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https://github.com/RYDE-WORK/lnp_ml.git
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44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
import glob
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import os
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import numpy as np
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import torch
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BASE = "models/abl"
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TASKS = ["size", "delivery", "pdi", "ee", "toxic", "biodist"]
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def latest(v: str):
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dirs = sorted(glob.glob(f"{BASE}/{v}/*/"), key=os.path.getmtime)
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return dirs[-1] if dirs else None
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for v in ["moe", "llm", "both"]:
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run = latest(v)
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if run is None:
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print(f"\n=== {v}: 无 run 目录 ===")
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continue
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files = sorted(glob.glob(os.path.join(run, "**", "model.pt"), recursive=True))
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print(f"\n=== {v} ({len(files)} folds) ===")
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if not files:
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print(" 未找到 model.pt（本次 run 未保存权重 -> 无法读取门控/log_vars）")
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continue
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gm, gl = [], []
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for f in files:
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sd = torch.load(f, map_location="cpu", weights_only=False)["model_state_dict"]
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if "fusion.g_moe" in sd:
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gm.append(sd["fusion.g_moe"].item())
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if "fusion.g_llm" in sd:
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gl.append(sd["fusion.g_llm"].item())
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if gm:
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print(f" g_moe: mean={np.mean(gm):+.4f} |abs|=[{min(map(abs, gm)):.4f},{max(map(abs, gm)):.4f}]")
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if gl:
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print(f" g_llm: mean={np.mean(gl):+.4f} |abs|=[{min(map(abs, gl)):.4f},{max(map(abs, gl)):.4f}]")
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sd = torch.load(files[0], map_location="cpu", weights_only=False)["model_state_dict"]
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for t in TASKS:
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lv = sd.get(f"head.log_vars.{t}")
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if lv is not None:
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print(f" {t:9s} log_var={lv.item():+.3f} eff_w={np.exp(-lv.item()):.3f}") |