code: def test_series_np_predict():
      ftdf = _ftdf()
      ft_clf = SeriesFtClassifier()
      ft_clf.fit(ftdf["txt"].values, ftdf["lbl"].values)
  
      preds = ft_clf.predict(ftdf["txt"].values)
      assert preds[0] == 0
      assert preds[1] == 1
  
imports: import pytest
  import pandas
  from sklearn.model_selection import cross_val_score
  from skift import FirstColFtClassifier, IdxBasedFtClassifier, ColLblBasedFtClassifier, FirstObjFtClassifier, SeriesFtClassifier
label_desc: Use image node_id 9 for calling a global function with example usage: test_series_np_predict() without return types