code: def test_multi_get_tensor(graph):
      F, G, N = graph
      cugraph_store = CuGraphStore(F, G, N)
  
      for vertex_type in sorted(N.keys()):
          v_ids = np.arange(N[vertex_type])
          feat_names = list(F.get_feature_list().keys())
          base_series = None
          for feat_name in feat_names:
              if base_series is None:
                  base_series = F.get_data(
                      v_ids, vertex_type, feat_name
                  )
              else:
                  base_series = np.stack(
                      [
                          base_series,
                          F.get_data(v_ids, vertex_type, feat_name),
                      ]
                  )
  
          tsr = cugraph_store.multi_get_tensor(
              [
                  CuGraphTensorAttr(vertex_type, feat_name, v_ids)
                  for feat_name in feat_names
              ]
          )
  
          assert torch.stack(tsr).tolist() == base_series.tolist()
  
imports: import cugraph
  from cugraph_pyg.data.cugraph_store import CuGraphTensorAttr, CuGraphEdgeAttr, EdgeLayout
  from cugraph_pyg.data import CuGraphStore
  import cudf
  import cupy
  import numpy
  from cugraph.utilities.utils import import_optional, MissingModule
  import pytest
label_desc: Use image node_id 13 for calling a global function with example usage: test_multi_get_tensor(graph) without return types