code: def _get_min_pred_prob(
      predictions: List[np.ndarray],
  ) -> float:
      """Returns min pred_prob out of all predictions."""
      pred_probs = [1.0]  # avoid calling np.min on empty array.
      for prediction in predictions:
          for class_prediction in prediction:
              pred_probs.extend(list(class_prediction[:, -1]))
  
      min_pred_prob = np.min(pred_probs)
      return min_pred_prob
  
imports: import warnings
  from cleanlab.internal.constants import ALPHA, CUSTOM_SCORE_WEIGHT_BADLOC, CUSTOM_SCORE_WEIGHT_OVERLOOKED, CUSTOM_SCORE_WEIGHT_SWAP, EUC_FACTOR, HIGH_PROBABILITY_THRESHOLD, LOW_PROBABILITY_THRESHOLD, MAX_ALLOWED_BOX_PRUNE, TINY_VALUE, TEMPERATURE, LABEL_OVERLAP_THRESHOLD
  import copy
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, TypeVar
  import numpy
  from cleanlab.internal.object_detection_utils import softmin1d, assert_valid_aggregation_weights, assert_valid_inputs
label_desc: Use image node_id 4 for calling a global function with example usage: _get_min_pred_prob(predictions) and returns: min_pred_prob