class_docstr: Total weighted labels, predictions, and examples.
class_docstr_tok: ["Total","weighted","labels",",","predictions",",","and","examples","."]
docstr: Initializes accumulator.
docstr_tok: ["Initializes","accumulator","."]
code: def __init__(self):
      """Initializes accumulator."""
      self.total_weighted_labels = 0.0
      self.total_weighted_predictions = 0.0
      self.total_weighted_examples = 0.0
  
imports: from typing import Any, Dict, Iterable, Optional
  import apache_beam
  import numpy
  from tensorflow_model_analysis.metrics import metric_types
  from tensorflow_model_analysis.metrics import metric_util
  from tensorflow_model_analysis.proto import config_pb2
label_desc: Use image node_id 1 to create a new _WeightedLabelsPredictionsExamples object  with example: obj = _WeightedLabelsPredictionsExamples()