code: def export_training_model(
      export_dir,
      loss,
      sess,
      inputs,
      labels=None,
      predictions=None,
      metrics=None,
      tensor_with_value=None,
      updates=None,
  ):
      grads, variables = TFOptimizer._get_vars_grads(loss)
  
      TFModel.export(
          export_dir,
          loss,
          sess,
          inputs,
          labels,
          predictions,
          grads,
          variables,
          loss.graph,
          tensor_with_value,
          metrics,
          updates,
      )
      logging.info(
          "Exported TensorFlow model in {} for training".format(
              export_dir
          )
      )
  
imports: import json
  import logging
  import os
  import sys
  import tempfile
  from bigdl.nn.criterion import Criterion
  from bigdl.nn.layer import Layer
  from bigdl.optim.optimizer import MaxEpoch, EveryEpoch
  from bigdl.util.common import to_list, JavaValue
  from zoo.common.utils import callZooFunc
  from zoo.feature.common import FeatureSet
  from zoo.pipeline.api.keras.engine.topology import to_bigdl_metric, Loss, OptimMethod
  from zoo.pipeline.api.net.utils import find_placeholders, to_bigdl_optim_method, find_tensors
  from zoo.pipeline.estimator import Estimator
  from zoo.util import nest
  from zoo.util.triggers import EveryEpoch
  from zoo.util.triggers import ZooTrigger
  from zoo.tfpark.tf_dataset import TFNdarrayDataset, check_data_compatible
  from zoo.tfpark.tf_dataset import _standarize_feature_label_dataset
label_desc: Use image node_id 10 for calling the TFOptimizer obj's underlying member method code with example usage: obj.export_training_model(export_dir, loss, sess, inputs, labels, predictions, metrics, tensor_with_value, updates) without return types