code: def test_crf_verbose(xseq, yseq, algorithm, use_dev):
      crf = CRF(algorithm, verbose=True)
  
      if use_dev:
          X_dev, y_dev = [xseq], [yseq]
      else:
          X_dev, y_dev = None, None
  
      crf.fit(X=[xseq, xseq], y=[yseq, yseq], X_dev=X_dev, y_dev=y_dev)
      y_pred = crf.predict([xseq])
      if (
          algorithm != "ap"
      ):  # Averaged Perceptron is regularized too much
          assert y_pred == [yseq]
  
file_path: sklearn-crfsuite/tests/test_crf.py
imports: import os
  import pickle
  import pytest
  from sklearn.model_selection import cross_val_score
  from sklearn_crfsuite import CRF
label_desc: Use image node_id 2 for calling a global function with example usage: test_crf_verbose(xseq, yseq, algorithm, use_dev) without return types