97 lines
3.0 KiB
Python
97 lines
3.0 KiB
Python
#!/usr/bin/env python3
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# -*- coding: UTF-8 -*-
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###########################################################################
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# Copyright © 1998 - 2026 Tencent. All Rights Reserved.
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###########################################################################
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"""
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Author: Tencent AI Arena Authors
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Robot Vacuum DIY Agent class based on kaiwudrl BaseAgent interface.
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清扫大作战 DIY Agent 主类，基于 kaiwudrl BaseAgent 接口。
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"""
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import torch
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from kaiwudrl.interface.agent import BaseAgent
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from agent_diy.model.model import Model
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from agent_diy.conf.conf import Config
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class Agent(BaseAgent):
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def __init__(self, agent_type="player", device=None, logger=None, monitor=None):
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"""Initialize the agent.
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初始化 Agent。
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"""
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super().__init__(agent_type, device, logger, monitor)
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def predict(self, list_obs_data):
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"""Predict action from observation data.
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根据观测数据推理动作。
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"""
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pass
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def exploit(self, list_obs_data):
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"""Evaluation mode inference (greedy).
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评估模式推理（贪心）。
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"""
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pass
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def learn(self, list_sample_data):
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"""Train the model.
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训练模型。
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"""
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pass
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def save_model(self, path=None, id="1"):
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"""Save model checkpoint.
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保存模型检查点。
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"""
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pass
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def load_model(self, path=None, id="1"):
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"""Load model checkpoint.
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加载模型检查点。
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"""
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pass
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def observation_process(self, obs, preprocessor, extra_info=None):
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"""
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This function is an important feature processing function, mainly responsible for:
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- Parsing information in the raw data
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- Parsing preprocessed feature data
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- Processing the features and returning the processed feature vector
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- Concatenation of features
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- Annotation of legal actions
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Function inputs:
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- obs: Local observation information returned by the environment
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- preprocessor: Preprocessor
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- extra_info: Global information returned by the environment
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Function outputs:
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- ObsData: Observation data for model inference
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- remain_info: Other data for reward calculation
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该函数是特征处理的重要函数, 主要负责：
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- 解析原始数据里的信息
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- 解析预处理后的特征数据
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- 对特征进行处理, 并返回处理后的特征向量
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- 特征的拼接
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- 合法动作的标注
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函数的输入：
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- obs: 环境返回的局部观测信息
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- preprocessor: 预处理器
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- extra_info: 环境返回的全局状态信息
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函数的输出：
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- ObsData: 用于模型推理的观测数据
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- remain_info: 用于奖励计算的其他数据
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"""
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pass
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def action_process(self, act_data):
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pass
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