code: def dist_tensor_test_sanity(data_shape, name=None):
      local_rank = dgl.distributed.get_rank() % num_client_per_machine
      dist_ten = dgl.distributed.DistTensor(
          data_shape, F.int32, init_func=zeros_init, name=name
      )
      # arbitrary value
      stride = 3
      pos = (part_id // 2) * num_client_per_machine + local_rank
      if part_id % 2 == 0:
          dist_ten[pos * stride : (pos + 1) * stride] = F.ones(
              (stride, 2), dtype=F.int32, ctx=F.cpu()
          ) * (pos + 1)
  
      dgl.distributed.client_barrier()
      assert F.allclose(
          dist_ten[pos * stride : (pos + 1) * stride],
          F.ones((stride, 2), dtype=F.int32, ctx=F.cpu()) * (pos + 1),
      )
  
imports: import json
  import os
  from itertools import product
  import dgl
  import dgl.backend
  import numpy
  from dgl.distributed import edge_split, load_partition_book, node_split
label_desc: Use image node_id 13 for calling a global function with example usage: dist_tensor_test_sanity(data_shape, name) without return types