code: def test_get_vertex_data_repeated(dask_client):
      from cugraph.experimental import MGPropertyGraph
  
      df = cudf.DataFrame(
          {"vertex": [2, 3, 4, 1], "feat": [0, 1, 2, 3]}
      )
      df = dask_cudf.from_cudf(df, npartitions=2)
      pG = MGPropertyGraph()
      pG.add_vertex_data(df, "vertex")
      df1 = pG.get_vertex_data(
          vertex_ids=[2, 1, 3, 1], columns=["feat"]
      )
      df1 = df1.compute()
      expected = cudf.DataFrame(
          {
              pG.vertex_col_name: [2, 1, 3, 1],
              pG.type_col_name: ["", "", "", ""],
              "feat": [0, 3, 1, 3],
          }
      )
      df1[pG.type_col_name] = df1[pG.type_col_name].astype(
          str
      )  # Undo category
      assert_frame_equal(df1, expected)
  
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 19 for calling a global function with example usage: test_get_vertex_data_repeated(dask_client) without return types