code: def initialise_network(self):
      w_regularizer = None
      b_regularizer = None
      reg_type = self.net_param.reg_type.lower()
      decay = self.net_param.decay
      if reg_type == "l2" and decay > 0:
          from tensorflow.contrib.layers.python.layers import (
              regularizers,
          )
  
          w_regularizer = regularizers.l2_regularizer(decay)
          b_regularizer = regularizers.l2_regularizer(decay)
      elif reg_type == "l1" and decay > 0:
          from tensorflow.contrib.layers.python.layers import (
              regularizers,
          )
  
          w_regularizer = regularizers.l1_regularizer(decay)
          b_regularizer = regularizers.l1_regularizer(decay)
  
      self.net = ApplicationNetFactory.create("toynet")(
          num_classes=self.multioutput_param.num_classes,
          w_initializer=InitializerFactory.get_initializer(
              name=self.net_param.weight_initializer
          ),
          b_initializer=InitializerFactory.get_initializer(
              name=self.net_param.bias_initializer
          ),
          w_regularizer=w_regularizer,
          b_regularizer=b_regularizer,
          acti_func=self.net_param.activation_function,
      )
  
imports: from __future__ import absolute_import, print_function
  import tensorflow
  from niftynet.application.base_application import BaseApplication
  from niftynet.engine.application_factory import ApplicationNetFactory, InitializerFactory, OptimiserFactory
  from niftynet.io.image_reader import ImageReader
  from niftynet.engine.sampler_grid_v2 import GridSampler
  from niftynet.engine.sampler_resize_v2 import ResizeSampler
  from niftynet.engine.sampler_uniform_v2 import UniformSampler
  from niftynet.engine.sampler_weighted_v2 import WeightedSampler
  from niftynet.engine.sampler_balanced_v2 import BalancedSampler
  from niftynet.engine.windows_aggregator_grid import GridSamplesAggregator
  from niftynet.engine.windows_aggregator_resize import ResizeSamplesAggregator
  from niftynet.engine.windows_aggregator_identity import WindowAsImageAggregator
  from niftynet.layer.loss_segmentation import LossFunction
  from niftynet.layer.post_processing import PostProcessingLayer
  from niftynet.engine.application_variables import CONSOLE, TF_SUMMARIES, NETWORK_OUTPUT
label_desc: Use image node_id 14 for calling the MultiOutputApplication obj's underlying member method code with example usage: obj.initialise_network() without return types