code: def _padded_forward(
      model: Model[SeqT, SeqT], Xp: Padded, is_train: bool
  ) -> Tuple[Padded, Callable]:
      layer: Model[Array3d, Array3d] = model.layers[0]
      Y, get_dX = layer(Xp.data, is_train)
  
      def backprop(dYp: Padded) -> Padded:
          assert isinstance(dYp, Padded)
          dX = get_dX(dYp.data)
          return Padded(dX, 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/with_array.py
imports: from typing import Callable, Optional, Tuple, TypeVar, Union, cast
  from ..backends import NumpyOps
  from ..config import registry
  from ..model import Model
  from ..types import Array3d, ArrayXd, ListXd, Padded, Ragged
label_desc: Use image node_id 7 for calling a global function with example usage: _padded_forward(model, Xp, is_train) and returns: Padded,  backprop, Padded