Initial commit
Browse files- .gitattributes +1 -0
- README.md +65 -0
- args.yml +59 -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 +125 -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
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@@ -25,3 +25,4 @@ 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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*.zstandard 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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*.zstandard 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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- metrics:
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- type: mean_reward
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value: 223.87 +/- 80.41
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name: mean_reward
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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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---
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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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```
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# Download model and save it into the logs/ folder
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python -m utils.load_from_hub --algo ddpg --env LunarLanderContinuous-v2 -orga sb3 -f logs/
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python enjoy.py --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 train.py --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 utils.push_to_hub --algo ddpg --env LunarLanderContinuous-v2 -f logs/ -orga sb3
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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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- - 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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- 10
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- - eval_freq
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- 10000
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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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- rl-trained-agents/
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- - log_interval
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- -1
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- - n_evaluations
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- 20
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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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- 10
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- - num_threads
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- -1
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- - optimize_hyperparameters
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- false
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- - pruner
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- median
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- - sampler
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- 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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- 2972747770
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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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- ''
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- - trained_agent
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- ''
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- - truncate_last_trajectory
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- true
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- - uuid
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- true
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- - vec_env
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- dummy
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- - verbose
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- 1
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config.yml
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+
!!python/object/apply:collections.OrderedDict
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- - - buffer_size
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- 200000
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+
- - gamma
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5 |
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- 0.98
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- - gradient_steps
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- -1
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- - learning_rate
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- 0.001
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+
- - learning_starts
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- 10000
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+
- - n_timesteps
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- 300000.0
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+
- - noise_std
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- 0.1
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- - noise_type
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- normal
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+
- - policy
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- MlpPolicy
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- - policy_kwargs
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- dict(net_arch=[400, 300])
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- - 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:a633dd6acea02743c250b086396977b00ac3edc25dfb4ba3ee86d7ae7a67b5af
|
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+
size 4027831
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ddpg-LunarLanderContinuous-v2/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
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+
1.5.1a8
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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 sha256:8f4f6a25222be61502e7419cb58e28d79af8402fc448adb4c58ff412e76df394
|
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+
size 999361
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ddpg-LunarLanderContinuous-v2/critic.optimizer.pth
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+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8a483ecdfee220adbebcc0572ad55b6ec62e0aeb212399567ec780a7d135e6ca
|
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+
size 1003329
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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'>",
|
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+
":serialized:": "gASVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLnRkMy5wb2xpY2llc5SMCVREM1BvbGljeZSTlC4=",
|
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+
"__module__": "stable_baselines3.td3.policies",
|
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"__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 ",
|
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+
"__init__": "<function TD3Policy.__init__ at 0x7fef9ae00170>",
|
8 |
+
"_build": "<function TD3Policy._build at 0x7fef9ae00200>",
|
9 |
+
"_get_constructor_parameters": "<function TD3Policy._get_constructor_parameters at 0x7fef9ae00290>",
|
10 |
+
"make_actor": "<function TD3Policy.make_actor at 0x7fef9ae00320>",
|
11 |
+
"make_critic": "<function TD3Policy.make_critic at 0x7fef9ae003b0>",
|
12 |
+
"forward": "<function TD3Policy.forward at 0x7fef9ae00440>",
|
13 |
+
"_predict": "<function TD3Policy._predict at 0x7fef9ae004d0>",
|
14 |
+
"set_training_mode": "<function TD3Policy.set_training_mode at 0x7fef9ae00560>",
|
15 |
+
"__abstractmethods__": "frozenset()",
|
16 |
+
"_abc_impl": "<_abc_data object at 0x7fef9adfe1b0>"
|
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+
},
|
18 |
+
"verbose": 1,
|
19 |
+
"policy_kwargs": {
|
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+
"net_arch": [
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400,
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+
300
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+
],
|
24 |
+
"n_critics": 1
|
25 |
+
},
|
26 |
+
"observation_space": {
|
27 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
28 |
+
":serialized:": "gASVwwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMA2xvd5SMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMDF9yZWNvbnN0cnVjdJSTlGgGjAduZGFycmF5lJOUSwCFlEMBYpSHlFKUKEsBSwiFlGgKiUMgAACA/wAAgP8AAID/AACA/wAAgP8AAID/AACA/wAAgP+UdJRijARoaWdolGgQaBJLAIWUaBSHlFKUKEsBSwiFlGgKiUMgAACAfwAAgH8AAIB/AACAfwAAgH8AAIB/AACAfwAAgH+UdJRijA1ib3VuZGVkX2JlbG93lGgQaBJLAIWUaBSHlFKUKEsBSwiFlGgHjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiiUMIAAAAAAAAAACUdJRijA1ib3VuZGVkX2Fib3ZllGgQaBJLAIWUaBSHlFKUKEsBSwiFlGgoiUMIAAAAAAAAAACUdJRijApfbnBfcmFuZG9tlE6MBl9zaGFwZZRLCIWUdWIu",
|
29 |
+
"dtype": "float32",
|
30 |
+
"low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
|
31 |
+
"high": "[inf inf inf inf inf inf inf inf]",
|
32 |
+
"bounded_below": "[False False False False False False False False]",
|
33 |
+
"bounded_above": "[False False False False False False False False]",
|
34 |
+
"_np_random": null,
|
35 |
+
"_shape": [
|
36 |
+
8
|
37 |
+
]
|
38 |
+
},
|
39 |
+
"action_space": {
|
40 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
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ddpg-LunarLanderContinuous-v2/policy.pth
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ddpg-LunarLanderContinuous-v2/pytorch_variables.pth
ADDED
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ddpg-LunarLanderContinuous-v2/system_info.txt
ADDED
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OS: Linux-5.13.0-44-generic-x86_64-with-debian-bullseye-sid #49~20.04.1-Ubuntu SMP Wed May 18 18:44:28 UTC 2022
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Python: 3.7.10
|
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Stable-Baselines3: 1.5.1a8
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PyTorch: 1.11.0
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GPU Enabled: True
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Numpy: 1.21.2
|
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Gym: 0.21.0
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env_kwargs.yml
ADDED
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{}
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replay.mp4
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{"mean_reward": 223.86709460000003, "std_reward": 80.40817956608241, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-06-02T22:39:30.763660"}
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