code: def test_input_validation():
      # DBSCAN.fit should accept a list of lists.
      X = [[1.0, 2.0], [3.0, 4.0]]
      DBSCAN().fit(X)
  
imports: import pickle
  import warnings
  import numpy
  import pytest
  from scipy.spatial import distance
  from sklearn.cluster import DBSCAN, dbscan
  from sklearn.cluster.tests.common import generate_clustered_data
  from sklearn.metrics.pairwise import pairwise_distances
  from sklearn.neighbors import NearestNeighbors
  from sklearn.utils._testing import assert_array_equal
  from sklearn.utils.fixes import CSR_CONTAINERS, LIL_CONTAINERS
label_desc: Use image node_id 12 for calling a global function with example usage: test_input_validation() without return types