code: def preprocess(self, data_group):
      input_data = data_group.preprocessed_case
  
      if self.new_channel_dim:
          output_data = np.tile(
              input_data[..., np.newaxis],
              (1, 1, self.channel_multiplier),
          )
      else:
          output_data = np.tile(
              input_data, (1, 1, self.channel_multiplier)
          )
  
      data_group.preprocessed_case = output_data
      self.output_data = output_data
  
imports: import subprocess
  import os
  import numpy
  import itertools
  from deepneuro.preprocessing.preprocessor import Preprocessor
  from deepneuro.utilities.util import add_parameter, quotes
label_desc: Use image node_id 3 for calling the CopyChannels obj's underlying member method code with example usage: obj.preprocess(data_group) without return types