code: def apply_mask(Xs: list[T], mask: list[bool]) -> list[T]:
      """Apply mask to list `Xs`, keeping only the elements for which
      mask is True.
  
      :param Xs: List to be masked.
      :type Xs: List[T]
      :param mask: Mask applied to `Xs`. If True, corresponding entry in `Xs` is kept.
      :type mask: List[bool]
      :return: Masked list.
      :rtype: List[T]
      """
      if len(Xs) != len(mask):
          raise ValueError(
              "mask not of same length as list that is to be masked."
          )
      return [x for x, keep in zip(Xs, mask) if keep]
  
imports: from __future__ import annotations
  from typing import TypeVar
  import numpy
  import tensorflow
  import tensorflow.keras.backend
  from innvestigate.backend.types import Layer, OptionalList, ShapeTuple, Tensor
label_desc: Use image node_id 12 for calling a global function with example usage: apply_mask(Xs, mask) and returns: unknown