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hyperparameter-tuning
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parameter_usage_example.py
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parameter_usage_example.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
使用新参数系统的示例
展示如何在autodl.py和其他模块中使用统一参数管理系统
"""
# 方法1: 使用原有的settings()函数(推荐,保持兼容性)
from parms_setting import settings
def main_with_settings():
"""使用settings()函数的方式"""
args = settings()
print(f"任务类型: {args.task_type}")
print(f"最大迭代次数: {getattr(args, 'max_iterations', '未设置')}")
print(f"随机种子: {getattr(args, 'random_seed', '未设置')}")
print(f"训练轮数: {args.epochs}")
# 方法2: 直接使用参数管理器(高级用法)
from parameter_manager import get_parameter_manager
from unified_parameter_registry import initialize_unified_parameters
def main_with_manager():
"""使用参数管理器的方式"""
# 初始化系统
initialize_unified_parameters()
# 获取管理器
manager = get_parameter_manager()
# 解析参数
args = manager.parse_arguments()
print(f"任务类型: {args.task_type}")
print(f"最大迭代次数: {args.max_iterations}")
print(f"随机种子: {args.random_seed}")
print(f"训练轮数: {args.epochs}")
# 方法3: 使用参数代理(延迟加载)
from parameter_manager import get_parameter_proxy
def main_with_proxy():
"""使用参数代理的方式"""
proxy = get_parameter_proxy()
# 延迟访问参数
task_type = proxy.get('task_type', 'LDA')
max_iterations = proxy.get('max_iterations', 50)
print(f"任务类型: {task_type}")
print(f"最大迭代次数: {max_iterations}")
if __name__ == "__main__":
print("=== 方法1: 使用settings()函数 ===")
main_with_settings()
print("\n=== 方法2: 使用参数管理器 ===")
# main_with_manager() # 注释掉避免重复解析
print("\n=== 方法3: 使用参数代理 ===")
main_with_proxy()
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