code: def soft_update_model(target_model, source_model, tau):
      """Update model parameter of target and source model.
  
      # noqa: D417
      Args:
          target_model
                  (garage.torch.Policy/garage.torch.QFunction):
                      Target model to update.
          source_model
                  (garage.torch.Policy/QFunction):
                      Source network to update.
          tau (float): Interpolation parameter for doing the
              soft target update.
  
      """
      for target_param, param in zip(
          target_model.parameters(), source_model.parameters()
      ):
          target_param.data.copy_(
              target_param.data * (1.0 - tau) + param.data * tau
          )
  
imports: import copy
  import math
  import warnings
  import torch
  from torch import nn
  import torch.nn.functional
label_desc: Use image node_id 12 for calling a global function with example usage: soft_update_model(target_model, source_model, tau) without return types