code: def _rand_noise(noise_mean, noise_dev, scale, shape):
      """Generate random noise given a particular scale and shape."""
      noise_shape = [x // scale for x in shape]
      noise_shape = [1 if x == 0 else x for x in noise_shape]
      noise = tf.random.normal(
          shape=noise_shape, mean=noise_mean, stddev=noise_dev
      )
      noise = tf.clip_by_value(
          noise,
          noise_mean - 2.0 * noise_dev,
          noise_mean + 2.0 * noise_dev,
      )
  
      if scale != 1:
          noise = tf.image.resize_images(noise, [shape[0], shape[1]])
          noise = tf.transpose(noise, [0, 2, 1])
          noise = tf.image.resize_images(noise, [shape[0], shape[2]])
          noise = tf.transpose(noise, [0, 2, 1])
      return noise
  
file_path: mesh/mesh_tensorflow/experimental/data_aug_lib.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow.compat.v1
  import tensorflow_probability
  from tensorflow.contrib import image
label_desc: Use image node_id 2 for calling a global function with example usage: _rand_noise(noise_mean, noise_dev, scale, shape) and returns: noise