gomoku_rl.policy package

Submodules

• gomoku_rl.policy.base module
  • Policy
    • Policy.REGISTRY
    • Policy.__call__()
    • Policy.__init__()
    • Policy.eval()
    • Policy.learn()
    • Policy.load_state_dict()
    • Policy.state_dict()
    • Policy.train()
• gomoku_rl.policy.common module
  • get_optimizer()
  • make_critic()
  • make_dataset_naive()
  • make_dqn_actor()
  • make_egreedy_actor()
  • make_ppo_ac()
  • make_ppo_actor()
• gomoku_rl.policy.dqn module
  • DQN
    • DQN.eval()
    • DQN.learn()
    • DQN.load_state_dict()
    • DQN.state_dict()
    • DQN.train()
  • get_replay_buffer()
• gomoku_rl.policy.ppo module
  • PPO
    • PPO.eval()
    • PPO.learn()
    • PPO.load_state_dict()
    • PPO.state_dict()
    • PPO.train()

Module contents

gomoku_rl.policy.get_policy(name: str, cfg: DictConfig, action_spec: DiscreteTensorSpec, observation_spec: TensorSpec, device='cuda') → Policy

Retrieves a policy object based on the specified policy name, configuration, action and observation specifications, and device.

Parameters:

• name (str) – The name of the policy to retrieve, which should match a key in the Policy registry.

• cfg (DictConfig) – Configuration settings for the policy, typically containing hyperparameters and other policy-specific settings.

• action_spec (DiscreteTensorSpec) – The specification of the action space, defining the shape, type, and bounds of actions the policy can take.

• observation_spec (TensorSpec) – The specification of the observation space, defining the shape and type of observations the policy will receive from the environment.

• device – The computing device (‘cuda’ or ‘cpu’) where the policy computations will be performed. Defaults to “cuda”.

Returns:

An instance of the requested policy class, initialized with the provided configurations, action and observation specifications, and device.

Return type:

Policy

gomoku_rl.policy.get_pretrained_policy(name: str, cfg: DictConfig, action_spec: DiscreteTensorSpec, observation_spec: TensorSpec, checkpoint_path: str, device='cuda') → Policy

Initializes and returns a pretrained policy object based on the specified policy name, configuration, action and observation specifications, checkpoint path, and device.

Parameters:

• name (str) – The name of the policy to be loaded, corresponding to a key in the Policy registry.

• cfg (DictConfig) – Configuration settings for the policy, typically containing hyperparameters and other policy-specific settings.

• action_spec (DiscreteTensorSpec) – The specification of the action space, detailing the shape, type, and bounds of actions the policy can execute.

• observation_spec (TensorSpec) – The specification of the observation space, detailing the shape and type of observations the policy will receive from the environment.

• checkpoint_path (str) – The file path to the saved model checkpoint from which the policy’s state should be loaded.

• device – The computing device (‘cuda’ or ‘cpu’) on which the policy computations will be executed. Defaults to “cuda”.

Returns:

An instance of the specified policy class, initialized with the provided configurations, action and observation specifications, and pretrained weights loaded from the given checkpoint path.

Return type:

Policy