code: def preprocess_patient(self, input_files):
      if self.threeD:
          preprocessor_class = GenericPreprocessor
      else:
          preprocessor_class = PreprocessorFor2D
  
      preprocessor = preprocessor_class(
          self.normalization_schemes,
          self.use_mask_for_norm,
          self.transpose_forward,
          self.intensity_properties,
      )
      d, s, properties = preprocessor.preprocess_test_case(
          input_files,
          self.plans["plans_per_stage"][self.stage]["current_spacing"],
      )
      return d, s, properties
  
imports: import numpy
  from functools import partial
  from typing import Tuple, List, Union
  from scipy.ndimage.filters import gaussian_filter
  from .utils import no_op, pad_nd_image
  import paddle
  from paddle.amp import auto_cast
  from tools.preprocess_utils import GenericPreprocessor, PreprocessorFor2D
  from nnunet.transforms import default_2D_augmentation_params, default_3D_augmentation_params
label_desc: Use image node_id 3 for calling the MultiFoldsPredictor obj's underlying member method code with example usage: obj.preprocess_patient(input_files) and returns: d,  s,  properties