code: def initialize_augmentation(self):
      if not self.initialization:
          self.choices = np.array(self.choices)
  
          for label, data_group in list(self.data_groups.items()):
              input_shape = data_group.get_shape()
              self.output_shape[label] = np.array(input_shape)
              self.output_shape[label][
                  self.axis[label]
              ] = self.num_chosen
              self.output_shape[label] = tuple(self.output_shape[label])
  
          self.initialization = True
  
imports: import numpy
  from random import shuffle
  from scipy.sparse import csr_matrix
  from deepneuro.utilities.util import add_parameter
  from deepneuro.augmentation.augment import Augmentation
label_desc: Use image node_id 2 for calling the ChooseData obj's underlying member method code with example usage: obj.initialize_augmentation() without return types