code: def is_evenly_distributed_thresholds(thresholds):
      """Check if the thresholds list is evenly distributed.
  
      We could leverage evenly distributed thresholds to use less memory when
      calculate metrcis like AUC where each individual threshold need to be
      evaluated.
  
      Args:
        thresholds: A python list or tuple, or 1D numpy array whose value is
          ranged in [0, 1].
  
      Returns:
        boolean, whether the values in the inputs are evenly distributed.
      """
      # Check the list value and see if it is evenly distributed.
      num_thresholds = len(thresholds)
      if num_thresholds < 3:
          return False
      even_thresholds = np.arange(num_thresholds, dtype=np.float32) / (
          num_thresholds - 1
      )
      return np.allclose(
          thresholds, even_thresholds, atol=backend.epsilon()
      )
  
imports: from enum import Enum
  import numpy
  from keras import backend
  from keras import ops
  from keras.losses.loss import squeeze_to_same_rank
  from keras.utils.python_utils import to_list
label_desc: Use image node_id 4 for calling a global function with example usage: is_evenly_distributed_thresholds(thresholds) and returns: np, False