1eb6137645
This is the PR for QR-DQN algorithm: https://arxiv.org/abs/1710.10044 1. add QR-DQN policy in tianshou/policy/modelfree/qrdqn.py. 2. add QR-DQN net in examples/atari/atari_network.py. 3. add QR-DQN atari example in examples/atari/atari_qrdqn.py. 4. add QR-DQN statement in tianshou/policy/init.py. 5. add QR-DQN unit test in test/discrete/test_qrdqn.py. 6. add QR-DQN atari results in examples/atari/results/qrdqn/. 7. add compute_q_value in DQNPolicy and C51Policy for simplify forward function. 8. move `with torch.no_grad():` from `_target_q` to BasePolicy By running "python3 atari_qrdqn.py --task "PongNoFrameskip-v4" --batch-size 64", get best_result': '19.8 ± 0.40', in epoch 8.
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
from tianshou.policy.base import BasePolicy
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from tianshou.policy.random import RandomPolicy
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from tianshou.policy.imitation.base import ImitationPolicy
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from tianshou.policy.modelfree.dqn import DQNPolicy
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from tianshou.policy.modelfree.c51 import C51Policy
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from tianshou.policy.modelfree.qrdqn import QRDQNPolicy
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from tianshou.policy.modelfree.pg import PGPolicy
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from tianshou.policy.modelfree.a2c import A2CPolicy
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from tianshou.policy.modelfree.ddpg import DDPGPolicy
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from tianshou.policy.modelfree.ppo import PPOPolicy
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from tianshou.policy.modelfree.td3 import TD3Policy
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from tianshou.policy.modelfree.sac import SACPolicy
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from tianshou.policy.modelfree.discrete_sac import DiscreteSACPolicy
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from tianshou.policy.imitation.discrete_bcq import DiscreteBCQPolicy
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from tianshou.policy.modelbase.psrl import PSRLPolicy
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from tianshou.policy.multiagent.mapolicy import MultiAgentPolicyManager
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__all__ = [
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"BasePolicy",
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"RandomPolicy",
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"ImitationPolicy",
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"DQNPolicy",
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"C51Policy",
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"QRDQNPolicy",
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"PGPolicy",
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"A2CPolicy",
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"DDPGPolicy",
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"PPOPolicy",
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"TD3Policy",
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"SACPolicy",
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"DiscreteSACPolicy",
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"DiscreteBCQPolicy",
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"PSRLPolicy",
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"MultiAgentPolicyManager",
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]
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