code: def setup_module():
      global dist_g
  
      reset_envs()
      os.environ["DGL_DIST_MODE"] = "standalone"
  
      dist_g = create_random_graph(10000)
      # Partition the graph.
      num_parts = 1
      graph_name = "dist_graph_test_3"
      dist_g.ndata["features"] = F.unsqueeze(
          F.arange(0, dist_g.num_nodes()), 1
      )
      dist_g.edata["features"] = F.unsqueeze(
          F.arange(0, dist_g.num_edges()), 1
      )
      dgl.distributed.partition_graph(
          dist_g, graph_name, num_parts, "/tmp/dist_graph"
      )
  
      dgl.distributed.initialize("kv_ip_config.txt")
      dist_g = dgl.distributed.DistGraph(
          graph_name,
          part_config="/tmp/dist_graph/{}.json".format(graph_name),
      )
      dist_g.edata["mask1"] = dgl.distributed.DistTensor(
          (dist_g.num_edges(),), F.bool, init_func=rand_mask
      )
      dist_g.edata["mask2"] = dgl.distributed.DistTensor(
          (dist_g.num_edges(),), F.bool, init_func=rand_mask
      )
  
file_path: dgl/tests/distributed/test_dist_tensor.py
imports: import operator
  import os
  import unittest
  import backend
  import dgl
  import pytest
  from utils import create_random_graph, generate_ip_config, reset_envs
label_desc: Use image node_id 2 for calling a global function with example usage: setup_module() without return types