class_docstr: Computes min label position metric.
class_docstr_tok: ["Computes","min","label","position","metric","."]
code: def extract_output(
      self, accumulator: _MinLabelPositionAccumulator
  ) -> Dict[metric_types.MetricKey, float]:
      if accumulator.total_weighted_examples > 0:
          value = (
              accumulator.total_min_position
              / accumulator.total_weighted_examples
          )
      else:
          value = float("nan")
      return {self._key: value}
  
file_path: model-analysis/tensorflow_model_analysis/metrics/min_label_position.py
imports: from typing import Dict, Iterable, List, 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
  from tensorflow_model_analysis.utils import util
label_desc: Use image node_id 5 for calling the _MinLabelPositionCombiner obj's underlying member method code with example usage: obj.extract_output(accumulator) and returns: dict