code: def _create_metrics(self):
      self.acc, self.acc_op = tf.metrics.accuracy(
          labels=self._label, predictions=self.output
      )
      self.auc, self.auc_op = tf.metrics.auc(
          labels=self._label,
          predictions=self.probability,
          num_thresholds=1000,
      )
      tf.summary.scalar("eval_acc", self.acc)
      tf.summary.scalar("eval_auc", self.auc)
  
imports: import time
  import argparse
  import tensorflow
  import os
  import sys
  import math
  import collections
  from tensorflow.python.client import timeline
  import json
  from tensorflow.python.ops import partitioned_variables
  import ray
  from bigdl.dllib.utils.log4Error import *
  from bigdl.orca import init_orca_context, stop_orca_context, OrcaContext
  from bigdl.orca.data.utils import process_spark_xshards
  from bigdl.orca.learn.utils import maybe_dataframe_to_xshards
  from bigdl.friesian.feature import FeatureTable
label_desc: Use image node_id 7 for calling the WDL obj's underlying member method code with example usage: obj._create_metrics() without return types