def __init__(self,
               combiner_ops,
               is_combining_accumulators):
    """Init method for _PackedCombinerWrapper.

    Args:
      combiner_ops: A List `analysis_graph_builder._CombinerOpWrapper` objects.
      is_combining_accumulators: A bool which indicates whether this is
        combining single or batched inputs, or already accumulated objects.
    """
    super().__init__(*[
        _CombinerWrapper(c.combiner, is_combining_accumulators)
        for c in combiner_ops
    ])
    self._is_combining_accumulators = is_combining_accumulators
    if self._is_combining_accumulators:
      # When combining accumulators, we expect to have only a single key which
      # represents the label of the individual combine.
      for op in combiner_ops:
        assert len(op.keys) == 1
      self._combiner_label_to_index = {
          op.keys[0]: index for index, op in enumerate(combiner_ops)}
    else:
      self._combiner_keys = [c.keys for c in combiner_ops]
    self._combiner_labels = [c.label for c in combiner_ops]
Init method for _PackedCombinerWrapper.

    Args:
      combiner_ops: A List `analysis_graph_builder._CombinerOpWrapper` objects.
      is_combining_accumulators: A bool which indicates whether this is
        combining single or batched inputs, or already accumulated objects.
    
tensorflow_transform/beam/analyzer_impls.py