code: def test_remote_module_call(hidden_dim=16):
      with background_server(
          num_experts=1,
          device="cpu",
          expert_cls="ffn",
          num_handlers=1,
          hidden_dim=hidden_dim,
          optim_cls=None,
      ) as server_peer_info:
          dht = DHT(initial_peers=server_peer_info.addrs, start=True)
          real_expert, fake_expert = create_remote_experts(
              [
                  ExpertInfo(
                      uid="expert.0", peer_id=server_peer_info.peer_id
                  ),
                  ExpertInfo(
                      uid="oiasfjiasjf",
                      peer_id=server_peer_info.peer_id,
                  ),
              ],
              dht=dht,
          )
          out1 = real_expert(torch.randn(1, hidden_dim))
          assert out1.shape == (1, hidden_dim)
          dummy_x = torch.randn(3, hidden_dim, requires_grad=True)
          out3 = real_expert(dummy_x)
          assert out3.shape == (3, hidden_dim)
          out3_again = real_expert(dummy_x[1:])
          assert torch.allclose(out3_again, out3[1:], atol=1e-5, rtol=0)
          out3_again.norm().backward()
          assert dummy_x.grad is not None and dummy_x.grad.norm() > 0
  
          try:
              real_expert(torch.randn(3, 11))
          except P2PHandlerError as e:
              assert str(11) in repr(
                  e
              ), "Exception must relay the remote server error (i.e. incorrect dimensions)"
          with pytest.raises(P2PHandlerError):
              fake_expert(dummy_x)
  
          # check that the server is still alive after processing a malformed request
          out3_yet_again = real_expert(dummy_x[1:])
          assert torch.allclose(
              out3_yet_again, out3[1:], atol=1e-5, rtol=0
          )
  
imports: import asyncio
  import ctypes
  import multiprocessing
  import threading
  import time
  import numpy
  import pytest
  import torch
  from hivemind.dht import DHT
  from hivemind.moe.client.expert import RemoteExpert, create_remote_experts
  from hivemind.moe.client.moe import DUMMY, RemoteMixtureOfExperts, _RemoteCallMany
  from hivemind.moe.client.remote_expert_worker import RemoteExpertWorker
  from hivemind.moe.client.switch_moe import RemoteSwitchMixtureOfExperts
  from hivemind.moe.expert_uid import ExpertInfo
  from hivemind.moe.server import ModuleBackend, Server, background_server, declare_experts
  from hivemind.moe.server.layers import name_to_block
  from hivemind.p2p.p2p_daemon_bindings.control import P2PHandlerError
  from hivemind.utils import BatchTensorDescriptor, MPFuture, get_dht_time
label_desc: Use image node_id 4 for calling a global function with example usage: test_remote_module_call(hidden_dim) without return types