code: def _dropout_array(
      model: Model[InT, InT], X: ArrayXd, is_train: bool
  ) -> Tuple[ArrayXd, Callable]:
      rate = model.attrs["dropout_rate"]
      mask = model.ops.get_dropout_mask(X.shape, rate)
  
      def backprop(dY: ArrayXd) -> ArrayXd:
          return dY * mask
  
      return cast(ArrayXd, X * mask), backprop
  
file_path: thinc/thinc/layers/dropout.py
imports: from typing import Callable, List, Sequence, Tuple, TypeVar, Union, cast
  from ..config import registry
  from ..model import Model
  from ..types import ArrayXd, Padded, Ragged
label_desc: Use image node_id 3 for calling a global function with example usage: _dropout_array(model, X, is_train) and returns: cast,  backprop, unknown