docstr: Faster on gpu device, while dataloading takes up a large portion of the time.
docstr_tok: ["Faster","on","gpu","device",",","while","dataloading","takes","up","a","large","portion","of","the","time","."]
code: def apply_preprocess(self, X, y):
      """
      Faster on gpu device, while dataloading takes up a large portion of the time.
      """
  
      with torch.no_grad():
          if not self.classification:
              y = (y.reshape((-1, 1)) - self.ymn) / self.ysd
          else:
              y = y.reshape((-1, 1))
          X = (X - self.Xmn) / self.sv1
  
          if self.preprocess == constants.Preprocess.ZSCORE:
              X /= self.Xsd
  
          return X, y
  
imports: import os
  import pickle
  import sys
  import time
  import numpy
  import scipy.sparse
  from sklearn.datasets import load_svmlight_file
  import torch
  from torch.utils.data import DataLoader, Dataset
  from torch.utils.data.dataloader import _SingleProcessDataLoaderIter, _MultiProcessingDataLoaderIter, _utils
  from .None import constants
  from .None import syssettings
label_desc: Use image node_id 14 for calling the PrepareData obj's underlying member method code with example usage: obj.apply_preprocess(X, y) and returns: X,  y