code: def generate_tests(
      prefix: str,
      mixin: Type[RpcAgentTestFixture],
      tests: List[Type[RpcAgentTestFixture]],
      module_name: str,
  ) -> Dict[str, Type[RpcAgentTestFixture]]:
      """Mix in the classes needed to autogenerate the tests based on the params.
  
      Takes a series of test suites, each written against a "generic" agent (i.e.,
      derived from the abstract RpcAgentTestFixture class), as the `tests` args.
      Takes a concrete subclass of RpcAgentTestFixture, which specializes it for a
      certain agent, as the `mixin` arg. Produces all combinations of them.
      Returns a dictionary of class names to class type
      objects which can be inserted into the global namespace of the calling
      module. The name of each test will be a concatenation of the `prefix` arg
      and the original name of the test suite.
      The `module_name` should be the name of the calling module so
      that the classes can be fixed to make it look like they belong to it, which
      is necessary for pickling to work on them.
      """
      ret: Dict[str, Type[RpcAgentTestFixture]] = {}
      for test_class in tests:
          if IS_SANDCASTLE and TEST_WITH_DEV_DBG_ASAN:
              print(
                  f"Skipping test {test_class} on sandcastle for the following reason: "
                  "Skip dev-asan as torch + multiprocessing spawn have known issues",
                  file=sys.stderr,
              )
              continue
  
          name = f"{prefix}{test_class.__name__}"
          class_ = type(name, (test_class, mixin, SpawnHelper), {})
          class_.__module__ = module_name
          ret[name] = class_
      return ret
  
imports: import os
  import sys
  import unittest
  from typing import Dict, List, Type
  from torch.testing._internal.common_distributed import MultiProcessTestCase
  from torch.testing._internal.common_utils import TEST_WITH_DEV_DBG_ASAN, find_free_port, IS_SANDCASTLE
  from torch.testing._internal.distributed.ddp_under_dist_autograd_test import CudaDdpComparisonTest, DdpComparisonTest, DdpUnderDistAutogradTest
  from torch.testing._internal.distributed.pipe_with_ddp_test import PipeWithDDPTest
  from torch.testing._internal.distributed.nn.api.remote_module_test import CudaRemoteModuleTest, RemoteModuleTest, ThreeWorkersRemoteModuleTest
  from torch.testing._internal.distributed.rpc.dist_autograd_test import DistAutogradTest, CudaDistAutogradTest, FaultyAgentDistAutogradTest, TensorPipeAgentDistAutogradTest, TensorPipeCudaDistAutogradTest
  from torch.testing._internal.distributed.rpc.dist_optimizer_test import DistOptimizerTest
  from torch.testing._internal.distributed.rpc.jit.dist_autograd_test import JitDistAutogradTest
  from torch.testing._internal.distributed.rpc.jit.rpc_test import JitRpcTest
  from torch.testing._internal.distributed.rpc.jit.rpc_test_faulty import JitFaultyAgentRpcTest
  from torch.testing._internal.distributed.rpc.rpc_agent_test_fixture import RpcAgentTestFixture
  from torch.testing._internal.distributed.rpc.faulty_agent_rpc_test import FaultyAgentRpcTest
  from torch.testing._internal.distributed.rpc.rpc_test import CudaRpcTest, RpcTest, TensorPipeAgentRpcTest, TensorPipeAgentCudaRpcTest
  from torch.testing._internal.distributed.rpc.examples.parameter_server_test import ParameterServerTest
  from torch.testing._internal.distributed.rpc.examples.reinforcement_learning_rpc_test import ReinforcementLearningRpcTest
label_desc: Use image node_id 3 for calling a global function with example usage: generate_tests(prefix, mixin, tests, module_name) and returns: ret