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cleanrl package with the following command:pip install "cleanrl[DQPN_DQN]"
python -m cleanrl_utils.enjoy --exp-name DQPN_DQN --env-id BreakoutNoFrameskip-v41curl -OL https://huggingface.co/pfunk/BreakoutNoFrameskip-v4-DQPN_DQN-seed2/raw/main/dqpn_freq_atari.py
2curl -OL https://huggingface.co/pfunk/BreakoutNoFrameskip-v4-DQPN_DQN-seed2/raw/main/pyproject.toml
3curl -OL https://huggingface.co/pfunk/BreakoutNoFrameskip-v4-DQPN_DQN-seed2/raw/main/poetry.lock
4poetry install --all-extras
5python dqpn_freq_atari.py --track --wandb-entity pfunk --wandb-project-name dqpn --capture-video true --save-model true --upload-model true --hf-entity pfunk --exp-name DQPN_DQN --target-network-frequency 1000 --policy-network-frequency 1 --seed 2 --env-id BreakoutNoFrameskip-v41{'alg_type': 'dqpn_freq_atari.py',
2 'batch_size': 32,
3 'buffer_size': 1000000,
4 'capture_video': True,
5 'cuda': True,
6 'double_learning': False,
7 'end_e': 0.05,
8 'env_id': 'BreakoutNoFrameskip-v4',
9 'exp_name': 'DQPN_DQN',
10 'exploration_fraction': 0.2,
11 'gamma': 0.99,
12 'hf_entity': 'pfunk',
13 'learning_rate': 0.0001,
14 'learning_starts': 10000,
15 'max_gradient_norm': inf,
16 'policy_network_frequency': 1,
17 'policy_tau': 1.0,
18 'save_model': True,
19 'seed': 2,
20 'start_e': 1.0,
21 'target_network_frequency': 1000,
22 'target_tau': 1.0,
23 'torch_deterministic': True,
24 'total_timesteps': 10000000,
25 'track': True,
26 'train_frequency': 1,
27 'upload_model': True,
28 'wandb_entity': 'pfunk',
29 'wandb_project_name': 'dqpn'}