code: def parse_init_thresholds(thresholds, default_threshold=0.5):
      if thresholds is not None:
          assert_thresholds_range(to_list(thresholds))
      thresholds = to_list(
          default_threshold if thresholds is None else thresholds
      )
      return thresholds
  
imports: from enum import Enum
  import functools
  import weakref
  import numpy
  from tensorflow.python.compat import compat
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_conversion
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.utils import losses_utils
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.keras.utils.generic_utils import to_list
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import clip_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops import weights_broadcast_ops
  from tensorflow.python.ops.parallel_for import control_flow_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.util import tf_decorator
label_desc: Use image node_id 5 for calling a global function with example usage: parse_init_thresholds(thresholds, default_threshold) and returns: thresholds