code: def test__subtract_confident_thresholds():
      labels = data["labels"]
      pred_probs = data["pred_probs"]
  
      # subtract confident class thresholds and renormalize
      pred_probs_adj = _subtract_confident_thresholds(
          labels, pred_probs
      )
  
      assert (
          pred_probs_adj > 0
      ).all()  # all pred_prob are positive numbers
      assert (abs(1 - pred_probs_adj.sum(axis=1)) < 1e-6).all()
  
imports: import numpy
  import pytest
  from cleanlab import rank
  from cleanlab.internal.label_quality_utils import _subtract_confident_thresholds
  from cleanlab.benchmarking.noise_generation import generate_noise_matrix_from_trace
  from cleanlab.benchmarking.noise_generation import generate_noisy_labels
  from cleanlab import count
  from cleanlab import outlier
  from sklearn.neighbors import NearestNeighbors
label_desc: Use image node_id 6 for calling a global function with example usage: test__subtract_confident_thresholds() without return types