class_docstr: Confusion Matrix accumulator with kwargs used to compute it.
  
  Confusion matrix for classification and retrieval tasks.
  See https://en.wikipedia.org/wiki/Confusion_matrix for more info.
  
  Attributes:
    tp: True positives count.
    tn: True negatives count.
    fp: False positives count.
    fn: False negative count.
    average: The average type of which this confusion matrix is computed.
    dtype: data type of the instance numpy array. None by default, dtype is
      deduced by numpy at construction.
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code: def __add__(self, other):
      tp = self.tp + other.tp
      tn = self.tn + other.tn
      fp = self.fp + other.fp
      fn = self.fn + other.fn
      return _ConfusionMatrix(tp, tn, fp, fn)
  
imports: from collections.abc import Iterable, Sequence
  import dataclasses
  import enum
  import itertools
  from typing import Any
  import numpy
  from numpy import typing
  from tensorflow_model_analysis.experimental.lazytf import api
label_desc: Use image node_id 5 for calling the _ConfusionMatrix obj's underlying member method code with example usage: obj.__add__(other) and returns: _ConfusionMatrix