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bbench-dep-marble / marble /modules /callbacks.py
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mirror sync @ 2026-05-27T11:23:00Z
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# marble/modules/callbacks.py
import os
import glob
import torch
from lightning.pytorch.callbacks import Callback, ModelCheckpoint
class LoadLatestCheckpointCallback(Callback):
"""
在 test 开始时,自动从 ModelCheckpoint 的 dirpath 目录里
找到最新的 .ckpt 文件并 load 到 pl_module 中。
"""
def on_test_start(self, trainer, pl_module):
# 1) 从 trainer.callbacks 中找到你的 ModelCheckpoint 实例
ckpt_cb: ModelCheckpoint | None = next(
(cb for cb in trainer.callbacks if isinstance(cb, ModelCheckpoint)),
None
)
if ckpt_cb is None:
raise RuntimeError("没找到 ModelCheckpoint 回调,无法定位 ckpt 目录。")
ckpt_dir = ckpt_cb.dirpath
if not os.path.isdir(ckpt_dir):
raise RuntimeError(f"Checkpoint 目录不存在:{ckpt_dir}")
# 2) 列出所有 .ckpt,按文件修改时间选最新的那一个
paths = glob.glob(os.path.join(ckpt_dir, "*.ckpt"))
if not paths:
raise RuntimeError(f"{ckpt_dir} 里没有任何 .ckpt 文件。")
latest_ckpt = max(paths, key=os.path.getmtime)
# 3) load 到模型上
# map_location 选 pl_module 当前所在设备
map_loc = {"cpu": "cpu"}
if pl_module.device.type == "cuda":
map_loc = {"cuda:0": f"cuda:{pl_module.device.index or 0}"}
checkpoint = torch.load(latest_ckpt, map_location=map_loc)
state_dict = checkpoint.get("state_dict", checkpoint)
pl_module.load_state_dict(state_dict)
# 4) 日志告知
trainer.logger.log_metrics({"loaded_ckpt": os.path.basename(latest_ckpt)})
print(f"[LoadLatestCheckpoint] loaded {latest_ckpt}")