class_docstr: Base combiner for aggregating metrics for keras based models.
class_docstr_tok: ["Base","combiner","for","aggregating","metrics","for","keras","based","models","."]
docstr: Updates state for metrics associated with model.
code: def _update_state(
      self, accumulator: tf_metric_accumulators.TFMetricsAccumulator
  ):
      """Updates state for metrics associated with model."""
      raise NotImplementedError(
          "Subclasses are expected to override this."
      )
  
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 6 for calling the _KerasCombiner obj's underlying member method code with example usage: obj._update_state(accumulator) without return types