code: def setUp(self) -> None:
      data_transforms = {
          "train": transforms.Compose(
              [
                  transforms.RandomResizedCrop(224),
                  transforms.RandomHorizontalFlip(),
                  transforms.ToTensor(),
                  transforms.Normalize(
                      [0.485, 0.456, 0.406], [0.229, 0.224, 0.225]
                  ),
              ]
          )
      }
      self.train_data = PyTorchImageDataset(
          str(image_path), str(label_file), data_transforms["train"]
      )
      self.model = torchvision.models.resnet18(pretrained=True)
      num_ftrs = self.model.fc.in_features
      self.model.fc = nn.Linear(num_ftrs, self.train_data.num_classes)
      self.training_cfg = TrainingConfig(
          output_dir="./ResNetOutput",
          overwrite_output_dir=True,
          epoch_num=1,
          batch_size=4,
          dataloader_num_workers=0,
          tensorboard="null",
      )
      self.op = MockOperator()
  
imports: import unittest
  import torchvision
  from pathlib import Path
  from shutil import rmtree
  from torch import nn
  from torch.optim import AdamW
  from torchvision import transforms
  from towhee.operator import NNOperator
  from towhee.trainer.training_config import TrainingConfig
  from towhee.data.dataset.image_datasets import PyTorchImageDataset
label_desc: Use image node_id 1 for calling the TrainerTest obj's underlying member method code with example usage: obj.setUp() without return types