code: def block17(
      net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=None
  ):
      """Builds the 17x17 resnet block."""
      with tf.variable_scope(scope, "Block17", [net], reuse=reuse):
          with tf.variable_scope("Branch_0"):
              tower_conv = slim.conv2d(net, 128, 1, scope="Conv2d_1x1")
          with tf.variable_scope("Branch_1"):
              tower_conv1_0 = slim.conv2d(
                  net, 128, 1, scope="Conv2d_0a_1x1"
              )
              tower_conv1_1 = slim.conv2d(
                  tower_conv1_0, 128, [1, 7], scope="Conv2d_0b_1x7"
              )
              tower_conv1_2 = slim.conv2d(
                  tower_conv1_1, 128, [7, 1], scope="Conv2d_0c_7x1"
              )
          mixed = tf.concat([tower_conv, tower_conv1_2], 3)
          up = slim.conv2d(
              mixed,
              net.get_shape()[3],
              1,
              normalizer_fn=None,
              activation_fn=None,
              scope="Conv2d_1x1",
          )
          net += scale * up
          if activation_fn:
              net = activation_fn(net)
      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 2 for calling a global function with example usage: block17(net, scale, activation_fn, scope, reuse) and returns: net