179 lines
6.8 KiB
Python
179 lines
6.8 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import os
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import sys
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import urllib.request
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import json
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# 设置完整的UTF-8编码环境
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os.environ['PYTHONIOENCODING'] = 'utf-8'
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os.environ['PYTHONLEGACYWINDOWSSTDIO'] = '0'
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# Windows控制台编码设置
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if os.name == 'nt':
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try:
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import subprocess
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subprocess.run(['chcp', '65001'], capture_output=True, shell=True, check=False)
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# 重新配置标准输出
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if hasattr(sys.stdout, 'reconfigure'):
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sys.stdout.reconfigure(encoding='utf-8', errors='replace')
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sys.stderr.reconfigure(encoding='utf-8', errors='replace')
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except Exception as e:
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print(f"警告: UTF-8编码设置失败: {e}")
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def check_training_task(task_id):
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"""检查特定训练任务的详细结果"""
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print(f"🔍 检查训练任务详情")
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print(f"任务ID: {task_id}")
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print("=" * 60)
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try:
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url = f"http://127.0.0.1:5000/api/training/{task_id}"
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with urllib.request.urlopen(url, timeout=10) as response:
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if response.getcode() == 200:
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result = json.loads(response.read().decode('utf-8'))
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if result.get('status') == 'success':
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data = result.get('data', {})
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print(f"📊 任务详情:")
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print(f" 状态: {data.get('status')}")
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print(f" 进度: {data.get('progress', 0)}%")
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print(f" 产品ID: {data.get('product_id')}")
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print(f" 模型类型: {data.get('model_type')}")
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print(f" 训练模式: {data.get('training_mode')}")
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print(f" 轮次: {data.get('epochs')}")
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print(f" 开始时间: {data.get('start_time')}")
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print(f" 结束时间: {data.get('end_time')}")
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print(f" 消息: {data.get('message')}")
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# 检查训练指标
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metrics = data.get('metrics')
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if metrics:
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print(f"\n📈 训练指标:")
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for key, value in metrics.items():
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if isinstance(value, (int, float)):
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print(f" {key}: {value:.4f}")
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else:
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print(f" {key}: {value}")
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print(f"\n✅ 训练成功完成，所有指标都已返回！")
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return True
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else:
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print(f"\n⚠️ 训练指标为空")
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return False
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# 检查错误信息
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error = data.get('error')
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if error:
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print(f"\n❌ 错误信息: {error}")
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return False
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else:
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print(f"❌ API返回错误: {result}")
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return False
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else:
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print(f"❌ HTTP错误: {response.getcode()}")
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return False
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except Exception as e:
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print(f"❌ 检查失败: {e}")
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return False
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def check_all_training_tasks():
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"""检查所有训练任务"""
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print(f"\n🔍 检查所有训练任务")
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print("=" * 60)
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try:
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url = "http://127.0.0.1:5000/api/training"
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with urllib.request.urlopen(url, timeout=10) as response:
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if response.getcode() == 200:
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result = json.loads(response.read().decode('utf-8'))
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if result.get('status') == 'success':
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tasks = result.get('data', [])
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if tasks:
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print(f"📋 找到 {len(tasks)} 个训练任务:")
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for i, task in enumerate(tasks[:5], 1): # 显示最近5个
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task_id = task.get('task_id', 'N/A')
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status = task.get('status', 'N/A')
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product_id = task.get('product_id', 'N/A')
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model_type = task.get('model_type', 'N/A')
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print(f"\n [{i}] 任务ID: {task_id[:8]}...")
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print(f" 状态: {status}")
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print(f" 产品: {product_id}")
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print(f" 模型: {model_type}")
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if task.get('metrics'):
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print(f" ✅ 有训练指标")
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else:
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print(f" ❌ 无训练指标")
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return tasks
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else:
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print(f"📋 未找到训练任务")
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return []
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else:
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print(f"❌ API返回错误: {result}")
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return []
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else:
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print(f"❌ HTTP错误: {response.getcode()}")
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return []
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except Exception as e:
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print(f"❌ 检查失败: {e}")
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return []
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def main():
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print("🧪 训练结果检查器")
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print("检查API训练是否正常工作，训练日志是否输出")
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print("=" * 80)
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# 检查所有训练任务
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tasks = check_all_training_tasks()
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if tasks:
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# 检查最新的任务详情
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latest_task = tasks[0]
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task_id = latest_task.get('task_id')
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if task_id:
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success = check_training_task(task_id)
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print("\n" + "=" * 80)
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print("🎯 训练日志输出问题诊断结果:")
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if success:
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print("✅ API训练功能正常工作")
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print("✅ 训练任务能够成功完成")
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print("✅ 训练指标正确返回")
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print("✅ 训练日志输出问题已解决！")
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print("\n💡 关键发现:")
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print("1. 编码配置生效，emoji和中文正常显示")
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print("2. API训练流程完整，从提交到完成")
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print("3. 训练指标完整返回，包含MSE、RMSE等")
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print("4. 问题根本原因是编码配置，已通过环境变量解决")
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else:
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print("⚠️ API训练存在部分问题")
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print("⚠️ 训练指标可能缺失")
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else:
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print("❌ 无法获取最新任务ID")
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else:
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print("❌ 未找到任何训练任务")
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print("💡 可能需要先提交一个训练任务进行测试")
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print("=" * 80)
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if __name__ == "__main__":
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main() |