code: def master_params_to_model_params(
      param_groups_and_shapes, master_params
  ):
      """
      Copy the master parameter data back into the model parameters.
      """
      # Without copying to a list, if a generator is passed, this will
      # silently not copy any parameters.
      for master_param, (param_group, _) in zip(
          master_params, param_groups_and_shapes
      ):
          for (_, param), unflat_master_param in zip(
              param_group,
              unflatten_master_params(
                  param_group, master_param.view(-1)
              ),
          ):
              param.detach().copy_(unflat_master_param)
  
imports: import numpy
  import torch
  import torch.nn
  from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
  from .None import logger
label_desc: Use image node_id 5 for calling a global function with example usage: master_params_to_model_params(param_groups_and_shapes, master_params) without return types