LAV2_navrl

SKRL configuration for the LAV2 NavRL task.

Classes:

Name	Description
`Shared`	Shared actor-critic model with sensor fusion.

Functions:

Name	Description
`get_agent_cfg`	Return the PPO agent configuration.
`get_model_class`	Return the model class for the agent.
`get_agent_class`	Return the agent class.
`get_memory_class`	Return the memory class.
`get_memory_cfg`	Return the memory configuration.
`get_trainer_class`	Return the trainer class.
`get_trainer_cfg`	Return the trainer configuration.

Shared

Shared(observation_space, state_space, action_space, device, clip_actions=False, clip_log_std=True, min_log_std=-20, max_log_std=2, reduction='sum')

Bases: GaussianMixin, DeterministicMixin, Model

Shared actor-critic model with sensor fusion.

Initialize encoders and policy/value heads.

Methods:

Name	Description
`act`	Compute actions or values depending on role.
`compute`	Compute policy/value outputs depending on role.

act(inputs: Any, role: str) -> Any

Compute actions or values depending on role.

Returns:

Type	Description
`Any`	tuple \| None: Action outputs for the given role, or `None` if role is unknown.

compute(inputs: Any, role: str) -> Any

Compute policy/value outputs depending on role.

Returns:

Type	Description
`Any`	tuple \| None: `(output_tensor, extras_dict)` for policy/value roles, or `None`.

get_agent_cfg() -> Any

Return the PPO agent configuration.

get_model_class() -> Any

Return the model class for the agent.

get_agent_class() -> Any

Return the agent class.

get_memory_class() -> Any

Return the memory class.

get_memory_cfg() -> Any

Return the memory configuration.

get_trainer_class() -> Any

Return the trainer class.

get_trainer_cfg() -> Any

Return the trainer configuration.