code: def clear_data_processors(self):
      self.augmentations = []
      self.preprocessors = []
  
      # A little inefficient -- will require loading data again to understand data shape.
      for data_group_label in list(self.data_groups.keys()):
          self.data_groups[data_group_label].output_shape = None
  
imports: import os
  import csv
  import numpy
  import tables
  import copy
  from tqdm import tqdm
  from deepneuro.augmentation.augment import Copy
  from deepneuro.utilities.conversion import read_image_files
  from deepneuro.data.data_group import DataGroup
  from deepneuro.data.data_load import parse_directories, parse_filepaths, parse_hdf5, parse_csv, parse_numpy
  from deepneuro.utilities.util import add_parameter
label_desc: Use image node_id 10 for calling the DataCollection obj's underlying member method code with example usage: obj.clear_data_processors() without return types