code: def __init__(self):
      super(Net, self).__init__()
      self.layer = nn.Sequential(
          nn.Conv2d(3, 64, 7, padding=1, stride=1),
          nn.ReLU(),
          nn.MaxPool2d(1, 2),
          nn.BatchNorm2d(64),
          nn.AvgPool2d(1, 1),
          nn.Dropout(0.5),
          nn.Linear(110, 30),
      )
  
file_path: tensorwatch/test/pre_train/draw_cust_model.py
imports: import torch
  import torchvision.models
  import tensorwatch
  import torch
  import torch.nn
  import torch.nn.functional
  import torchvision
  from torch.utils.tensorboard import SummaryWriter
  from torchvision import datasets, transforms
label_desc: Use image node_id 1 to create a new Net object from inherited base classes: nn with example: obj = Net()