code: def __init__(self):
      super().__init__()
      self.model = resnet18(pretrained=True)
      num_ftrs = self.model.fc.in_features
      # Here the size of each output sample is set to 37.
      self.model.fc = nn.Linear(num_ftrs, 37)
  
file_path: BigDL/python/nano/tutorial/training/pytorch/pytorch_train_ipex_decorator.py
imports: import torch
  from torch import nn
  from torch.utils.data import DataLoader
  from torchvision import transforms
  from torchvision.models import resnet18
  from torchvision.datasets import OxfordIIITPet
  from tqdm import tqdm
  from bigdl.nano.pytorch import nano
label_desc: Use image node_id 1 to create a new MyPytorchModule object from inherited base classes: nn with example: obj = MyPytorchModule()