class_docstr: Creates histogram from labels, predictions, and example weights.
class_docstr_tok: ["Creates","histogram","from","labels",",","predictions",",","and","example","weights","."]
code: def create_accumulator(self) -> _CalibrationHistogramCombinerAcctype:
      # The number of accumulator (histogram) buckets is variable and depends on
      # the number of distinct intervals that are matched during calls to
      # add_inputs. This allows the histogram size to start small and gradually
      # grow size during calls to merge until reaching the final histogram.
      return {}
  
file_path: model-analysis/tensorflow_model_analysis/metrics/calibration_histogram.py
imports: import dataclasses
  import operator
  from typing import Dict, Iterable, List, Optional
  import apache_beam
  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 3 for calling the _CalibrationHistogramCombiner obj's underlying member method code with example usage: obj.create_accumulator() and returns: dict