code: def main(_):
      """Run the sample attack"""
      eps = FLAGS.max_epsilon / 255.0
      batch_shape = [
          FLAGS.batch_size,
          FLAGS.image_height,
          FLAGS.image_width,
          3,
      ]
  
      with tf.Graph().as_default():
          x_input = tf.placeholder(tf.float32, shape=batch_shape)
          noisy_images = x_input + eps * tf.sign(
              tf.random_normal(batch_shape)
          )
          x_output = tf.clip_by_value(noisy_images, 0.0, 1.0)
  
          with tf.Session(FLAGS.master) as sess:
              for filenames, images in load_images(
                  FLAGS.input_dir, batch_shape
              ):
                  out_images = sess.run(
                      x_output, feed_dict={x_input: images}
                  )
                  save_images(out_images, filenames, FLAGS.output_dir)
  
file_path: cleverhans/cleverhans_v3.1.0/examples/nips17_adversarial_competition/dev_toolkit/sample_attacks/random_noise/attack_random_noise.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import numpy
  from scipy.misc import imread
  from scipy.misc import imsave
  import tensorflow
label_desc: Use image node_id 3 for calling a global function with example usage: main(_) without return types