code: def __init__(self):
      super().__init__()
  
      self.cnn = nn.Sequential(
          nn.Conv2d(1, 32, (3, 3)),
          nn.ReLU(),
          nn.Conv2d(32, 64, (3, 3)),
          nn.ReLU(),
          nn.MaxPool2d((2, 2)),
          nn.Dropout(0.25),
      )
      self.out = nn.Sequential(
          nn.Linear(64 * 12 * 12, 128),
          nn.ReLU(),
          nn.Dropout(0.5),
          nn.Linear(128, 10),
          nn.Softmax(dim=-1),
      )
  
imports: import argparse
  import time
  import numpy
  from sklearn.datasets import fetch_openml
  from sklearn.model_selection import train_test_split
  from sklearn.model_selection import StratifiedKFold
  from sklearn.metrics import accuracy_score
  from sklearn.utils import shuffle
  import torch
  from torch import nn
  from skorch.utils import to_device
  from skorch import NeuralNetClassifier
  from skorch.callbacks import EpochScoring
label_desc: Use image node_id 1 to create a new ClassifierModule object from inherited base classes: nn with example: obj = ClassifierModule()