code: def bench_uniform_neighbor_sample_email_eu_core(
      gpubenchmark, dask_client, n_samples
  ):
      input_data_path = email_Eu_core.get_path()
      chunksize = dcg.get_chunksize(input_data_path)
  
      ddf = dask_cudf.read_csv(
          input_data_path,
          chunksize=chunksize,
          delimiter=" ",
          names=["src", "dst", "value"],
          dtype=["int32", "int32", "int32"],
      )
  
      dg = cugraph.Graph(directed=False)
      dg.from_dask_cudf_edgelist(
          ddf,
          source="src",
          destination="dst",
          edge_attr="value",
          store_transposed=False,
      )
      # Partition the dataframe to add in chunks
      srcs = dg.input_df["src"]
      start_list = srcs[:n_samples].compute()
  
      def func():
          _ = cugraph.dask.uniform_neighbor_sample(dg, start_list, [10])
          del _
  
      gpubenchmark(func)
  
imports: import gc
  import random
  import os
  import pytest
  import pandas
  import cupy
  import cudf
  import cugraph
  import dask_cudf
  import cugraph.dask
  from cugraph.testing import UNDIRECTED_DATASETS
  from cugraph.dask import uniform_neighbor_sample
  from cugraph.dask.common.mg_utils import is_single_gpu
  from cugraph.datasets import email_Eu_core, small_tree
  from pylibcugraph.testing.utils import gen_fixture_params_product
label_desc: Use image node_id 25 for calling a global function with example usage: bench_uniform_neighbor_sample_email_eu_core(gpubenchmark, dask_client, n_samples) without return types