Source code for embodichain.agents.rl.algo.base

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from __future__ import annotations

from typing import Dict, Any, Callable
import torch


[docs] class BaseAlgorithm: """Base class for RL algorithms. Algorithms must implement buffer initialization, rollout collection, and policy update. Trainer depends only on this interface to remain algorithm-agnostic. """ device: torch.device
[docs] def initialize_buffer( self, num_steps: int, num_envs: int, obs_dim: int, action_dim: int ) -> None: """Initialize internal buffer(s) required by the algorithm.""" raise NotImplementedError
[docs] def collect_rollout( self, env, policy, obs: torch.Tensor, num_steps: int, on_step_callback: Callable | None = None, ) -> Dict[str, Any]: """Collect trajectories and return logging info (e.g., reward components).""" raise NotImplementedError
[docs] def update(self) -> Dict[str, float]: """Update policy using collected data and return training losses.""" raise NotImplementedError