code: def decompress_decoder(
      inputs, hparams, strides=(2, 2), kernel=(3, 3), name=None
  ):
      """Decoder that decompresses 2-D inputs by 2**num_compress_steps.
  
      Args:
        inputs: Tensor of shape [batch, compress_height, compress_width, channels].
        hparams: HParams.
        strides: Tuple, strides for conv block.
        kernel: Tuple, kernel window size for conv block.
        name: string, variable scope.
  
      Returns:
        Tensor of shape [batch, height, width, hparams.hidden_size].
      """
      with tf.variable_scope(name, default_name="decompress"):
          x = inputs
          x = tf.layers.dense(
              x, hparams.hidden_size, name=name + "_dense"
          )
          x = residual_block_layer(x, hparams)
          for i in range(hparams.num_compress_steps // 2):
              j = hparams.num_compress_steps // 2 - i - 1
              with tf.variable_scope(name + "_%d" % j):
                  if hparams.do_decompress_attend:
                      y = compress_self_attention_layer(
                          x, hparams, name="decompress_selfatt"
                      )
                      x += y
                  y = tf.layers.conv2d_transpose(
                      x,
                      hparams.hidden_size,
                      kernel,
                      strides=strides,
                      padding="SAME",
                      activation=tf.nn.relu if i > 0 else None,
                      name="decompress_conv",
                  )
                  x = y
          return x
  
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_image_attention
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import transformer_layers
  from tensor2tensor.utils import beam_search
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
  import tensorflow_probability
label_desc: Use image node_id 10 for calling a global function with example usage: decompress_decoder(inputs, hparams, strides, kernel, name) and returns: x