code: def isemhash_bottleneck(
      x,
      bottleneck_bits,
      bottleneck_noise,
      discretize_warmup_steps,
      mode,
      isemhash_noise_dev=0.5,
      isemhash_mix_prob=0.5,
  ):
      """Improved semantic hashing bottleneck."""
      with tf.variable_scope("isemhash_bottleneck"):
          x = tf.layers.dense(x, bottleneck_bits, name="dense")
          y = common_layers.saturating_sigmoid(x)
          if (
              isemhash_noise_dev > 0
              and mode == tf_estimator.ModeKeys.TRAIN
          ):
              noise = tf.truncated_normal(
                  common_layers.shape_list(x),
                  mean=0.0,
                  stddev=isemhash_noise_dev,
              )
              y = common_layers.saturating_sigmoid(x + noise)
          d = tf.to_float(tf.less(0.5, y)) + y - tf.stop_gradient(y)
          d = 2.0 * d - 1.0  # Move from [0, 1] to [-1, 1].
          if mode == tf_estimator.ModeKeys.TRAIN:  # Flip some bits.
              noise = tf.random_uniform(common_layers.shape_list(x))
              noise = (
                  2.0 * tf.to_float(tf.less(bottleneck_noise, noise))
                  - 1.0
              )
              d *= noise
              d = common_layers.mix(
                  d,
                  2.0 * y - 1.0,
                  discretize_warmup_steps,
                  mode == tf_estimator.ModeKeys.TRAIN,
                  max_prob=isemhash_mix_prob,
              )
          return d, 0.0
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from functools import partial
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_image_attention
  from tensor2tensor.layers import common_layers
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
  import tensorflow_probability
  from tensorflow.python.training import moving_averages
label_desc: Use image node_id 25 for calling a global function with example usage: isemhash_bottleneck(x, bottleneck_bits, bottleneck_noise, discretize_warmup_steps, mode, isemhash_noise_dev, isemhash_mix_prob) and returns: d,  int