code: def test_balance_by_size_tuple():
      class Twin(nn.Module):
          def forward(self, x):
              return x, x.detach()
  
      class Add(nn.Module):
          def forward(self, a_b):
              a, b = a_b
              return a + b
  
      model = nn.Sequential(Twin(), Add())
      sample = torch.rand(1, requires_grad=True)
      balance_by_size(1, model, sample)
  
imports: import time
  import pytest
  import torch
  from torch import nn
  from fairscale.nn.pipe.balance import balance_by_size, balance_by_time, blockpartition
  from fairscale.nn.pipe.balance.profile import layerwise_sandbox
label_desc: Use image node_id 14 for calling a global function with example usage: test_balance_by_size_tuple() and returns: x,  x, unknown