code: def test_lr_finder(self):
      # 0.001 gives 54 examples
      with skip_if_downloading_fails():
          train_ds = MedNISTDataset(
              root_dir=self.root_dir,
              transform=self.transforms,
              section="validation",
              val_frac=0.001,
              download=True,
              num_workers=2,
          )
      train_loader = DataLoader(
          train_ds, batch_size=300, shuffle=True, num_workers=2
      )
      num_classes = train_ds.get_num_classes()
  
      model = DenseNet(
          spatial_dims=2,
          in_channels=1,
          out_channels=num_classes,
          init_features=2,
          growth_rate=2,
          block_config=(2,),
      )
      loss_function = torch.nn.CrossEntropyLoss()
      learning_rate = 1e-5
      optimizer = torch.optim.Adam(model.parameters(), learning_rate)
  
      lr_finder = LearningRateFinder(
          model=model,
          optimizer=optimizer,
          criterion=loss_function,
          device=device,
          pickle_module=pickle,
          pickle_protocol=4,
      )
      lr_finder.range_test(
          train_loader, val_loader=train_loader, end_lr=10.0, num_iter=5
      )
      print(lr_finder.get_steepest_gradient(0, 0)[0])
  
      if has_matplotlib:
          ax = plt.subplot()
          plt.show(block=False)
          lr_finder.plot(
              0, 0, ax=ax
          )  # to inspect the loss-learning rate graph
          plt.pause(3)
          plt.close()
  
      lr_finder.reset()
  
file_path: MONAI/tests/test_lr_finder.py
imports: from __future__ import annotations
  import os
  import pickle
  import random
  import sys
  import unittest
  from typing import TYPE_CHECKING
  import torch
  from torch.utils.data import DataLoader
  from monai.apps import MedNISTDataset
  from monai.networks.nets import DenseNet
  from monai.optimizers import LearningRateFinder
  from monai.transforms import Compose, EnsureChannelFirstd, LoadImaged, ScaleIntensityd, ToTensord
  from monai.utils import optional_import, set_determinism
  from monai.utils.misc import MONAIEnvVars
  from tests.utils import skip_if_downloading_fails
label_desc: Use image node_id 2 for calling the TestLRFinder obj's underlying member method code with example usage: obj.test_lr_finder() without return types