code: def test_balance_by_time(device):
      class Delay(nn.Module):
          def __init__(self, seconds):
              super().__init__()
              self.seconds = seconds
  
          def forward(self, x):
              time.sleep(self.seconds)
              return x
  
      model = nn.Sequential(
          *[Delay(i / 10) for i in [1, 2, 3, 4, 5, 6]]
      )
      sample = torch.rand(1)
      balance = balance_by_time(2, model, sample, device=device)
      assert balance == [4, 2]
  
imports: import time
  import pytest
  import torch
  from torch import nn
  from torch.distributed.pipeline.sync._balance import balance_by_size, balance_by_time, blockpartition
  from torch.distributed.pipeline.sync._balance.profile import layerwise_sandbox
  from torch.testing._internal.common_utils import run_tests
label_desc: Use image node_id 5 for calling a global function with example usage: test_balance_by_time(device) and returns: x