code: def get_dummy_sampled_df_csc():
      df_dict = dict(
          minors=np.array(
              [1, 1, 2, 1, 0, 3, 1, 3, 2, 3, 2, 4, 0, 1, 1, 0, 3, 2],
              dtype=np.int32,
          ),
          major_offsets=np.arange(19, dtype=np.int64),
          map=np.array(
              [26, 29, 33, 22, 23, 32, 18, 29, 33, 33, 8, 30, 32],
              dtype=np.int32,
          ),
          renumber_map_offsets=np.array([0, 4, 9, 13], dtype=np.int64),
          label_hop_offsets=np.array(
              [0, 1, 3, 6, 7, 9, 13, 14, 16, 18], dtype=np.int64
          ),
      )
  
      # convert values to Series so that NaNs are padded automatically
      return cudf.DataFrame(
          {k: cudf.Series(v) for k, v in df_dict.items()}
      )
  
file_path: cugraph/python/cugraph-dgl/tests/test_utils.py
imports: import cudf
  import cupy
  import numpy
  from cugraph_dgl.dataloading.utils.sampling_helpers import cast_to_tensor, _get_renumber_map, _split_tensor, _get_tensor_d_from_sampled_df, create_homogeneous_sampled_graphs_from_dataframe, _get_source_destination_range, _create_homogeneous_cugraph_dgl_nn_sparse_graph, create_homogeneous_sampled_graphs_from_dataframe_csc
  from cugraph.utilities.utils import import_optional
label_desc: Use image node_id 3 for calling a global function with example usage: get_dummy_sampled_df_csc() and returns: cudf