code: def create_distributed_karate_graph(store_transposed=True):
      input_data_path = (
          RAPIDS_DATASET_ROOT_DIR_PATH / "karate.csv"
      ).as_posix()
  
      chunksize = dcg.get_chunksize(input_data_path)
  
      ddf = dask_cudf.read_csv(
          input_data_path,
          chunksize=chunksize,
          delimiter=" ",
          names=["src", "dst", "value"],
          dtype=["int32", "int32", "float32"],
      )
  
      dg = cugraph.Graph(directed=True)
      dg.from_dask_cudf_edgelist(
          ddf, "src", "dst", store_transposed=store_transposed
      )
  
      return dg
  
file_path: cugraph/python/cugraph/cugraph/tests/link_analysis/test_pagerank_mg.py
imports: import gc
  import pytest
  import numpy
  import cudf
  import cugraph
  import cugraph.dask
  import dask_cudf
  from cugraph.testing import utils
  from cugraph.dask.common.mg_utils import is_single_gpu
  from cugraph.testing.utils import RAPIDS_DATASET_ROOT_DIR_PATH
label_desc: Use image node_id 2 for calling a global function with example usage: create_distributed_karate_graph(store_transposed) and returns: dg