code: def _parameter_linear_combination(
      paramss: List[Tuple[Tensor, ...]], cs: Tensor
  ) -> Tuple[Tensor, ...]:
      """
      scales each parameter (tensor of tuples) in a list by the corresponding scalar in a
      1D tensor of the same length, and sums up the scaled parameters
      """
      assert len(cs.shape) == 1
      result = _parameter_multiply(paramss[0], cs[0])
      for params, c in zip(paramss[1:], cs[1:]):
          result = _parameter_add(
              result, _parameter_multiply(params, c)
          )
      return result
  
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 24 for calling a global function with example usage: _parameter_linear_combination(paramss, cs) and returns: result