code: def reduction_a(net, k, l, m, n):
      with tf.variable_scope("Branch_0"):
          tower_conv = slim.conv2d(
              net,
              n,
              3,
              stride=2,
              padding="VALID",
              scope="Conv2d_1a_3x3",
          )
      with tf.variable_scope("Branch_1"):
          tower_conv1_0 = slim.conv2d(net, k, 1, scope="Conv2d_0a_1x1")
          tower_conv1_1 = slim.conv2d(
              tower_conv1_0, l, 3, scope="Conv2d_0b_3x3"
          )
          tower_conv1_2 = slim.conv2d(
              tower_conv1_1,
              m,
              3,
              stride=2,
              padding="VALID",
              scope="Conv2d_1a_3x3",
          )
      with tf.variable_scope("Branch_2"):
          tower_pool = slim.max_pool2d(
              net, 3, stride=2, padding="VALID", scope="MaxPool_1a_3x3"
          )
      net = tf.concat([tower_conv, tower_conv1_2, tower_pool], 3)
      return net
  
file_path: MMdnn/mmdnn/conversion/examples/tensorflow/models/inception_resnet_v1.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tensorflow.contrib.slim
label_desc: Use image node_id 4 for calling a global function with example usage: reduction_a(net, k, l, m, n) and returns: net