Quentin Gallouédec
commited on
Commit
•
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Parent(s):
e6b6967
Initial commit
Browse files- .gitattributes +1 -0
- README.md +77 -0
- args.yml +81 -0
- config.yml +24 -0
- ddpg-LunarLanderContinuous-v2.zip +3 -0
- ddpg-LunarLanderContinuous-v2/_stable_baselines3_version +1 -0
- ddpg-LunarLanderContinuous-v2/actor.optimizer.pth +3 -0
- ddpg-LunarLanderContinuous-v2/critic.optimizer.pth +3 -0
- ddpg-LunarLanderContinuous-v2/data +135 -0
- ddpg-LunarLanderContinuous-v2/policy.pth +3 -0
- ddpg-LunarLanderContinuous-v2/pytorch_variables.pth +3 -0
- ddpg-LunarLanderContinuous-v2/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
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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library_name: stable-baselines3
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tags:
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- LunarLanderContinuous-v2
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- deep-reinforcement-learning
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- reinforcement-learning
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- stable-baselines3
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model-index:
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- name: DDPG
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results:
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- task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: LunarLanderContinuous-v2
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type: LunarLanderContinuous-v2
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metrics:
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- type: mean_reward
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value: 240.06 +/- 89.35
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name: mean_reward
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verified: false
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---
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# **DDPG** Agent playing **LunarLanderContinuous-v2**
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This is a trained model of a **DDPG** agent playing **LunarLanderContinuous-v2**
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using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
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and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
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The RL Zoo is a training framework for Stable Baselines3
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reinforcement learning agents,
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with hyperparameter optimization and pre-trained agents included.
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## Usage (with SB3 RL Zoo)
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RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
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SB3: https://github.com/DLR-RM/stable-baselines3<br/>
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SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
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Install the RL Zoo (with SB3 and SB3-Contrib):
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```bash
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pip install rl_zoo3
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```
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```
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# Download model and save it into the logs/ folder
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python -m rl_zoo3.load_from_hub --algo ddpg --env LunarLanderContinuous-v2 -orga qgallouedec -f logs/
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python -m rl_zoo3.enjoy --algo ddpg --env LunarLanderContinuous-v2 -f logs/
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```
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If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
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```
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python -m rl_zoo3.load_from_hub --algo ddpg --env LunarLanderContinuous-v2 -orga qgallouedec -f logs/
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python -m rl_zoo3.enjoy --algo ddpg --env LunarLanderContinuous-v2 -f logs/
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```
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## Training (with the RL Zoo)
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```
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python -m rl_zoo3.train --algo ddpg --env LunarLanderContinuous-v2 -f logs/
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# Upload the model and generate video (when possible)
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python -m rl_zoo3.push_to_hub --algo ddpg --env LunarLanderContinuous-v2 -f logs/ -orga qgallouedec
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```
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## Hyperparameters
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```python
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OrderedDict([('buffer_size', 200000),
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('gamma', 0.98),
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('gradient_steps', -1),
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('learning_rate', 0.001),
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('learning_starts', 10000),
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('n_timesteps', 300000.0),
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('noise_std', 0.1),
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('noise_type', 'normal'),
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('policy', 'MlpPolicy'),
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('policy_kwargs', 'dict(net_arch=[400, 300])'),
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('train_freq', [1, 'episode']),
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('normalize', False)])
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```
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args.yml
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!!python/object/apply:collections.OrderedDict
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- - - algo
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- ddpg
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- - conf_file
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- null
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- - device
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- auto
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- - env
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- LunarLanderContinuous-v2
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- - env_kwargs
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- null
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- - eval_episodes
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- 5
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- - eval_freq
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- 25000
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- - gym_packages
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- []
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- - hyperparams
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- null
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- - log_folder
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- logs
