code: def networkx_strong_call(graph_file):
      G = graph_file.get_graph(
          create_using=cugraph.Graph(directed=True)
      )
      dataset_path = graph_file.get_path()
      M = utils.read_csv_for_nx(dataset_path)
      Gnx = nx.from_pandas_edgelist(
          M, source="0", target="1", create_using=nx.DiGraph()
      )
  
      t1 = time.time()
      result = nx.strongly_connected_components(Gnx)
      t2 = time.time() - t1
      print("Time : " + str(t2))
  
      nx_labels = sorted(result)
      nx_n_components = len(nx_labels)
      lst_nx_components = sorted(nx_labels, key=len, reverse=True)
  
      return (
          G,
          dataset_path,
          nx_labels,
          nx_n_components,
          lst_nx_components,
          "strong",
      )
  
imports: import gc
  import time
  from collections import defaultdict
  import pytest
  import cupy
  import numpy
  import networkx
  from cupyx.scipy.sparse import coo_matrix
  from cupyx.scipy.sparse import csr_matrix
  from cupyx.scipy.sparse import csc_matrix
  from scipy.sparse import coo_matrix
  from scipy.sparse import csr_matrix
  from scipy.sparse import csc_matrix
  from cugraph.utilities import is_nx_graph_type
  import cudf
  import cugraph
  from cugraph.testing import utils, DEFAULT_DATASETS
  from cugraph.datasets import dolphins, netscience, email_Eu_core
label_desc: Use image node_id 3 for calling a global function with example usage: networkx_strong_call(graph_file) and returns: G,  dataset_path,  nx_labels,  nx_n_components,  lst_nx_components,  str