code: def __init__(
      self,
      guest_bottom,
      host_bottom,
      guest_top,
      agg_layer_guest,
      agg_layer_host,
      is_binary=True,
  ):
      super(FakeNNModel, self).__init__()
      self.guest_bottom = t.nn.Linear(guest_bottom[0], guest_bottom[1])
      self.host_bottom = t.nn.Linear(host_bottom[0], host_bottom[1])
      self.guest_top = t.nn.Linear(guest_top[0], guest_top[1])
      self.agg_layer_guest = t.nn.Linear(
          agg_layer_guest[0], agg_layer_guest[1]
      )
      self.agg_layer_host = t.nn.Linear(
          agg_layer_host[0], agg_layer_host[1]
      )
      self.is_binary = is_binary
  
file_path: FATE/examples/benchmark_quality/hetero_nn/nn.py
imports: import argparse
  import os
  import torch
  import pandas
  import math
  from sklearn.metrics import roc_auc_score, precision_score, accuracy_score, recall_score, roc_curve, mean_absolute_error, mean_squared_error
  from fate_client.pipeline.utils.test_utils import JobConfig
label_desc: Use image node_id 1 to create a new FakeNNModel object from inherited base classes: t.nn with example: obj = FakeNNModel(guest_bottom, host_bottom, guest_top, agg_layer_guest, agg_layer_host, is_binary)