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- - log_interval
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- -1
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- - max_total_trials
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- null
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+
- - n_eval_envs
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- 1
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- - n_evaluations
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- null
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+
- - n_jobs
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- 1
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+
- - n_startup_trials
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- 10
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+
- - n_timesteps
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- -1
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+
- - n_trials
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- 500
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+
- - no_optim_plots
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+
- false
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+
- - num_threads
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+
- -1
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+
- - optimization_log_path
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- null
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+
- - optimize_hyperparameters
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- false
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+
- - progress
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+
- false
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48 |
+
- - pruner
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49 |
+
- median
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+
- - sampler
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51 |
+
- tpe
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+
- - save_freq
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+
- -1
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+
- - save_replay_buffer
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+
- false
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+
- - seed
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+
- 2756518495
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+
- - storage
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+
- null
|
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+
- - study_name
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+
- null
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+
- - tensorboard_log
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+
- runs/LunarLanderContinuous-v2__ddpg__2756518495__1671825121
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+
- - track
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65 |
+
- true
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66 |
+
- - trained_agent
|
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+
- ''
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68 |
+
- - truncate_last_trajectory
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+
- true
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+
- - uuid
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71 |
+
- false
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+
- - vec_env
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73 |
+
- dummy
|
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+
- - verbose
|
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+
- 1
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+
- - wandb_entity
|
77 |
+
- openrlbenchmark
|
78 |
+
- - wandb_project_name
|
79 |
+
- sb3
|
80 |
+
- - yaml_file
|
81 |
+
- null
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config.yml
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+
!!python/object/apply:collections.OrderedDict
|
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+
- - - 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
|
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+
- - noise_type
|
17 |
+
- normal
|
18 |
+
- - policy
|
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+
- MlpPolicy
|
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+
- - policy_kwargs
|
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+
- dict(net_arch=[400, 300])
|
22 |
+
- - train_freq
|
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+
- - 1
|
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+
- episode
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ddpg-LunarLanderContinuous-v2.zip
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version https://git-lfs.github.com/spec/v1
|
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+
oid sha256:a32e005edb593687ef24cebd30dc851c7873debfdd35ef861307b840f529fc7f
|
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+
size 4031261
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ddpg-LunarLanderContinuous-v2/_stable_baselines3_version
ADDED
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+
1.8.0a6
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ddpg-LunarLanderContinuous-v2/actor.optimizer.pth
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+
version https://git-lfs.github.com/spec/v1
|
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+
oid sha256:c6be0e35aa47a1b07125f686ebdb5a2cae6c6e9bdce8620350ee6f542531e6cf
|
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+
size 1000879
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ddpg-LunarLanderContinuous-v2/critic.optimizer.pth
ADDED
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+
version https://git-lfs.github.com/spec/v1
|
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+
oid sha256:58af5a1a76c97ba96857389ef9c876f60f701d1ae77a5551cf371ed4134e5a6d
|
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+
size 1004847
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ddpg-LunarLanderContinuous-v2/data
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{
|
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+
"policy_class": {
|
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+
":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 0x7f47cedee940>",
|
8 |
+
"_build": "<function TD3Policy._build at 0x7f47cedee9d0>",
|
9 |
+
"_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7f47cedeea60>",
|
10 |
+
"make_actor": "<function TD3Policy.make_actor at 0x7f47cedeeaf0>",
|
11 |
+
"make_critic": "<function TD3Policy.make_critic at 0x7f47cedeeb80>",
|
12 |
+
"forward": "<function TD3Policy.forward at 0x7f47cedeec10>",
|
13 |
+
"_predict": "<function TD3Policy._predict at 0x7f47cedeeca0>",
|
14 |
+
"set_training_mode": "<function TD3Policy.set_training_mode at 0x7f47cedeed30>",
|
15 |
+
"__abstractmethods__": "frozenset()",
|
16 |
+
"_abc_impl": "<_abc._abc_data object at 0x7f47cf217340>"
|
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 |
+
8
|
32 |
+
],
|
33 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
34 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
35 |
+
"bounded_below": "[False False False False False False False False]",
|
36 |
+
"bounded_above": "[False False False False False False False False]",
|
37 |
+
"_np_random": null
|
38 |
+
},
|
39 |
+
"action_space": {
|
40 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
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- 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
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