code: def forward(
      model: Model[InT, OutT], Xs: InT, is_train: bool
  ) -> Tuple[OutT, Callable]:
      lengths = NUMPY_OPS.asarray1i([len(x) for x in Xs])
  
      def backprop(dY: OutT) -> InT:
          return model.ops.unflatten(dY, lengths)
  
      return model.ops.flatten(Xs), backprop
  
imports: from typing import Callable, List, Tuple, TypeVar
  from ..backends import NumpyOps
  from ..config import registry
  from ..model import Model
  from ..types import Array2d
label_desc: Use image node_id 2 for calling a global function with example usage: forward(model, Xs, is_train) and returns: model,  backprop, model