code: def test_build_pipeline_predict_arguments_assertion(
      has_repeated_learners,
  ):
      test_df = pd.DataFrame(
          {"x": [1, 2, 3, 4, 5], "y": [2, 4, 6, 8, 10]}
      )
  
      @fp.curry
      def invalid_learner(df):
          def p(dataset, *a, **b):
              return dataset + len(a) + len(b)
  
          return p, df, {}
  
      with pytest.raises(ValueError):
          build_pipeline(
              invalid_learner,
              has_repeated_learners=has_repeated_learners,
          )(test_df)
  
file_path: fklearn/tests/training/test_pipeline.py
imports: import itertools
  import numpy
  import pandas
  import pytest
  import toolz
  from fklearn.training.imputation import placeholder_imputer
  from fklearn.training.pipeline import build_pipeline
  from fklearn.training.regression import xgb_regression_learner
  from fklearn.training.transformation import count_categorizer, onehot_categorizer
label_desc: Use image node_id 5 for calling a global function with example usage: test_build_pipeline_predict_arguments_assertion(has_repeated_learners) and returns: p,  df,  dict, unknown