code: def train(self, feed_dict):
      for key in feed_dict.keys():
          feed_dict[key] = _utils.convert_shared_float_array_to_numpy(
              feed_dict[key]
          )
  
      _, loss_value = self.sess.run(
          fetches=[self.optimizer, self.loss],
          feed_dict={
              self.tf_input: feed_dict["input"],
              self.tf_index: feed_dict["index"],
              self.tf_style: feed_dict["labels"],
          },
      )
  
      return {"loss": _np.array(loss_value)}
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  from turicreate.toolkits._tf_model import TensorFlowModel
  import numpy
  import turicreate.toolkits._tf_utils
  from turicreate._deps.minimal_package import _minimal_package_import_check
label_desc: Use image node_id 7 for calling the StyleTransferTensorFlowModel obj's underlying member method code with example usage: obj.train(feed_dict) and returns: dict