class_docstr: Computes min label position metric.
class_docstr_tok: ["Computes","min","label","position","metric","."]
code: def __init__(
      self,
      key: metric_types.MetricKey,
      eval_config: Optional[config_pb2.EvalConfig],
      example_weighted: bool,
      label_key: Optional[str],
  ):
      self._key = key
      self._eval_config = eval_config
      self._example_weighted = example_weighted
      self._label_key = label_key
  
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 1 to create a new _MinLabelPositionCombiner object from inherited base classes: beam with example: obj = _MinLabelPositionCombiner(key, eval_config, example_weighted, label_key)