code: def test_dist_neighbor_sampler_edge_level_temporal(
      seed_time,
      temporal_strategy,
  ):
      seed_time = torch.tensor(seed_time)
  
      mp_context = torch.multiprocessing.get_context("spawn")
      with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
          s.settimeout(1)
          s.bind(("127.0.0.1", 0))
          port = s.getsockname()[1]
  
      world_size = 2
      w0 = mp_context.Process(
          target=dist_neighbor_sampler_temporal,
          args=(
              world_size,
              0,
              port,
              seed_time,
              temporal_strategy,
              "edge_time",
          ),
      )
  
      w1 = mp_context.Process(
          target=dist_neighbor_sampler_temporal,
          args=(
              world_size,
              1,
              port,
              seed_time,
              temporal_strategy,
              "edge_time",
          ),
      )
  
      w0.start()
      w1.start()
      w0.join()
      w1.join()
  
imports: import atexit
  import socket
  from typing import Optional
  import pytest
  import torch
  from torch_geometric.data import Data
  from torch_geometric.datasets import FakeHeteroDataset
  from torch_geometric.distributed import DistNeighborSampler, LocalFeatureStore, LocalGraphStore, Partitioner
  from torch_geometric.distributed.dist_context import DistContext
  from torch_geometric.distributed.event_loop import ConcurrentEventLoop
  from torch_geometric.distributed.partition import load_partition_info
  from torch_geometric.distributed.rpc import init_rpc, shutdown_rpc
  from torch_geometric.sampler import NeighborSampler, NodeSamplerInput
  from torch_geometric.sampler.neighbor_sampler import node_sample
  from torch_geometric.testing import onlyLinux, withPackage
label_desc: Use image node_id 9 for calling a global function with example usage: test_dist_neighbor_sampler_edge_level_temporal(seed_time, temporal_strategy) without return types