code: def test_warm_start_effectiveness():
      # A 1-iteration second fit on same data should give almost same result
      # with warm starting, and quite different result without warm starting.
  
      nca_warm = NeighborhoodComponentsAnalysis(
          warm_start=True, random_state=0
      )
      nca_warm.fit(iris_data, iris_target)
      transformation_warm = nca_warm.components_
      nca_warm.max_iter = 1
      nca_warm.fit(iris_data, iris_target)
      transformation_warm_plus_one = nca_warm.components_
  
      nca_cold = NeighborhoodComponentsAnalysis(
          warm_start=False, random_state=0
      )
      nca_cold.fit(iris_data, iris_target)
      transformation_cold = nca_cold.components_
      nca_cold.max_iter = 1
      nca_cold.fit(iris_data, iris_target)
      transformation_cold_plus_one = nca_cold.components_
  
      diff_warm = np.sum(
          np.abs(transformation_warm_plus_one - transformation_warm)
      )
      diff_cold = np.sum(
          np.abs(transformation_cold_plus_one - transformation_cold)
      )
      assert diff_warm < 3.0, (
          "Transformer changed significantly after one "
          "iteration even though it was warm-started."
      )
  
      assert diff_cold > diff_warm, (
          "Cold-started transformer changed less "
          "significantly than warm-started "
          "transformer after one iteration."
      )
  
imports: import re
  import numpy
  import pytest
  from numpy.testing import assert_array_almost_equal, assert_array_equal
  from scipy.optimize import check_grad
  from sklearn import clone
  from sklearn.datasets import load_iris, make_blobs, make_classification
  from sklearn.exceptions import ConvergenceWarning
  from sklearn.metrics import pairwise_distances
  from sklearn.neighbors import NeighborhoodComponentsAnalysis
  from sklearn.preprocessing import LabelEncoder
  from sklearn.utils import check_random_state
label_desc: Use image node_id 10 for calling a global function with example usage: test_warm_start_effectiveness() without return types