code: def test_kernel_density(kernel, bandwidth):
      n_samples, n_features = (100, 3)
  
      rng = np.random.RandomState(0)
      X = rng.randn(n_samples, n_features)
      Y = rng.randn(n_samples, n_features)
  
      dens_true = compute_kernel_slow(Y, X, kernel, bandwidth)
  
      for rtol in [0, 1e-5]:
          for atol in [1e-6, 1e-2]:
              for breadth_first in (True, False):
                  check_results(
                      kernel, bandwidth, atol, rtol, X, Y, dens_true
                  )
  
imports: import joblib
  import numpy
  import pytest
  from sklearn.datasets import make_blobs
  from sklearn.exceptions import NotFittedError
  from sklearn.model_selection import GridSearchCV
  from sklearn.neighbors import KDTree, KernelDensity, NearestNeighbors
  from sklearn.neighbors._ball_tree import kernel_norm
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils._testing import assert_allclose
label_desc: Use image node_id 3 for calling a global function with example usage: test_kernel_density(kernel, bandwidth) without return types