code: def _get_grads(self, process_group, hook_type=None):
      device_id = gpus_for_rank(self.world_size)[self.rank][0]
      gpu_model = DistributedDataParallel(
          TestDdpCommHook().to(device_id),
          device_ids=[device_id],
          process_group=process_group,
      )
  
      # Register DDP Communication Hook if defined
      if hook_type is not None:
          register_ddp_comm_hook(
              comm_hook_type=hook_type,
              model=gpu_model,
              state=process_group,
          )
  
      return self._run_and_get_grads(gpu_model)
  
imports: import os
  import sys
  import torch
  from torch import nn
  import torch.distributed
  from torch.distributed.algorithms.ddp_comm_hooks import DDPCommHookType, register_ddp_comm_hook
  from torch.nn.parallel import DistributedDataParallel
  from torch.testing._internal.common_distributed import MultiProcessTestCase, requires_nccl, skip_if_lt_x_gpu
  from torch.testing._internal.common_utils import run_tests, TEST_WITH_DEV_DBG_ASAN
label_desc: Use image node_id 6 for calling the DistributedDataParallelCommHookTest obj's underlying member method code with example usage: obj._get_grads(process_group, hook_type) and returns: self