code: def from_train_op(
      cls,
      train_op,
      loss,
      *,
      inputs=None,
      labels=None,
      metrics=None,
      updates=None,
      sess=None,
      dataset=None,
      tensor_with_value=None,
      session_config=None,
      model_dir=None,
  ):
      sess = TFOptimizer._get_or_create_session(sess)
      grads, variables = TFOptimizer._get_vars_grads_from_train_op(
          train_op
      )
      if dataset is None:
          dataset = TFOptimizer._get_dataset_from_loss(loss)
      _ = dataset.tensors  # trigger create tensors if not available
      dataset_inputs = dataset._original_tensors
      if isinstance(dataset_inputs, tuple) and len(dataset_inputs) == 2:
          if inputs is None:
              inputs = dataset_inputs[0]
  
          if labels is None:
              labels = dataset_inputs[1]
      else:
          if inputs is None:
              inputs = dataset_inputs
  
          if labels is None:
              labels = []
  
      inputs = nest.flatten(inputs)
      labels = nest.flatten(labels)
      from zoo.tfpark.zoo_optimizer import FakeOptimMethod
  
      return TFOptimizer._from_grads(
          loss=loss,
          sess=sess,
          inputs=inputs,
          labels=labels,
          grads=grads,
          variables=variables,
          dataset=dataset,
          metrics=metrics,
          tensor_with_value=tensor_with_value,
          optim_method=FakeOptimMethod(),
          session_config=session_config,
          updates=updates,
          model_dir=model_dir,
          train_op=train_op,
      )
  
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 7 for calling the TFOptimizer obj's underlying member method code with example usage: obj.from_train_op(cls, train_op, loss) and returns: TFOptimizer