code: def random_call(G, partitions):
      random.seed(0)
      num_verts = G.number_of_vertices()
      assignment = []
      for i in range(num_verts):
          assignment.append(random.randint(0, partitions - 1))
  
      assignment_cu = cudf.DataFrame(assignment, columns=["cluster"])
      assignment_cu["vertex"] = assignment_cu.index
      assignment_cu = assignment_cu.astype("int32")
  
      score = cugraph.analyzeClustering_modularity(
          G, partitions, assignment_cu, "vertex", "cluster"
      )
      return score
  
file_path: cugraph/python/cugraph/cugraph/tests/community/test_modularity.py
imports: import gc
  import random
  import pytest
  import networkx
  import cudf
  import cugraph
  from cugraph.testing import utils, DEFAULT_DATASETS
  from cugraph.utilities import ensure_cugraph_obj_for_nx
label_desc: Use image node_id 2 for calling a global function with example usage: random_call(G, partitions) and returns: score