code: def compute_loss(self, features, training=False):
      labels = features.pop("rating")
      scores = self(features)
      return self.task(
          labels=labels,
          predictions=scores,
      )
  
file_path: BigDL/python/orca/example/learn/tf2/dcn/dcn_parquet.py
imports: import sys
  from optparse import OptionParser
  import math
  import tensorflow
  import tensorflow_recommenders
  from bigdl.dllib.utils.log4Error import invalidInputError
  from bigdl.orca import init_orca_context
  from bigdl.orca.learn.tf2.estimator import Estimator
  from bigdl.orca.data.tf.data import Dataset
  from bigdl.friesian.feature import FeatureTable
label_desc: Use image node_id 3 for calling the DCN obj's underlying member method code with example usage: obj.compute_loss(features, training) and returns: self