code: def lenpred_mlp(name, logits, hidden_size, bound):
      with tf.variable_scope(name, reuse=tf.AUTO_REUSE):
          logits = tf.layers.dense(logits, hidden_size)
          logits = tf.nn.elu(logits)
          logits = tf.layers.dense(logits, hidden_size)
          logits = tf.nn.elu(logits)
          logits = tf.layers.dense(logits, bound * 2 + 1)
      return logits
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from six.moves import range
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import transformer_glow_layers_ops
  from tensor2tensor.models.transformer import transformer_decoder_layer
  from tensor2tensor.models.transformer import transformer_encoder
  from tensor2tensor.models.transformer import transformer_prepare_encoder
  from tensor2tensor.utils import learning_rate
  from tensor2tensor.utils import mlperf_log
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 11 for calling a global function with example usage: lenpred_mlp(name, logits, hidden_size, bound) and returns: logits