code: def decompress_step(source, hparams, first_relu, name):
      """Decompression function."""
      with tf.variable_scope(name):
          shape = common_layers.shape_list(source)
          multiplier = 2
          kernel = (1, 1)
          thicker = common_layers.conv_block(
              source,
              hparams.hidden_size * multiplier,
              [((1, 1), kernel)],
              first_relu=first_relu,
              name="decompress_conv",
          )
          return tf.reshape(
              thicker, [shape[0], shape[1] * 2, 1, hparams.hidden_size]
          )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  from six.moves import range
  from tensor2tensor.layers import common_layers
  from tensor2tensor.models import transformer
  from tensor2tensor.utils import beam_search
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
  from tensorflow.python.training import moving_averages
label_desc: Use image node_id 6 for calling a global function with example usage: decompress_step(source, hparams, first_relu, name) and returns: tf