112 lines
3.6 KiB
Python
112 lines
3.6 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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测试修复后的API训练日志
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"""
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import os
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import sys
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import time
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import requests
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import json
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# 设置编码环境
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os.environ['PYTHONIOENCODING'] = 'utf-8'
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def test_api_training_logs():
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"""测试API训练日志是否正常显示"""
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print("🧪 测试API训练日志修复效果")
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print("=" * 50)
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# 检查API服务器是否在运行
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try:
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response = requests.get('http://localhost:5000/api/products', timeout=5)
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if response.status_code != 200:
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print("❌ API服务器不可访问")
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return False
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print("✅ API服务器正在运行")
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except requests.exceptions.ConnectionError:
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print("❌ API服务器未启动，请先启动: PYTHONIOENCODING=utf-8 uv run server/api.py")
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return False
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except Exception as e:
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print(f"❌ API连接错误: {e}")
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return False
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# 启动训练任务
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print("\n🚀 启动训练任务...")
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training_data = {
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"product_id": "P003", # 使用不同的产品避免冲突
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"model_type": "transformer",
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"epochs": 5 # 较短的训练用于测试
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}
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try:
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response = requests.post(
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'http://localhost:5000/api/training',
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json=training_data,
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timeout=10
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)
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if response.status_code != 200:
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print(f"❌ 训练启动失败: {response.status_code}")
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print(f"响应: {response.text}")
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return False
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result = response.json()
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task_id = result.get('task_id')
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if not task_id:
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print("❌ 未获得任务ID")
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return False
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print(f"✅ 训练任务已启动: {task_id[:8]}")
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except Exception as e:
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print(f"❌ 启动训练失败: {e}")
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return False
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# 监控训练状态
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print(f"\n📊 监控训练状态 (任务: {task_id[:8]})...")
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print("检查API服务器控制台是否有训练日志输出...")
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for i in range(30): # 最多等待30秒
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try:
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response = requests.get(f'http://localhost:5000/api/training/{task_id}', timeout=5)
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if response.status_code == 200:
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status_data = response.json()
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task_status = status_data.get('data', {}).get('status', 'unknown')
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print(f"⏱️ [{i+1:2d}/30] 状态: {task_status}")
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if task_status == 'completed':
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print("✅ 训练完成!")
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metrics = status_data.get('data', {}).get('metrics')
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if metrics:
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print(f"📊 训练指标: {metrics}")
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break
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elif task_status == 'failed':
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print("❌ 训练失败!")
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error = status_data.get('data', {}).get('error')
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if error:
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print(f"错误信息: {error}")
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break
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except Exception as e:
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print(f"⚠️ 状态查询错误: {e}")
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time.sleep(2)
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print("\n" + "=" * 50)
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print("🎯 测试结果:")
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print("请检查API服务器控制台是否显示了以下类型的日志:")
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print("- [task_id] 🚀 训练进程启动")
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print("- [task_id] 📋 任务参数")
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print("- [task_id] 🤖 开始执行模型训练")
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print("- [task_id] ✅ 模型训练完成")
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print("- [task_id] 📊 训练指标")
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print("\n如果看到这些日志，说明修复成功！")
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return True
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if __name__ == "__main__":
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test_api_training_logs()
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