code: def _create_loss(self):
      self._logits = tf.squeeze(self._logits)
      self.loss = tf.losses.sigmoid_cross_entropy(
          self._label,
          self._logits,
          scope="loss",
          reduction=tf.losses.Reduction.SUM_OVER_BATCH_SIZE,
      )
      tf.summary.scalar("loss", self.loss)
  
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 5 for calling the WDL obj's underlying member method code with example usage: obj._create_loss() without return types