class_docstr: Convolutional Neural Network.
class_docstr_tok: ["Convolutional","Neural","Network","."]
code: def __init__(self) -> None:
      super().__init__()
      self.conv1 = nn.Conv2d(1, 20, kernel_size=5, stride=1)
      self.fc1 = nn.Linear(8 * 8 * 20, 64)
      self.fc2 = nn.Linear(64, 10)
  
file_path: Ax/ax/utils/tutorials/cnn_utils.py
imports: from itertools import accumulate
  from typing import Dict, List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torchvision
  import torchvision.transforms
  from torch._tensor import Tensor
  from torch.utils.data import DataLoader, Dataset, Subset
label_desc: Use image node_id 1 to create a new CNN object from inherited base classes: nn with example: obj = CNN()