code: def __init__(self):
      super(M, self).__init__()
      self.cn1 = nn.Conv2d(
          in_channels=1, out_channels=64, kernel_size=3
      )
      self.cn2 = nn.Conv2d(
          in_channels=64, out_channels=32, kernel_size=3
      )
      self.fc1 = nn.Linear(in_features=128, out_features=2)
  
file_path: tensorboardX/examples/demo_embedding.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  import os
  from torch.autograd.variable import Variable
  from tensorboardX import SummaryWriter
  from torch.utils.data import TensorDataset, DataLoader
label_desc: Use image node_id 1 to create a new M object from inherited base classes: nn with example: obj = M()