code: def test_to_device(
      layer_list: List[Tuple[str, nn.Module]],
      layer_config: Dict[str, Any],
  ) -> None:
      """Tests that inputs, labels, and module are initialized on CPU, and that moving
      them to GPU and CPU works correctly.
  
      Args:
          layer_list: list of tuples of form (layer_name, module)
          layer_config: config for instantiating the layers in layer_list
      """
      cuda = torch.device("cuda:0")
      cpu = torch.device("cpu")
      assert reset_peak_memory_stats(cuda).cur_mem == 0
  
      for layer_name, module, gsm_mode_blocklist in layer_list:
          for gsm_mode in GSM_MODES - set(gsm_mode_blocklist):
              layer = LayerFactory.create(
                  layer_name=layer_name,
                  batch_size=64,
                  gsm_mode=gsm_mode,
                  **layer_config,
              )
              if layer is None:
                  continue
              # layer should be initialized on CPU
              assert torch.cuda.memory_allocated(cuda) == 0
  
              mem_stats = layer.to(cuda)
              allocated = torch.cuda.memory_allocated(cuda)
              assert allocated > 0
              # all allocated memory should be accounted for in the memory statistics
              assert allocated == sum(v for _, v in mem_stats.items())
  
              mem_stats = layer.to(cpu)
              allocated = torch.cuda.memory_allocated(cuda)
              assert allocated == 0
              assert allocated == sum(v for _, v in mem_stats.items())
  
      assert reset_peak_memory_stats(cuda).cur_mem == 0
  
file_path: opacus/benchmarks/tests/test_layers.py
imports: import copy
  import logging
  import random
  from typing import Any, Dict, List, Tuple, Type
  import pytest
  import torch
  import torch.nn
  from helpers import skipifnocuda
  from opacus.grad_sample import GradSampleModule
  from opacus.grad_sample.gsm_exp_weights import GradSampleModuleExpandedWeights
  from opacus.layers import DPGRU, DPLSTM, DPRNN, DPMultiheadAttention
  from benchmarks.layers import LayerFactory
  from benchmarks.utils import reset_peak_memory_stats
label_desc: Use image node_id 2 for calling a global function with example usage: test_to_device(layer_list, layer_config) without return types