class_docstr: Defines the SVGDecoder model.
code: def body(self, features):
      if self._hparams.initializer == "orthogonal":
          raise ValueError(
              "LSTM models fail with orthogonal initializer."
          )
      train = self._hparams.mode == tf_estimator.ModeKeys.TRAIN
      return self.render2cmd_v3_internal(features, self._hparams, train)
  
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 1 for calling the SVGDecoder obj's underlying member method code with example usage: obj.body(features) and returns: self