code: def test_reasonable_predictions(self):
      model = Comparison(**self.default_config())
  
      # fake dataset generation
      animals = [
          "dog",
          "cat",
          "horse",
          "cow",
          "pig",
          "sheep",
          "goat",
          "chicken",
          "guinea pig",
          "donkey",
          "turkey",
          "duck",
          "camel",
          "goose",
          "llama",
          "rabbit",
          "fox",
      ]
      numbers = [
          "one",
          "two",
          "three",
          "four",
          "five",
          "six",
          "seven",
          "eight",
          "nine",
          "ten",
          "eleven",
          "twelve",
          "thirteen",
          "fourteen",
          "fifteen",
          "sixteen",
      ]
  
      n_per = 100
      similar = []
      different = []
      for dataset in [animals, numbers]:
          for i in range(n_per // 2):
              similar.append(
                  [random.choice(dataset), random.choice(dataset)]
              )
      for i in range(n_per):
          different.append(
              [random.choice(animals), random.choice(numbers)]
          )
  
      targets = np.asarray(
          ["similar"] * len(similar) + ["different"] * len(different)
      )
      data = similar + different
  
      x_tr, x_te, t_tr, t_te = train_test_split(
          data, targets, test_size=0.3
      )
      model.finetune(x_tr, t_tr)
  
      predictions = model.predict(x_te)
      accuracy = np.mean(
          [pred == true for pred, true in zip(predictions, t_te)]
      )
      naive_baseline = max(
          np.mean(targets == "similar"), np.mean(targets == "different")
      )
      self.assertGreater(accuracy, naive_baseline)
  
file_path: finetune/tests/test_comparison.py
imports: import os
  import unittest
  import warnings
  import random
  import tensorflow
  import numpy
  from sklearn.model_selection import train_test_split
  from finetune import Comparison
  from finetune.util import list_transpose
  import random
label_desc: Use image node_id 4 for calling the TestComparison obj's underlying member method code with example usage: obj.test_reasonable_predictions() without return types