code: def _model_make_functional(model, param_names, params):
      params = tuple(
          [param.detach().requires_grad_() for param in params]
      )
  
      for param_name in param_names:
          _del_attr(model, param_name.split("."))
  
      return params
  
imports: import warnings
  from functools import reduce
  from typing import Any, Callable, Iterable, List, NamedTuple, Optional, Tuple, TYPE_CHECKING, Union
  import torch
  import torch.nn
  from captum._utils.common import _get_module_from_name, _parse_version
  from captum._utils.gradient import _compute_jacobian_wrt_params, _compute_jacobian_wrt_params_with_sample_wise_trick
  from captum._utils.progress import progress
  from torch import Tensor
  from torch.nn import Module
  from torch.utils.data import DataLoader, Dataset
label_desc: Use image node_id 29 for calling a global function with example usage: _model_make_functional(model, param_names, params) and returns: params