code: def test_smooth_knn_dist_l1norms(nn_data):
      norms = smooth_knn(nn_data)
      assert_array_almost_equal(
          norms,
          1.0 + np.log2(10) * np.ones(norms.shape[0]),
          decimal=3,
          err_msg="Smooth knn-dists does not give expected" "norms",
      )
  
file_path: umap/umap/tests/test_umap_nn.py
imports: import numpy
  import pytest
  from numpy.testing import assert_array_almost_equal
  from sklearn.neighbors import KDTree
  from sklearn.preprocessing import normalize
  from umap import distances
  from umap.umap_ import nearest_neighbors, smooth_knn_dist
label_desc: Use image node_id 12 for calling a global function with example usage: test_smooth_knn_dist_l1norms(nn_data) without return types