class_docstr: Defines the SVGDecoder model.
code: def unbottleneck(
      self, x, res_size, reuse=tf.AUTO_REUSE, name_append=""
  ):
      with tf.variable_scope(
          "unbottleneck{}".format(name_append), reuse=reuse
      ):
          x = tf.layers.dense(
              x, res_size, name="dense", activation="tanh"
          )
          return x
  
imports: import copy
  from magenta.contrib import rnn
  from magenta.models.svg_vae import image_vae
  from magenta.models.svg_vae import svg_decoder_loss
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  from tensor2tensor.utils import trainer_lib
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 7 for calling the SVGDecoder obj's underlying member method code with example usage: obj.unbottleneck(x, res_size, reuse, name_append) and returns: x