code: def _process_preprocessing(
      self, preprocessing: Preprocessing
  ) -> PreprocessArgs:
      if preprocessing is None:
          preprocessing = dict()
  
      unsupported = set(preprocessing.keys()) - {
          "mean",
          "std",
          "axis",
          "flip_axis",
      }
      if len(unsupported) > 0:
          raise ValueError(
              f"unknown preprocessing key: {unsupported.pop()}"
          )
  
      mean = preprocessing.get("mean", None)
      std = preprocessing.get("std", None)
      axis = preprocessing.get("axis", None)
      flip_axis = preprocessing.get("flip_axis", None)
  
      def to_tensor(x: Any) -> Optional[ep.Tensor]:
          if x is None:
              return None
          if isinstance(x, ep.Tensor):
              return x
          try:
              y = ep.astensor(x)  # might raise ValueError
              if not isinstance(y, type(self._dummy)):
                  raise ValueError
              return y
          except ValueError:
              return ep.from_numpy(self._dummy, x)
  
      mean_ = to_tensor(mean)
      std_ = to_tensor(std)
  
      def apply_axis(
          x: Optional[ep.Tensor], axis: int
      ) -> Optional[ep.Tensor]:
          if x is None:
              return None
          if x.ndim != 1:
              raise ValueError(
                  f"non-None axis requires a 1D tensor, got {x.ndim}D"
              )
          if axis >= 0:
              raise ValueError(
                  "expected axis to be None or negative, -1 refers to the last axis"
              )
          return atleast_kd(x, -axis)
  
      if axis is not None:
          mean_ = apply_axis(mean_, axis)
          std_ = apply_axis(std_, axis)
  
      return mean_, std_, flip_axis
  
imports: from typing import TypeVar, Callable, Optional, Tuple, Any
  from abc import ABC, abstractmethod
  import copy
  import eagerpy
  from ..types import Bounds, BoundsInput, Preprocessing
  from ..devutils import atleast_kd
label_desc: Use image node_id 7 for calling the ModelWithPreprocessing obj's underlying member method code with example usage: obj._process_preprocessing(preprocessing) and returns: mean_,  std_,  flip_axis, atleast_kd, None, x, y, None, ep