code: def test_0_train_and_predict_bypass(self):
      df = pd.read_csv("tests/data/tripadvisor_binary_sample.csv")[:100]
      predictor = predictor_from_problem(
          df,
          ProblemDefinition.from_dict(
              {"target": "Label", "time_aim": 40}
          ),
      )
      # Test with a short time aim
      predictor.learn(df)
      predictions = predictor.predict(df)
      for x in predictions["prediction"]:
          assert x is not None
  
file_path: lightwood/tests/integration/advanced/test_text_input.py
imports: from lightwood.api.types import ProblemDefinition
  from lightwood.api.high_level import predictor_from_problem
  import pandas
  import unittest
label_desc: Use image node_id 1 for calling the TestText obj's underlying member method code with example usage: obj.test_0_train_and_predict_bypass() without return types