code: def test_renumber_edges_by_type(
      dataset1_MGPropertyGraph, prev_id_column
  ):
      from cugraph.experimental import MGPropertyGraph
  
      (pG, data) = dataset1_MGPropertyGraph
      with pytest.raises(ValueError, match="existing column"):
          pG.renumber_edges_by_type("time")
      df_id_ranges = pG.renumber_edges_by_type(prev_id_column)
      expected = {
          "referrals": [0, 5],  # stop is inclusive
          "relationships": [6, 9],
          "transactions": [10, 13],
      }
      for key, (start, stop) in expected.items():
          assert df_id_ranges.loc[key, "start"] == start
          assert df_id_ranges.loc[key, "stop"] == stop
          df = pG.get_edge_data(types=[key]).compute().to_pandas()
          df = df.reset_index(drop=True)
          assert len(df) == stop - start + 1
          assert (
              df[pG.edge_id_col_name]
              == pd.Series(range(start, stop + 1))
          ).all()
  
          if prev_id_column is not None:
              assert prev_id_column in df.columns
  
      empty_pG = MGPropertyGraph()
      assert empty_pG.renumber_edges_by_type(prev_id_column) is None
  
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 24 for calling a global function with example usage: test_renumber_edges_by_type(dataset1_MGPropertyGraph, prev_id_column) without return types