code: def __init__(self):
      super(LeNetBottom_, self).__init__()
      self.layer0 = nn.Sequential(
          ConvBlock(1, 8, kernel_size=5),
          nn.ReLU(inplace=True),
          nn.MaxPool2d(2, 2),
      )
  
      self.layer1 = nn.Sequential(
          ConvPassportBlock(
              8, 16, 5, num_passport=64, passport_mode="multi"
          ),
          nn.ReLU(inplace=True),
      )
  
imports: from torch.nn import init
  import sys
  import torch
  import torch
  import torchvision
  from torch import nn
  from datetime import datetime
  from fate.ml.nn.model_zoo.agg_layer.fedpass._passport_block import ConvPassportBlock
  from fate.ml.nn.model_zoo.hetero_nn_model import HeteroNNModelGuest, HeteroNNModelHost
  from fate.ml.nn.hetero.hetero_nn import HeteroNNTrainerGuest, HeteroNNTrainerHost, TrainingArguments, FedPassArgument
label_desc: Use image node_id 1 to create a new LeNetBottom_ object from inherited base classes: nn with example: obj = LeNetBottom_()