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cleanrl package with the following command:pip install "cleanrl[jax,envpool,atari]"
python -m cleanrl_utils.enjoy --exp-name cleanba_ppo_envpool_procgen --env-id NinjaHard-v01curl -OL https://huggingface.co/cleanrl/NinjaHard-v0-cleanba_ppo_envpool_procgen-seed1/raw/main/cleanba_ppo_envpool_procgen.py
2curl -OL https://huggingface.co/cleanrl/NinjaHard-v0-cleanba_ppo_envpool_procgen-seed1/raw/main/pyproject.toml
3curl -OL https://huggingface.co/cleanrl/NinjaHard-v0-cleanba_ppo_envpool_procgen-seed1/raw/main/poetry.lock
4poetry install --all-extras
5python cleanba_ppo_envpool_procgen.py --distributed --track --save-model --upload-model --wandb-project-name cleanba --hf-entity cleanrl --env-id NinjaHard-v0 --seed 11{'actor_device_ids': [0],
2 'actor_devices': ['gpu:0'],
3 'anneal_lr': False,
4 'async_batch_size': 20,
5 'async_update': 3,
6 'batch_size': 61440,
7 'capture_video': False,
8 'clip_coef': 0.2,
9 'cuda': True,
10 'distributed': True,
11 'ent_coef': 0.01,
12 'env_id': 'NinjaHard-v0',
13 'exp_name': 'cleanba_ppo_envpool_procgen',
14 'gae_lambda': 0.95,
15 'gamma': 0.999,
16 'global_learner_decices': ['gpu:0', 'gpu:1', 'gpu:2', 'gpu:3'],
17 'hf_entity': 'cleanrl',
18 'learner_device_ids': [0],
19 'learner_devices': ['gpu:0'],
20 'learning_rate': 0.0005,
21 'local_batch_size': 15360,
22 'local_minibatch_size': 1920,
23 'local_num_envs': 60,
24 'local_rank': 0,
25 'max_grad_norm': 0.5,
26 'minibatch_size': 7680,
27 'norm_adv': True,
28 'num_envs': 240,
29 'num_minibatches': 8,
30 'num_steps': 256,
31 'num_updates': 1627,
32 'profile': False,
33 'save_model': True,
34 'seed': 1,
35 'target_kl': None,
36 'test_actor_learner_throughput': False,
37 'torch_deterministic': True,
38 'total_timesteps': 100000000,
39 'track': True,
40 'update_epochs': 3,
41 'upload_model': True,
42 'vf_coef': 0.5,
43 'wandb_entity': None,
44 'wandb_project_name': 'cleanba',
45 'world_size': 4}