
"""simple docstring"""



from typing import List

import jiwer
import jiwer.transforms as tr
from packaging import version

import datasets
from datasets.config import PY_VERSION


if PY_VERSION < version.parse('3.8'):
    import importlib_metadata
else:
    import importlib.metadata as importlib_metadata


UpperCamelCase__          =	''


if version.parse(importlib_metadata.version('jiwer')) < version.parse('2.3.0'):





    class 				a			(					tr.AbstractTransform      ):



          def __init__(   self     ,	UpperCamelCase_ = " "      ):
              UpperCAmelCase__	:      Union[str, Any]     							=					sentence_delimiter



          def  __snake_case							(   self     ,	UpperCamelCase_      ):
              return list(UpperCamelCase_      )



          def  __snake_case							(   self     ,	UpperCamelCase_      ):
              UpperCAmelCase__	:      Tuple     							=					[]
              for sent_idx, sentence in enumerate(UpperCamelCase_      ):
                  chars.extend(self.process_string(UpperCamelCase_      )      )
                  if self.sentence_delimiter is not None and self.sentence_delimiter != "" and sent_idx < len(UpperCamelCase_      ) - 1:
                      chars.append(self.sentence_delimiter      )
              return chars




    UpperCamelCase__          =	tr.Compose(
        [tr.RemoveMultipleSpaces(), tr.Strip(), SentencesToListOfCharacters(SENTENCE_DELIMITER)]
    )
else:
    UpperCamelCase__          =	tr.Compose(
        [
            tr.RemoveMultipleSpaces(),
            tr.Strip(),
            tr.ReduceToSingleSentence(SENTENCE_DELIMITER),
            tr.ReduceToListOfListOfChars(),
        ]
    )


UpperCamelCase__          =	'\\n@inproceedings{inproceedings,\n    author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n    year = {2004},\n    month = {01},\n    pages = {},\n    title = {From WER and RIL to MER and WIL: improved evaluation measures for connected speech recognition.}\n}\n'

UpperCamelCase__          =	'\\nCharacter error rate (CER) is a common metric of the performance of an automatic speech recognition system.\n\nCER is similar to Word Error Rate (WER), but operates on character instead of word. Please refer to docs of WER for further information.\n\nCharacter error rate can be computed as:\n\nCER = (S + D + I) / N = (S + D + I) / (S + D + C)\n\nwhere\n\nS is the number of substitutions,\nD is the number of deletions,\nI is the number of insertions,\nC is the number of correct characters,\nN is the number of characters in the reference (N=S+D+C).\n\nCER\'s output is not always a number between 0 and 1, in particular when there is a high number of insertions. This value is often associated to the percentage of characters that were incorrectly predicted. The lower the value, the better the\nperformance of the ASR system with a CER of 0 being a perfect score.\n'

UpperCamelCase__          =	'\nComputes CER score of transcribed segments against references.\nArgs:\n    references: list of references for each speech input.\n    predictions: list of transcribtions to score.\n    concatenate_texts: Whether or not to concatenate sentences before evaluation, set to True for more accurate result.\nReturns:\n    (float): the character error rate\n\nExamples:\n\n    >>> predictions = ["this is the prediction", "there is an other sample"]\n    >>> references = ["this is the reference", "there is another one"]\n    >>> cer = datasets.load_metric("cer")\n    >>> cer_score = cer.compute(predictions=predictions, references=references)\n    >>> print(cer_score)\n    0.34146341463414637\n'





@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION						,		_KWARGS_DESCRIPTION      )
class 				a			(					datasets.Metric      ):



      def  __snake_case							(   self      ):
          return datasets.MetricInfo(
              description=_DESCRIPTION     ,	citation=_CITATION     ,	inputs_description=_KWARGS_DESCRIPTION     ,	features=datasets.Features(
                  {
                      'predictions': datasets.Value('string'     ,	id='sequence'      ),
                      'references': datasets.Value('string'     ,	id='sequence'      ),
                  }      )     ,	codebase_urls=['https://github.com/jitsi/jiwer/']     ,	reference_urls=[
                  'https://en.wikipedia.org/wiki/Word_error_rate',
                  'https://sites.google.com/site/textdigitisation/qualitymeasures/computingerrorrates',
              ]     ,	)



      def  __snake_case							(   self     ,	UpperCamelCase_     ,	UpperCamelCase_     ,	UpperCamelCase_=False      ):
          if concatenate_texts:
              return jiwer.compute_measures(
                  UpperCamelCase_     ,	UpperCamelCase_     ,	truth_transform=UpperCamelCase_     ,	hypothesis_transform=UpperCamelCase_     ,	)["wer"]

