code: def test_step_multigpu_mixed_precision():
      if not torch.cuda.device_count() > 1:
          return
      weight = torch.randn(10, 5).cuda(0).half().requires_grad_()
      bias = torch.randn(10).cuda(1).half().requires_grad_()
      input = torch.randn(5).cuda(0).half()
      optimizer = Adam([weight, bias], lr=1e-3)
  
      step_test(optimizer, weight, bias, input)
  
imports: from copy import deepcopy
  import functools
  import pytest
  import torch
label_desc: Use image node_id 12 for calling a global function with example usage: test_step_multigpu_mixed_precision() without return types