class_docstr: Creates multi-label confusion matrix at thresholds from standard inputs.
class_docstr_tok: ["Creates","multi-label","confusion","matrix","at","thresholds","from","standard","inputs","."]
code: def __init__(
      self,
      key: metric_types.PlotKey,
      eval_config: Optional[config_pb2.EvalConfig],
      example_weighted: bool,
      thresholds: List[float],
  ):
      self._key = key
      self._eval_config = eval_config
      self._example_weighted = example_weighted
      self._thresholds = thresholds if thresholds else [0.5]
  
file_path: model-analysis/tensorflow_model_analysis/metrics/multi_label_confusion_matrix_plot.py
imports: from typing import Dict, Iterable, List, Optional, NamedTuple
  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
  from tensorflow_model_analysis.proto import metrics_for_slice_pb2
label_desc: Use image node_id 1 to create a new _MultiLabelConfusionMatrixPlotCombiner object from inherited base classes: beam with example: obj = _MultiLabelConfusionMatrixPlotCombiner(key, eval_config, example_weighted, thresholds)