code: def export_weights(self):
      _tf = _lazy_import_tensorflow()
  
      tf_export_params = {}
  
      with self.st_graph.as_default():
          tvars = _tf.trainable_variables()
          tvars_vals = self.sess.run(tvars)
  
      for var, val in zip(tvars, tvars_vals):
          if "weight" in var.name:
              if "conv" in var.name:
                  tf_export_params[
                      var.name.split(":")[0]
                  ] = _utils.convert_conv2d_tf_to_coreml(val)
              else:
                  tf_export_params[
                      var.name.split(":")[0]
                  ] = _utils.convert_dense_tf_to_coreml(val)
          else:
              tf_export_params[var.name.split(":")[0]] = _np.array(val)
      for layer_name in tf_export_params.keys():
          tf_export_params[layer_name] = _np.ascontiguousarray(
              tf_export_params[layer_name]
          )
      return tf_export_params
  
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 9 for calling the StyleTransferTensorFlowModel obj's underlying member method code with example usage: obj.export_weights() and returns: tf_export_params