code: def test_graph_creation_edges(graph_file, directed, renumber):
      # Verifies that the input dataframe passed the user is the same
      # retrieved from the graph when the graph is directed
      srcCol = "source"
      dstCol = "target"
      wgtCol = "weight"
      input_df = cudf.read_csv(
          graph_file,
          delimiter=" ",
          names=[srcCol, dstCol, wgtCol],
          dtype=["int32", "int32", "float32"],
          header=None,
      )
  
      G = cugraph.Graph(directed=directed)
  
      if renumber:
          # trigger renumbering by passing a list of vertex column
          srcCol = [srcCol]
          dstCol = [dstCol]
          vertexCol = srcCol + dstCol
      else:
          vertexCol = [srcCol, dstCol]
      G.from_cudf_edgelist(
          input_df, source=srcCol, destination=dstCol, edge_attr=wgtCol
      )
  
      columns = vertexCol.copy()
      columns.append(wgtCol)
  
      edge_list_view = G.view_edge_list().loc[:, columns]
      edges = G.edges().loc[:, vertexCol]
  
      assert_frame_equal(
          edge_list_view.drop(columns=wgtCol)
          .sort_values(by=vertexCol)
          .reset_index(drop=True),
          edges.sort_values(by=vertexCol).reset_index(drop=True),
          check_dtype=False,
      )
  
      if directed:
          assert_frame_equal(
              edge_list_view.sort_values(by=vertexCol).reset_index(
                  drop=True
              ),
              input_df.sort_values(by=vertexCol).reset_index(drop=True),
              check_dtype=False,
          )
      else:
          # If the graph is undirected, ensures that only the upper triangular
          # matrix of the adjacency matrix is returned
          if isinstance(srcCol, list):
              srcCol = srcCol[0]
              dstCol = dstCol[0]
          is_upper_triangular = (
              edge_list_view[srcCol] <= edge_list_view[dstCol]
          )
          is_upper_triangular = list(
              set(is_upper_triangular.values_host)
          )
          assert len(is_upper_triangular) == 1
          assert is_upper_triangular[0]
  
imports: import gc
  import time
  import pytest
  import pandas
  import scipy
  import networkx
  import cupy
  import cudf
  import cugraph
  from cugraph.testing import utils
  from cudf.testing import assert_series_equal
  from cudf.testing.testing import assert_frame_equal
  import dask_cudf
  import cugraph.dask
  from dask.distributed import Client
  from dask_cuda import LocalCUDACluster
  from pylibcugraph import ResourceHandle
  from pylibcugraph import bfs
  from cugraph.dask.traversal.bfs import convert_to_cudf
  from cugraph.dask.common.mg_utils import is_single_gpu
label_desc: Use image node_id 34 for calling a global function with example usage: test_graph_creation_edges(graph_file, directed, renumber) without return types