code: def make_full_precision_params():
      weight = torch.randn(2, 1).cuda().requires_grad_()
      bias = torch.randn(2).cuda().requires_grad_()
      input = torch.randn(1).cuda()
  
      return weight, bias, input
  
imports: from copy import deepcopy
  import functools
  import pytest
  import torch
label_desc: Use image node_id 2 for calling a global function with example usage: make_full_precision_params() and returns: weight,  bias,  input