class_docstr: Type of AUC summation method.
  
  https://en.wikipedia.org/wiki/Riemann_sum)
  
  Contains the following values:
  * 'interpolation': Applies mid-point summation scheme for `ROC` curve. For
    `PR` curve, interpolates (true/false) positives but not the ratio that is
    precision (see Davis & Goadrich 2006 for details).
  * 'minoring': Applies left summation for increasing intervals and right
    summation for decreasing intervals.
  * 'majoring': Applies right summation for increasing intervals and left
    summation for decreasing intervals.
class_docstr_tok: ["Type","of","AUC","summation","method",".","https",":","\/\/en.wikipedia.org\/wiki\/Riemann_sum",")","Contains","the","following","values",":","*","'interpolation","'",":","Applies","mid-point","summation","scheme","for","`","ROC","`","curve",".","For","`","PR","`","curve",",","interpolates","(","true\/false",")","positives","but","not","the","ratio","that","is","precision","(","see","Davis","&","Goadrich","2006","for","details",")",".","*","'minoring","'",":","Applies","left","summation","for","increasing","intervals","and","right","summation","for","decreasing","intervals",".","*","'majoring","'",":","Applies","right","summation","for","increasing","intervals","and","left","summation","for","decreasing","intervals","."]
code: def from_str(key):
      if key in ("interpolation", "Interpolation"):
          return AUCSummationMethod.INTERPOLATION
      elif key in ("majoring", "Majoring"):
          return AUCSummationMethod.MAJORING
      elif key in ("minoring", "Minoring"):
          return AUCSummationMethod.MINORING
      else:
          raise ValueError(
              'Invalid AUC summation method value "%s".' % key
          )
  
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 1 for calling the AUCSummationMethod obj's underlying member method code with example usage: obj.from_str(key) and returns: AUCSummationMethod, AUCSummationMethod, AUCSummationMethod