code: def block35(
      net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=None
  ):
      """Builds the 35x35 resnet block."""
      with tf.variable_scope(scope, "Block35", [net], reuse=reuse):
          with tf.variable_scope("Branch_0"):
              tower_conv = slim.conv2d(net, 32, 1, scope="Conv2d_1x1")
          with tf.variable_scope("Branch_1"):
              tower_conv1_0 = slim.conv2d(
                  net, 32, 1, scope="Conv2d_0a_1x1"
              )
              tower_conv1_1 = slim.conv2d(
                  tower_conv1_0, 32, 3, scope="Conv2d_0b_3x3"
              )
          with tf.variable_scope("Branch_2"):
              tower_conv2_0 = slim.conv2d(
                  net, 32, 1, scope="Conv2d_0a_1x1"
              )
              tower_conv2_1 = slim.conv2d(
                  tower_conv2_0, 48, 3, scope="Conv2d_0b_3x3"
              )
              tower_conv2_2 = slim.conv2d(
                  tower_conv2_1, 64, 3, scope="Conv2d_0c_3x3"
              )
          mixed = tf.concat(
              axis=3, values=[tower_conv, tower_conv1_1, tower_conv2_2]
          )
          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: cleverhans/cleverhans_v3.1.0/examples/nips17_adversarial_competition/dev_toolkit/sample_defenses/ens_adv_inception_resnet_v2/inception_resnet_v2.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import warnings
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: block35(net, scale, activation_fn, scope, reuse) and returns: net