Source code for embodichain.agents.rl.algo.base
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# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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# http://www.apache.org/licenses/LICENSE-2.0
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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