code: def test_CoFrNet(self):
      network_depth = 13
      input_size = 40
      output_size = 3
      cofrnet_version = "diag_ladder_of_ladder_combined"
      model = CoFrNet_Model(
          generate_connections(
              network_depth, input_size, output_size, cofrnet_version
          )
      )
  
      first_column_csv = 0
      last_column_csv = -1
  
      web_link = "http://www.dropbox.com/s/qtdv1teptf097zl/waveformnoise.csv?dl=1"
      (
          tensor_x_train,
          tensor_y_train,
          tensor_x_val,
          tensor_y_val,
          tensor_x_test,
          y_test,
      ) = process_data(
          first_column_csv=first_column_csv,
          last_column_csv=last_column_csv,
          web_link=web_link,
      )
  
      train_dataset = OnlyTabularDataset(tensor_x_train, tensor_y_train)
  
      batch_size = 100
      dataloader = DataLoader(train_dataset, batch_size)
  
      train(model, dataloader, output_size)
  
      explainer = CoFrNet_Explainer(model)
      explainer.print_accuracy(tensor_x_test, y_test)
  
imports: import unittest
  import os
  import shutil
  import sys
  from torch.utils.data import DataLoader
  from tqdm import tqdm
  import numpy
  from torch.utils.data import Dataset
  import torch
  import torch.nn
  from torch.autograd import Function
  from torch.nn.parameter import Parameter
  import torch.nn.functional
  from sklearn.preprocessing import MinMaxScaler
  from sklearn.model_selection import train_test_split
  import torch.optim
  from sklearn.datasets import load_breast_cancer, load_wine, load_linnerud, load_diabetes, load_iris, load_digits
  from sklearn.preprocessing import LabelEncoder
  from sklearn.preprocessing import StandardScaler
  import random
  import pandas
  from aix360.algorithms.cofrnet.CustomizedLinearClasses import CustomizedLinearFunction
  from aix360.algorithms.cofrnet.CustomizedLinearClasses import CustomizedLinear
  from aix360.algorithms.cofrnet.utils import generate_connections
  from aix360.algorithms.cofrnet.utils import process_data
  from aix360.algorithms.cofrnet.utils import train
  from aix360.algorithms.cofrnet.utils import OnlyTabularDataset
  from aix360.algorithms.cofrnet.CoFrNet import CoFrNet_Model
  from aix360.algorithms.cofrnet.CoFrNet import CoFrNet_Explainer
label_desc: Use image node_id 1 for calling the TestCoFrNets obj's underlying member method code with example usage: obj.test_CoFrNet() without return types