          UpperCAmelCase__	:      Union[str, Any]     							=					0
          UpperCAmelCase__	:      Tuple     							=					0
          for prediction, reference in zip(UpperCamelCase_     ,	UpperCamelCase_      ):
              UpperCAmelCase__	:      Union[str, Any]     							=					jiwer.compute_measures(
                  UpperCamelCase_     ,	UpperCamelCase_     ,	truth_transform=UpperCamelCase_     ,	hypothesis_transform=UpperCamelCase_     ,	)
              incorrect += measures["substitutions"] + measures["deletions"] + measures["insertions"]
              total += measures["substitutions"] + measures["deletions"] + measures["hits"]

          return incorrect / total



"""simple docstring"""



import random
def 					lowerCamelCase   (     _snake_case ):
    UpperCAmelCase__	:      Tuple     							=					num - 1
    UpperCAmelCase__	:      Dict     							=					0

    while s % 2 == 0:
        UpperCAmelCase__	:      Optional[int]     							=					s // 2
        t += 1

    for _ in range(5 ):
        UpperCAmelCase__	:      Optional[int]     							=					random.randrange(2    ,num - 1 )
        UpperCAmelCase__	:      List[str]     							=					pow(_snake_case    ,_snake_case    ,_snake_case )
        if v != 1:
            UpperCAmelCase__	:      List[Any]     							=					0
            while v != (num - 1):
                if i == t - 1:
                    return False
                else:
                    UpperCAmelCase__	:      Optional[Any]     							=					i + 1
                    UpperCAmelCase__	:      Any     							=					(v**2) % num
    return True
def 					lowerCamelCase   (     _snake_case ):
    if num < 2:
        return False

    UpperCAmelCase__	:      str     							=					[
        2,
        3,
        5,
        7,
        11,
        13,
        17,
        19,
        23,
        29,
        31,
        37,
        41,
        43,
        47,
        53,
        59,
        61,
        67,
        71,
        73,
        79,
        83,
        89,
        97,
        101,
        103,
        107,
        109,
        113,
        127,
        131,
        137,
        139,
        149,
        151,
        157,
        163,
        167,
        173,
        179,
        181,
        191,
        193,
        197,
        199,
        211,
        223,
        227,
        229,
        233,
        239,
        241,
        251,
        257,
        263,
        269,
        271,
        277,
        281,
        283,
        293,
        307,
        311,
        313,
        317,
        331,
        337,
        347,
        349,
        353,
        359,
        367,
        373,
        379,
        383,
        389,
        397,
        401,
        409,
        419,
        421,
        431,
        433,
        439,
        443,
        449,
        457,
        461,
        463,
        467,
        479,
        487,
        491,
        499,
        503,
        509,
        521,
        523,
        541,
        547,
        557,
        563,
        569,
        571,
        577,
        587,
        593,
        599,
        601,
        607,
        613,
        617,
        619,
        631,
        641,
        643,
        647,
        653,
        659,
        661,
        673,
        677,
        683,
        691,
        701,
        709,
        719,
        727,
        733,
        739,
        743,
        751,
        757,
        761,
        769,
        773,
        787,
        797,
        809,
        811,
        821,
        823,
        827,
        829,
        839,
        853,
        857,
        859,
        863,
        877,
        881,
        883,
        887,
        907,
        911,
        919,
        929,
        937,
        941,
        947,
        953,
        967,
        971,
        977,
        983,
        991,
        997,
    ]

    if num in low_primes:
        return True

    for prime in low_primes:
        if (num % prime) == 0:
            return False

    return rabin_miller(_snake_case )
def 					lowerCamelCase   (     _snake_case = 1024 ):
    while True:
        UpperCAmelCase__	:      List[Any]     							=					random.randrange(2 ** (keysize - 1)    ,2 ** (keysize) )
        if is_prime_low_num(_snake_case ):
            return num


if __name__ == "__main__":
    UpperCamelCase__          =	generate_large_prime()
    print(('Prime number:', num))
    print(('is_prime_low_num:', is_prime_low_num(num)))

