docstr: Ensure model training does not error out
  Ensure model returns predictions of the right type
docstr_tok: ["Ensure","model","training","does","not","error","out","Ensure","model","returns","predictions","of","the","right","type"]
code: def test_fit_predict(self):
      """
      Ensure model training does not error out
      Ensure model returns predictions of the right type
      """
  
      model = Comparison(**self.default_config())
      n_samples = 10
      model.fit(
          [
              [
                  "Transformers was a terrible movie but a great model",
                  "Transformers are a great model but a terrible movie",
              ]
          ]
          * n_samples,
          ["yes"] * n_samples,
      )
  
      test_data = [
          [
              "Transformers was a terrible movie but a great model",
              "Transformers are a great model but a terrible movie",
          ]
      ]
  
      predictions = model.predict(test_data)
      for prediction in predictions:
          self.assertIsInstance(prediction, (str, bytes))
  
      probabilities = model.predict_proba(test_data)
      for proba in probabilities:
          self.assertIsInstance(proba, dict)
  
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 3 for calling the TestComparison obj's underlying member method code with example usage: obj.test_fit_predict() without return types