code: def _custom_functional_call(model, d, features):
      param_names, params = zip(*list(d.items()))
      _params = _model_make_functional(model, param_names, params)
      _model_reinsert_params(model, param_names, params)
      out = model(*features)
      _model_reinsert_params(model, param_names, _params, register=True)
      return out
  
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 31 for calling a global function with example usage: _custom_functional_call(model, d, features) and returns: out