code: def run_test_gpt2(
      rank,
      world_size,
      backend,
      device,
      temp_file_name,
      reduce_buffer_size,
  ):
      INPUT_DIM = 16
      BACH_SIZE = 10
      STEPS = 10
  
      url = "file://" + temp_file_name
      dist.init_process_group(
          init_method=url,
          backend=backend,
          rank=rank,
          world_size=world_size,
      )
      torch.cuda.set_device(rank)
  
      torch.manual_seed(rank)
      np.random.seed(rank)
      model = GPT2(
          embed_dim=256,
          num_heads=2,
          num_layers=12,
          num_positions=INPUT_DIM * INPUT_DIM,
          num_vocab=512,
          num_classes=2,
      )
      optimizer = OSS(
          params=model.parameters(),
          optim=torch.optim.SGD,
          lr=1e-3,
          momentum=0.99,
      )
      ddp_model = ShardedDataParallel(
          model, optimizer, reduce_buffer_size=reduce_buffer_size
      )
  
      # Move the model to another device post-construction
      model = model.to(device)
  
      # Optim loop
      set_to_none = True
  
      def closure():
          nonlocal set_to_none
          ddp_model.zero_grad(set_to_none=set_to_none)
          set_to_none = not set_to_none
  
          # Force int inputs to prevent the first grad from firing
          input_tensor = torch.randint(10, (BACH_SIZE, INPUT_DIM)).to(
              device
          )
          loss = ddp_model(input_tensor).abs().sum()
          loss.backward()
          return loss
  
      # Check for bucketing overflows
      for i in range(STEPS):
          _ = optimizer.step(closure=closure)
  
          # Stress test the .to() method
          ddp_model.to(device=device, dtype=torch.float16)
          ddp_model.to(device=device, dtype=torch.float32)
  
      dist.destroy_process_group()
  
imports: from contextlib import suppress
  import numpy
  import pytest
  import torch
  import torch.distributed
  import torch.multiprocessing
  from torch.nn import Linear, Sequential
  from fairscale.fair_dev.testing.testing import GPT2, SGDWithPausingCompute, available_devices, check_same_models_across_ranks, skip_if_less_than_four_gpu, skip_if_no_cuda, skip_if_single_gpu, temp_files_ctx
  from fairscale.nn.data_parallel import ShardedDataParallel
  from fairscale.optim import OSS
label_desc: Use image node_id 21 for calling a global function with example usage: run_test_gpt2(rank, world_size, backend, device, temp_file_name, reduce_buffer_size) and returns: loss