code: def __init__(self, in_ch, out_ch):
      super().__init__()
      self.depthwise = nn.Conv2d(
          in_ch, in_ch, kernel_size=3, groups=in_ch
      )
      self.pointwise = nn.Conv2d(in_ch, out_ch, kernel_size=1)
  
imports: import os
  import random
  from pathlib import Path
  import nni
  import torch
  import torch.nn.functional
  import nni.retiarii.nn.pytorch
  import nni.retiarii.strategy
  from nni.retiarii import model_wrapper
  from nni.retiarii.evaluator import FunctionalEvaluator
  from nni.retiarii.experiment.pytorch import RetiariiExeConfig, RetiariiExperiment, debug_mutated_model
  from torch.utils.data import DataLoader
  from torchvision import transforms
  from torchvision.datasets import MNIST
label_desc: Use image node_id 1 to create a new DepthwiseSeparableConv object from inherited base classes: nn with example: obj = DepthwiseSeparableConv(in_ch, out_ch)