code: def convert_pytorch_default_inputs(
      model: Model, X: Any, is_train: bool
  ) -> Tuple[ArgsKwargs, Callable[[ArgsKwargs], Any]]:
      shim = cast(PyTorchShim, model.shims[0])
      xp2torch_ = lambda x: xp2torch(
          x, requires_grad=is_train, device=shim.device
      )
      converted = convert_recursive(is_xp_array, xp2torch_, X)
      if isinstance(converted, ArgsKwargs):
  
          def reverse_conversion(dXtorch):
              return convert_recursive(
                  is_torch_array, torch2xp, dXtorch
              )
  
          return converted, reverse_conversion
      elif isinstance(converted, dict):
  
          def reverse_conversion(dXtorch):
              dX = convert_recursive(is_torch_array, torch2xp, dXtorch)
              return dX.kwargs
  
          return (
              ArgsKwargs(args=tuple(), kwargs=converted),
              reverse_conversion,
          )
      elif isinstance(converted, (tuple, list)):
  
          def reverse_conversion(dXtorch):
              dX = convert_recursive(is_torch_array, torch2xp, dXtorch)
              return dX.args
  
          return (
              ArgsKwargs(args=tuple(converted), kwargs={}),
              reverse_conversion,
          )
      else:
  
          def reverse_conversion(dXtorch):
              dX = convert_recursive(is_torch_array, torch2xp, dXtorch)
              return dX.args[0]
  
          return (
              ArgsKwargs(args=(converted,), kwargs={}),
              reverse_conversion,
          )
  
file_path: thinc/thinc/layers/pytorchwrapper.py
imports: from typing import Any, Callable, Dict, Optional, Tuple, cast
  from ..compat import torch
  from ..config import registry
  from ..model import Model
  from ..shims import PyTorchGradScaler, PyTorchShim
  from ..types import ArgsKwargs, Floats3d, Padded
  from ..util import convert_recursive, is_torch_array, is_xp_array, partial, torch2xp, xp2torch
label_desc: Use image node_id 6 for calling a global function with example usage: convert_pytorch_default_inputs(model, X, is_train) and returns: converted,  reverse_conversion, convert_recursive, ArgsKwargs,  reverse_conversion, dX, ArgsKwargs,  reverse_conversion, ArgsKwargs,  reverse_conversion, dX, dX