: False
|
6 |
+
Numpy: 1.22.3
|
7 |
+
Gym: 0.21.0
|
train_eval_metrics.zip
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:6b617fef221802955270c6483ba0e5709bb7195941425e87f630ce139614b592
|
3 |
+
size 34481
|