code: def initialize(self, data_collection):
      super(CopyChannels, self).initialize(data_collection)
  
      for label, data_group in list(self.data_groups.items()):
          data_shape = list(data_group.get_shape())
  
          if self.new_channel_dim:
              data_shape += [self.channel_multiplier]
          else:
              data_shape[-1] = self.channel_multiplier * data_shape[-1]
  
          self.output_shape[label] = tuple(data_shape)
  
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 2 for calling the CopyChannels obj's underlying member method code with example usage: obj.initialize(data_collection) without return types