docstr: Compute a renumbered edge list
  This function works in the MNMG pipeline and will transform
  the input dask_cudf.DataFrame into a renumbered edge list
  in the prescribed direction.
  This function will be called by the algorithms to ensure
  that the graph is renumbered properly.  The graph object will
  cache the most recent renumbering attempt.  For benchmarking
  purposes, this function can be called prior to calling a
  graph algorithm so we can measure the cost of computing
  the renumbering separately from the cost of executing the
  algorithm.
  When creating a CSR-like structure, set transposed to False.
  When creating a CSC-like structure, set transposed to True.
  
  Parameters
  ----------
  transposed : (optional) bool
      If True, renumber with the intent to make a CSC-like
      structure.  If False, renumber with the intent to make
      a CSR-like structure.  Defaults to False.
  
  legacy_renum_only : (optional) bool
      if True, The C++ renumbering will not be triggered.
      This parameter is added for new algos following the
      C/Pylibcugraph path
  
      This parameter is deprecated and will be removed.
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code: def compute_renumber_edge_list(
      self, transposed=False, legacy_renum_only=False
  ):
      """
      Compute a renumbered edge list
      This function works in the MNMG pipeline and will transform
      the input dask_cudf.DataFrame into a renumbered edge list
      in the prescribed direction.
      This function will be called by the algorithms to ensure
      that the graph is renumbered properly.  The graph object will
      cache the most recent renumbering attempt.  For benchmarking
      purposes, this function can be called prior to calling a
      graph algorithm so we can measure the cost of computing
      the renumbering separately from the cost of executing the
      algorithm.
      When creating a CSR-like structure, set transposed to False.
      When creating a CSC-like structure, set transposed to True.
  
      Parameters
      ----------
      transposed : (optional) bool
          If True, renumber with the intent to make a CSC-like
          structure.  If False, renumber with the intent to make
          a CSR-like structure.  Defaults to False.
  
      legacy_renum_only : (optional) bool
          if True, The C++ renumbering will not be triggered.
          This parameter is added for new algos following the
          C/Pylibcugraph path
  
          This parameter is deprecated and will be removed.
      """
  
      if legacy_renum_only:
          warning_msg = "The parameter 'legacy_renum_only' is deprecated and will be removed."
          warnings.warn(warning_msg, DeprecationWarning)
  
      if not self.properties.renumber:
          self.edgelist = self.EdgeList(self.input_df)
          self.renumber_map = None
      else:
          if self.edgelist is not None:
              if self.properties.directed is False:
                  return
  
              if self.properties.store_transposed == transposed:
                  return
  
              del self.edgelist
  
          (
              renumbered_ddf,
              number_map,
          ) = NumberMap.renumber_and_segment(
              self.input_df,
              self.source_columns,
              self.destination_columns,
              store_transposed=transposed,
              legacy_renum_only=legacy_renum_only,
          )
  
          self.edgelist = self.EdgeList(renumbered_ddf)
          self.renumber_map = number_map
          self.properties.store_transposed = transposed
  
imports: import gc
  from typing import Union
  import warnings
  import cudf
  import cupy
  import dask
  import dask_cudf
  from dask import delayed
  from dask.distributed import wait, default_client
  import numpy
  from pylibcugraph import MGGraph, ResourceHandle, GraphProperties, get_two_hop_neighbors, select_random_vertices
  from cugraph.structure import graph_primtypes_wrapper
  from cugraph.structure.graph_primtypes_wrapper import Direction
  from cugraph.structure.number_map import NumberMap
  from cugraph.structure.symmetrize import symmetrize
  from cugraph.dask.common.part_utils import get_persisted_df_worker_map, persist_dask_df_equal_parts_per_worker
  from cugraph.dask.common.mg_utils import run_gc_on_dask_cluster
  from cugraph.dask import get_n_workers
  import cugraph.dask.comms.comms
label_desc: Use image node_id 25 for calling the simpleDistributedGraphImpl obj's underlying member method code with example usage: obj.compute_renumber_edge_list(transposed, legacy_renum_only) without return types