183 lines
5.7 KiB
Python
183 lines
5.7 KiB
Python
#!/usr/bin/env python3
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"""蒸馏训练实时监控 — 在GPU服务器终端直接运行
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不刷新不覆盖,只追加新行,保持完整的输出历史。
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用法(GPU服务器上):
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cd /root/autodl-tmp
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python3 scripts/watch_distill.py
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或者直接:
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python3 /root/autodl-tmp/scripts/watch_distill.py
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"""
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import time, re, os, sys
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from datetime import datetime
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LOG = "/root/autodl-tmp/distill_mother.log"
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OUT = "/root/autodl-tmp/output/qwen25-15b-shuangyan-distill"
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def fmt_time():
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return datetime.now().strftime("%H:%M:%S")
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def get_gpu():
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"""解析nvidia-smi输出"""
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try:
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r = os.popen(
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"nvidia-smi --query-gpu=memory.used,memory.total,utilization.gpu,temperature.gpu "
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"--format=csv,noheader,nounits 2>/dev/null"
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).read().strip()
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if not r:
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return "N/A"
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parts = [p.strip() for p in r.split(", ")]
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if len(parts) >= 2:
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used, total = parts[0], parts[1]
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pct = int(used) / int(total) * 100 if int(total) > 0 else 0
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gpu_util = parts[2] if len(parts) >= 3 else "?"
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temp = parts[3] if len(parts) >= 4 else "?"
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return f"显存: {used}/{total} MiB ({pct:.0f}%) | GPU: {gpu_util}% | 温度: {temp}°C"
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return r
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except:
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return "N/A"
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def parse_loss(line):
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"""从训练日志行解析loss"""
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m = re.search(r"'loss':\s*'?([\d.]+)'?", line)
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if m:
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return float(m.group(1))
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m = re.search(r"loss[=:]\s*([\d.]+)", line)
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if m:
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return float(m.group(1))
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m = re.search(r"loss=([\d.]+)", line)
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if m:
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return float(m.group(1))
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return None
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def parse_step(line):
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"""解析训练步数和epoch"""
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m = re.search(r"(\d+)/(\d+)\s+\[", line)
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if m:
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return int(m.group(1)), int(m.group(2))
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m = re.search(r"step=(\d+)", line)
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if m:
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return int(m.group(1)), None
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return None, None
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def parse_progress(line):
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"""解析进度条百分比"""
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m = re.search(r"(\d+)%\|", line)
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if m:
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return int(m.group(1))
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return None
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def parse_eta(line):
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"""解析剩余时间"""
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m = re.search(r"<(\d+:\d+)", line)
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if m:
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return m.group(1)
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return None
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def parse_epoch(line):
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m = re.search(r"'epoch':\s*'?([\d.]+)'?", line)
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if m:
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return float(m.group(1))
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return None
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def main():
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print("=" * 60)
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print(f" 铸渊蒸馏监控 · {fmt_time()}")
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print(f" Watch: {LOG}")
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print(f" 不刷新不覆盖,只追加新行")
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print("=" * 60)
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print()
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# 先读已有日志
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last_size = 0
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if os.path.exists(LOG):
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last_size = os.path.getsize(LOG)
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with open(LOG) as f:
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for line in f:
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line = line.rstrip()
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if line:
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print(f" [{fmt_time()}] {line}")
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gpu_interval = 15 # 每15秒打一次GPU状态
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last_gpu = 0
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last_loss = None
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last_step = None
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total_steps = None
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last_epoch = None
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progress = None
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print()
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print("-" * 40)
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print(f" [{fmt_time()}] 🔄 进入实时监控模式,每2秒刷新")
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print("-" * 40)
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sys.stdout.flush()
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try:
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while True:
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now = time.time()
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# 读新增日志行
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if os.path.exists(LOG):
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new_size = os.path.getsize(LOG)
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if new_size > last_size:
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with open(LOG) as f:
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f.seek(last_size)
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for line in f:
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line = line.rstrip()
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if not line:
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continue
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print(f" [{fmt_time()}] {line}")
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# 解析关键指标
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loss = parse_loss(line)
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if loss is not None:
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last_loss = loss
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step, total = parse_step(line)
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if step is not None:
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last_step = step
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if total is not None:
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total_steps = total
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pct = parse_progress(line)
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if pct is not None:
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progress = pct
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epoch = parse_epoch(line)
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if epoch is not None:
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last_epoch = epoch
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last_size = new_size
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sys.stdout.flush()
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# 每15秒打一次GPU和进度摘要
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if now - last_gpu >= gpu_interval:
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last_gpu = now
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gpu_info = get_gpu()
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summary_parts = [f"[{fmt_time()}] 📊 {gpu_info}"]
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if last_loss is not None:
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summary_parts.append(f"loss={last_loss:.4f}")
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if last_step is not None and total_steps is not None:
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summary_parts.append(f"step={last_step}/{total_steps}")
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if last_epoch is not None:
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summary_parts.append(f"epoch={last_epoch:.2f}")
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if progress is not None:
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summary_parts.append(f"progress={progress}%")
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print(f" {' | '.join(summary_parts)}")
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sys.stdout.flush()
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time.sleep(2)
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except KeyboardInterrupt:
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print()
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print(f" [{fmt_time()}] 👋 监控已退出")
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print(f" 最后状态: loss={last_loss}, step={last_step}/{total_steps}, epoch={last_epoch}")
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sys.exit(0)
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if __name__ == "__main__":
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main()
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