mirror of
https://github.com/RYDE-WORK/lnp_ml.git
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46 lines
1.6 KiB
Python
46 lines
1.6 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 = os.environ.get("GATES_BASE", "models/abl")
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VARIANTS = os.environ.get("GATES_VARIANTS", "moe,llm,both").split(",")
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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 VARIANTS:
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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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for key, acc in (("fusion.g_moe", gm), ("fusion.g_llm", gl)):
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if key not in sd:
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continue
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t = sd[key]
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acc.append(abs(t.item()) if t.dim() == 0
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else float(t.norm()) / (t.numel() ** 0.5))
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for name, acc in (("g_moe", gm), ("g_llm", gl)):
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if acc:
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print(f" {name}: mean={np.mean(acc):.4f} range=[{min(acc):.4f},{max(acc):.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}") |