code: def get_thresholds_from_inputs(
      self,
      pc: PrepareContext,
      max_output_boxes_per_class: int,
      iou_threshold: float,
      score_threshold: float,
  ) -> Tuple[int, float, float]:
      if pc.max_output_boxes_per_class_ is not None:
          max_output_boxes_per_class = max(
              pc.max_output_boxes_per_class_[0], 0
          )
  
      if pc.iou_threshold_ is not None:
          iou_threshold = pc.iou_threshold_[0]
  
      if pc.score_threshold_ is not None:
          score_threshold = pc.score_threshold_[0]
  
      return max_output_boxes_per_class, iou_threshold, score_threshold
  
file_path: onnx/onnx/reference/ops/op_non_max_suppression.py
imports: import dataclasses
  from typing import Optional, Tuple
  import numpy
  from onnx.reference.op_run import OpRun
label_desc: Use image node_id 1 for calling the NonMaxSuppression obj's underlying member method code with example usage: obj.get_thresholds_from_inputs(pc, max_output_boxes_per_class, iou_threshold, score_threshold) and returns: max_output_boxes_per_class,  iou_threshold,  score_threshold