code: def _verify_select_neuron(
      layer_output: Tuple[Tensor, ...],
      selector: Union[int, Tuple[Union[int, slice], ...], Callable],
  ) -> Tensor:
      if callable(selector):
          return selector(
              layer_output if len(layer_output) > 1 else layer_output[0]
          )
  
      assert len(layer_output) == 1, (
          "Cannot select neuron index from layer with multiple tensors,"
          "consider providing a neuron selector function instead."
      )
  
      selected_neurons = _verify_select_column(
          layer_output[0], selector
      )
      if _contains_slice(selector):
          return selected_neurons.reshape(
              selected_neurons.shape[0], -1
          ).sum(1)
      return selected_neurons
  
imports: import typing
  from enum import Enum
  from functools import reduce
  from inspect import signature
  from typing import Any, Callable, cast, Dict, List, overload, Tuple, Union
  import numpy
  import torch
  from captum._utils.typing import BaselineType, Literal, TargetType, TensorOrTupleOfTensorsGeneric, TupleOrTensorOrBoolGeneric
  from torch import device, Tensor
  from torch.nn import Module
label_desc: Use image node_id 40 for calling a global function with example usage: _verify_select_neuron(layer_output, selector) and returns: selected_neurons, selector, selected_neurons