code: def test_knn_with_aligner():
      """Tests KNN classifier with alignment distance on unequal length data."""
      from sktime.dists_kernels.compose_from_align import (
          DistFromAligner,
      )
      from sktime.utils._testing.hierarchical import _make_hierarchical
  
      X = _make_hierarchical(
          (3,), min_timepoints=5, max_timepoints=10, random_state=0
      )
      y = np.array([0, 1, 1])
  
      dtw_dist = DistFromAligner(AlignerDTW())
      clf = KNeighborsTimeSeriesClassifier(distance=dtw_dist)
  
      clf.fit(X, y)
  
file_path: sktime/sktime/classification/distance_based/tests/test_time_series_neighbors.py
imports: import numpy
  import pandas
  import pytest
  from sktime.alignment.dtw_python import AlignerDTW
  from sktime.classification.distance_based._time_series_neighbors import KNeighborsTimeSeriesClassifier
  from sktime.datasets import load_unit_test
  from sktime.tests.test_switch import run_test_for_class
  from sktime.utils.validation._dependencies import _check_estimator_deps
label_desc: Use image node_id 3 for calling a global function with example usage: test_knn_with_aligner() without return types