code: def _dropout_padded(
      model: Model[InT, InT], Xp: Padded, is_train: bool
  ) -> Tuple[Padded, Callable]:
      X = Xp.data
      mask = model.ops.get_dropout_mask(
          X.shape, model.attrs["dropout_rate"]
      )
      Y = X * mask
  
      def backprop(dYp: Padded) -> Padded:
          return Padded(
              dYp.data * mask, dYp.size_at_t, dYp.lengths, dYp.indices
          )
  
      return Padded(Y, Xp.size_at_t, Xp.lengths, Xp.indices), 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 4 for calling a global function with example usage: _dropout_padded(model, Xp, is_train) and returns: Padded,  backprop, Padded