class_docstr: Data Preprocessing.
  
  Base class for applying common real-time data preprocessing.
  
  This class is meant to be used as an argument of `input_data`. When training
  a model, the defined pre-processing methods will be applied at both
  training and testing time. Note that DataAugmentation is similar to
  DataPreprocessing, but only applies at training time.
  
  Arguments:
      None.
  
  Parameters:
      methods: `list of function`. Augmentation methods to apply.
      args: A `list` of arguments to use for these methods.
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docstr: add_samplewise_zero_center.
  
  Zero center each sample by subtracting it by its mean.
  
  Returns:
      Nothing.
docstr_tok: ["add_samplewise_zero_center",".","Zero","center","each","sample","by","subtracting","it","by","its","mean",".","Returns",":","Nothing","."]
code: def add_samplewise_zero_center(self):
      """add_samplewise_zero_center.
  
      Zero center each sample by subtracting it by its mean.
  
      Returns:
          Nothing.
  
      """
      self.methods.append(self._samplewise_zero_center)
      self.args.append(None)
  
imports: from __future__ import division, print_function, absolute_import
  import numpy
  import pickle
  import tensorflow.compat.v1
label_desc: Use image node_id 6 for calling the DataPreprocessing obj's underlying member method code with example usage: obj.add_samplewise_zero_center() without return types