code: def create(
      loss_tensor,
      sess,
      inputs,
      labels,
      predictions,
      grads,
      variables,
      graph,
      tensors_with_value,
      session_config,
      metrics,
      updates,
      model_dir,
      train_op=None,
  ):
      if model_dir is None:
          model_dir = tempfile.mkdtemp()
      else:
          if not os.path.isdir(model_dir):
              os.makedirs(model_dir)
  
      meta, saver, val_methods = TFModel.export(
          model_dir,
          loss_tensor,
          sess,
          inputs,
          labels,
          predictions,
          grads,
          variables,
          graph,
          tensors_with_value,
          metrics,
          updates,
          train_op,
      )
  
      training_helper_layer = TFTrainingHelper(
          model_dir, session_config, saver, meta, sess
      )
  
      criterion = IdentityCriterion()
  
      return TFModel(training_helper_layer, criterion, val_methods)
  
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 9 for calling the TFModel obj's underlying member method code with example usage: obj.create(loss_tensor, sess, inputs, labels, predictions, grads, variables, graph, tensors_with_value, session_config, metrics, updates, model_dir, train_op) and returns: TFModel