Initial commit
Browse files- .gitattributes +2 -0
- README.md +63 -0
- args.yml +65 -0
- ars-Ant-v3.zip +3 -0
- ars-Ant-v3/_stable_baselines3_version +1 -0
- ars-Ant-v3/data +572 -0
- ars-Ant-v3/policy.pth +3 -0
- ars-Ant-v3/pytorch_variables.pth +3 -0
- ars-Ant-v3/system_info.txt +7 -0
- config.yml +19 -0
- env_kwargs.yml +1 -0
- replay.mp4 +3 -0
- results.json +1 -0
- train_eval_metrics.zip +3 -0
- vec_normalize.pkl +3 -0
.gitattributes
CHANGED
@@ -25,3 +25,5 @@ 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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vec_normalize.pkl filter=lfs diff=lfs merge=lfs -text
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README.md
ADDED
@@ -0,0 +1,63 @@
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1 |
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---
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library_name: stable-baselines3
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tags:
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- Ant-v3
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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: ARS
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results:
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- metrics:
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- type: mean_reward
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value: 2318.51 +/- 13.05
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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: Ant-v3
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type: Ant-v3
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---
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# **ARS** Agent playing **Ant-v3**
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This is a trained model of a **ARS** agent playing **Ant-v3**
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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 ars --env Ant-v3 -orga sb3 -f logs/
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python enjoy.py --algo ars --env Ant-v3 -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 ars --env Ant-v3 -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 ars --env Ant-v3 -f logs/ -orga sb3
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```
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## Hyperparameters
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```python
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OrderedDict([('alive_bonus_offset', -1),
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('delta_std', 0.025),
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('learning_rate', 0.015),
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('n_delta', 60),
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('n_envs', 16),
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('n_timesteps', 75000000.0),
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('n_top', 20),
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('normalize', 'dict(norm_obs=True, norm_reward=False)'),
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('policy', 'LinearPolicy'),
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('normalize_kwargs', {'norm_obs': True, 'norm_reward': False})])
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```
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args.yml
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@@ -0,0 +1,65 @@
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!!python/object/apply:collections.OrderedDict
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- - - algo
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- ars
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- - env
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- Ant-v3
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- - env_kwargs
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- null
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- - eval_episodes
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- 20
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- - eval_freq
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- 100000
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- - gym_packages
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- []
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- - hyperparams
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- n_envs: 16
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- - log_folder
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- rl-trained-agents/
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- - log_interval
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- 10
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- - n_eval_envs
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- 5
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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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- 10000000
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- - n_trials
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- 10
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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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- - 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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- 3734959199
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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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- false
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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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ars-Ant-v3.zip
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:9992cb04be614655b87bac323c984b690a1e7645801626d618843b33c447c23d
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size 37093
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ars-Ant-v3/_stable_baselines3_version
ADDED
@@ -0,0 +1 @@
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1.5.1a8
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ars-Ant-v3/data
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{
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"policy_class": {
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3 |
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":type:": "<class 'abc.ABCMeta'>",
|
4 |
+
":serialized:": "gASVMAAAAAAAAACMGHNiM19jb250cmliLmFycy5wb2xpY2llc5SMD0FSU0xpbmVhclBvbGljeZSTlC4=",
|
5 |
+
"__module__": "sb3_contrib.ars.policies",
|
6 |
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"__doc__": "\n Linear policy network for ARS.\n\n :param observation_space: The observation space of the environment\n :param action_space: The action space of the environment\n :param with_bias: With or without bias on the output\n :param squash_output: For continuous actions, whether the output is squashed\n or not using a ``tanh()`` function. If not squashed with tanh the output will instead be clipped.\n ",
|
7 |
+
"__init__": "<function ARSLinearPolicy.__init__ at 0x7fd2079db7a0>",
|
8 |
+
"__abstractmethods__": "frozenset()",
|
9 |
+
"_abc_impl": "<_abc_data object at 0x7fd207c9c870>"
|
10 |
+
},
|
11 |
+
"verbose": 1,
|
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+
"policy_kwargs": {},
|
13 |
+
"observation_space": {
|
14 |
+
":type:": "<class 'gym.spaces.box.Box'>",
|
15 |
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ars-Ant-v3/policy.pth
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1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:e8f26f5180ed56509cacd76422f78d11c4a6ee977f6c98f01f3dba1f9057841f
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size 4459
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ars-Ant-v3/pytorch_variables.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
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size 431
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ars-Ant-v3/system_info.txt
ADDED
@@ -0,0 +1,7 @@
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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
|
4 |
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PyTorch: 1.11.0
|
5 |
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GPU Enabled: True
|
6 |
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Numpy: 1.21.2
|
7 |
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Gym: 0.21.0
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config.yml
ADDED
@@ -0,0 +1,19 @@
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|
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!!python/object/apply:collections.OrderedDict
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2 |
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|
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|
4 |
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- 0.025
|
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- 0.015
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- - n_delta
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- 60
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- - n_envs
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- 16
|
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- - n_timesteps
|
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- 75000000.0
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- 20
|
16 |
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- - normalize
|
17 |
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- dict(norm_obs=True, norm_reward=False)
|
18 |
+
- - policy
|
19 |
+
- LinearPolicy
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env_kwargs.yml
ADDED
@@ -0,0 +1 @@
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|
1 |
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{}
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replay.mp4
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version https://git-lfs.github.com/spec/v1
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oid sha256:2a589fd15be1a489fd231fed296273826c03c4977fba0e3f524db522793e2170
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size 2474729
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results.json
ADDED
@@ -0,0 +1 @@
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train_eval_metrics.zip
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version https://git-lfs.github.com/spec/v1
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vec_normalize.pkl
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version https://git-lfs.github.com/spec/v1
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