code: def block35(
      net,
      input_num_channels,
      scale=1.0,
      with_act=True,
      act_type="relu",
      mirror_attr={},
      name="",
  ):
      M = 1.0
      tower_conv = ConvFactory(
          net,
          int(input_num_channels * 0.25 * M),
          (1, 1),
          name=name + "_conv",
      )
      tower_conv1_0 = ConvFactory(
          net,
          int(input_num_channels * 0.25 * M),
          (1, 1),
          name=name + "_conv1_0",
      )
      tower_conv1_1 = ConvFactory(
          tower_conv1_0,
          int(input_num_channels * 0.25 * M),
          (3, 3),
          pad=(1, 1),
          name=name + "_conv1_1",
      )
      tower_conv2_0 = ConvFactory(
          net,
          int(input_num_channels * 0.25 * M),
          (1, 1),
          name=name + "_conv2_0",
      )
      tower_conv2_1 = ConvFactory(
          tower_conv2_0,
          int(input_num_channels * 0.375 * M),
          (3, 3),
          pad=(1, 1),
          name=name + "_conv2_1",
      )
      tower_conv2_2 = ConvFactory(
          tower_conv2_1,
          int(input_num_channels * 0.5 * M),
          (3, 3),
          pad=(1, 1),
          name=name + "_conv2_2",
      )
      tower_mixed = mx.symbol.Concat(
          *[tower_conv, tower_conv1_1, tower_conv2_2]
      )
      tower_out = ConvFactory(
          tower_mixed,
          input_num_channels,
          (1, 1),
          with_act=False,
          name=name + "_conv_out",
      )
  
      net = net + scale * tower_out
      if with_act:
          act = mx.symbol.Activation(
              data=net, act_type=act_type, attr=mirror_attr
          )
          return act
      else:
          return net
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import mxnet
  import numpy
  from config import config
label_desc: Use image node_id 8 for calling a global function with example usage: block35(net, input_num_channels, scale, with_act, act_type, mirror_attr, name) and returns: act, net