code: def _extract_parameters_from_layers(layer_modules):
      layer_parameters = []
      if layer_modules is not None:
          layer_parameters = [
              parameter
              for layer_module in layer_modules
              for parameter in layer_module.parameters()
          ]
          assert (
              len(layer_parameters) > 0
          ), "No parameters are available for modules for provided input `layers`"
      return layer_parameters
  
imports: import threading
  import typing
  import warnings
  from collections import defaultdict
  from typing import Any, Callable, cast, Dict, List, Optional, Sequence, Tuple, Union
  import torch
  from captum._utils.common import _reduce_list, _run_forward, _sort_key_list, _verify_select_neuron
  from captum._utils.sample_gradient import SampleGradientWrapper
  from captum._utils.typing import Literal, ModuleOrModuleList, TargetType, TensorOrTupleOfTensorsGeneric
  from torch import device, Tensor
  from torch.nn import Module
label_desc: Use image node_id 22 for calling a global function with example usage: _extract_parameters_from_layers(layer_modules) and returns: layer_parameters