code: def copy_in_grads(params, params_with_grad):
      for param, param_w_grad in zip(params, params_with_grad):
          if param.grad is None:
              param.grad = torch.nn.Parameter(
                  param.data.new().resize_(*param.data.size())
              )
          param.grad.data.copy_(param_w_grad.grad.data)
  
imports: import torch
  import torch.nn
  from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
label_desc: Use image node_id 15 for calling a global function with example usage: copy_in_grads(params, params_with_grad) without return types