初始化Trainer时，您可能需要指定default_root_dir：

trainer = Trainer(default_root_dir='./my_dir')

官方文件中的描述：

default_root_dir-未传递任何记录器或pytorch_lightning.callbacks.ModelCheckpoint回调时日志和权重的默认路径。

程式码范例：

import numpy as np
import torch
from pytorch_lightning import LightningModule, Trainer
from torch.utils.data import DataLoader, Dataset

class MyDataset(Dataset):
    def __init__(self) -> None:
        super().__init__()

    def __getitem__(self, index):
        x = np.zeros((10,), np.float32)
        y = np.zeros((1,), np.float32)
        return x, y

    def __len__(self):
        return 100

class MyModel(LightningModule):
    def __init__(self):
        super().__init__()
        self.model = torch.nn.Linear(10, 1)

    def forward(self, x):
        return self.model(x)

    def training_step(self, batch, batch_idx):
        x, y = batch
        y_hat = self(x)
        loss = torch.nn.MSELoss()(y_hat, y)
        return loss

    def configure_optimizers(self):
        return torch.optim.Adam(self.parameters(), lr=0.02)

model = MyModel()
trainer = Trainer(default_root_dir='./my_dir')
train_dataloader = DataLoader(MyDataset())
trainer.tuner.lr_find(model, train_dataloader)