class_docstr: Base combiner for aggregating metrics for keras based models.
class_docstr_tok: ["Base","combiner","for","aggregating","metrics","for","keras","based","models","."]
code: def compact(
      self, accumulator: tf_metric_accumulators.TFMetricsAccumulator
  ) -> tf_metric_accumulators.TFMetricsAccumulator:
      self._process_batch(accumulator)
      self._num_compacts.inc(1)
      return accumulator
  
imports: import collections
  from itertools import chain
  from typing import Dict, Iterable, List, Optional
  import apache_beam
  import numpy
  import tensorflow
  from tensorflow_model_analysis import constants
  from tensorflow_model_analysis.api import types
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.metrics import tf_metric_accumulators
  from tensorflow_model_analysis.proto import config_pb2
  from tensorflow_model_analysis.utils import model_util
  from tensorflow_model_analysis.utils import util
label_desc: Use image node_id 11 for calling the _KerasCombiner obj's underlying member method code with example usage: obj.compact(accumulator) and returns: accumulator