code: def net_PropertyGraph(request):
      """
      Fixture which returns an instance of a PropertyGraph with vertex and edge
      data added from the netscience.csv dataset, parameterized for different
      DataFrame types.
      """
      from cugraph.experimental import PropertyGraph
  
      dataframe_type = request.param[0]
      netscience_csv = netscience.get_path()
      source_col_name = "src"
      dest_col_name = "dst"
  
      if dataframe_type is pd.DataFrame:
          read_csv = pd.read_csv
      else:
          read_csv = cudf.read_csv
      df = read_csv(
          netscience_csv,
          delimiter=" ",
          names=["src", "dst", "value"],
          dtype=["int32", "int32", "float32"],
      )
  
      pG = PropertyGraph()
      pG.add_edge_data(df, (source_col_name, dest_col_name))
  
      return pG
  
imports: import gc
  import pytest
  import pandas
  import numpy
  import cudf
  import cugraph
  import dask_cudf
  import cupy
  import cugraph.dask
  from cupy.testing import assert_array_equal
  from cudf.testing import assert_frame_equal, assert_series_equal
  from pylibcugraph.testing.utils import gen_fixture_params_product
  from cugraph.dask.common.mg_utils import is_single_gpu
  from cugraph.datasets import cyber, netscience
label_desc: Use image node_id 4 for calling a global function with example usage: net_PropertyGraph(request) and returns: pG