code: def get_config(self):
      cfg = super().get_config()
      cfg.update({"update_y_pred": self.update_y_pred})
      return cfg
  
imports: from absl.testing import parameterized
  import apache_beam
  from apache_beam.testing import util
  import numpy
  import tensorflow
  from tensorflow_model_analysis.eval_saved_model import testutil
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.metrics import tf_metric_wrapper
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 3 for calling the _CustomMetric obj's underlying member method code with example usage: obj.get_config() and returns: cfg