code: def test_balance_by_time_tuple():
      class Twin(nn.Module):
          def forward(self, x):
              return x, x.detach()
  
      class Add(nn.Module):
          def forward(self, a, b):
              return a + b
  
      model = nn.Sequential(Twin(), Add())
      sample = torch.rand(1, requires_grad=True)
      balance_by_time(1, model, sample, device="cpu")
  
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 13 for calling a global function with example usage: test_balance_by_time_tuple() and returns: x,  x, unknown