84 lines
3.2 KiB
Python
84 lines
3.2 KiB
Python
#!/usr/bin/env python3
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"""自动训练流水线 - 铸渊自管理系统
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母模型完成 → 上传COS → 启动代码模型训练 → 上传COS
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使用方法：
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export ZY_OSS_KEY=<SecretId>
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export ZY_OSS_SECRET=<SecretKey>
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nohup python3 auto_pipeline.py > pipeline.log 2>&1 &
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"""
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import os, json, time, sys, subprocess
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sys.stdout.reconfigure(line_buffering=True)
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MOTHER_LOG = "/root/autodl-tmp/train_mother.log"
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MOTHER_OUT = "/root/autodl-tmp/output/qwen25-7b-sft/final"
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COS_BUCKET = "sy-finetune-corpus-1317346199"
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COS_REGION = "ap-guangzhou"
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# 密钥通过环境变量读取（不硬编码）
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COS_SECRET_ID = os.environ.get("ZY_OSS_KEY") or os.environ.get("COS_SECRET_ID")
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COS_SECRET_KEY = os.environ.get("ZY_OSS_SECRET") or os.environ.get("COS_SECRET_KEY")
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if not COS_SECRET_ID or not COS_SECRET_KEY:
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print("❌ 需要环境变量：export ZY_OSS_KEY=... ZY_OSS_SECRET=...")
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sys.exit(1)
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CODE_MODEL = "Qwen/Qwen2.5-Coder-7B"
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CODE_CACHE = "/root/autodl-tmp/cache"
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CODE_OUT = "/root/autodl-tmp/output/qwen25-coder-7b-sft"
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CODE_SCRIPT = "/root/autodl-tmp/train_coder.py"
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DATA_FILE = "/root/autodl-tmp/data/sft.jsonl"
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POLL_INTERVAL = 300
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def run_cmd(cmd):
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r = subprocess.run(cmd, shell=True, capture_output=True, text=True)
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return r.stdout.strip(), r.returncode
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def log(msg):
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t = time.strftime("%Y-%m-%d %H:%M:%S")
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print(f"[{t}] {msg}"); sys.stdout.flush()
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def upload_to_cos(local_path, cos_key):
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log(f"Uploading {local_path} → cos://{COS_BUCKET}/{cos_key}")
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s = "from qcloud_cos import CosConfig, CosS3Client; "
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s += f"c=CosS3Client(CosConfig(Region='{COS_REGION}',SecretId='{COS_SECRET_ID}',SecretKey='{COS_SECRET_KEY}')); "
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s += f"c.upload_file(Bucket='{COS_BUCKET}',Key='{cos_key}',LocalFilePath='{local_path}')"
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out, rc = run_cmd(f"python3 -c \"{s}\"")
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log(out); return rc == 0
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def check_mother_done():
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if not os.path.exists(MOTHER_LOG): return False
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out, _ = run_cmd(f"grep -a 'DONE' {MOTHER_LOG} | tail -1")
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return "DONE" in out
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def check_mother_output():
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return os.path.isdir(MOTHER_OUT) and any(f.endswith('.safetensors') for f in os.listdir(MOTHER_OUT))
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def generate_coder_script():
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s = open("/root/autodl-tmp/train_mother.py").read()
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s = s.replace("Qwen2___5-7B", "Qwen2___5-Coder-7B")
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s = s.replace("qwen25-7b-sft", "qwen25-coder-7b-sft")
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return s
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def main():
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log("=== 自动训练流水线启动 ===")
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while True:
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if check_mother_done() or check_mother_output():
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break
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time.sleep(POLL_INTERVAL)
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log("✅ 母模型训练完成")
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if upload_to_cos(MOTHER_OUT, "models/qwen25-7b-sft/final"):
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log("✅ 母模型上传COS完成")
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with open(CODE_SCRIPT, 'w') as f: f.write(generate_coder_script())
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run_cmd(f"nohup python3 -u {CODE_SCRIPT} > train_coder.log 2>&1 &")
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log("✅ 代码模型训练已启动")
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while True:
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out, _ = run_cmd("grep -a 'DONE' /root/autodl-tmp/train_coder.log | tail -1")
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if "DONE" in out:
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log("✅ 代码模型训练完成"); break
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time.sleep(POLL_INTERVAL)
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if upload_to_cos(f"{CODE_OUT}/final", "models/qwen25-coder-7b-sft/final"):
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log("✅ 代码模型上传COS完成")
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log("🎉 全部训练完成！")
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if __name__ == "__main__":
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main()
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