

"""simple docstring"""






from jiwer import compute_measures

import datasets


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

_lowerCAmelCase						=		"""\
Word error rate (WER) is a common metric of the performance of an automatic speech recognition system.

The general difficulty of measuring performance lies in the fact that the recognized word sequence can have a different length from the reference word sequence (supposedly the correct one). The WER is derived from the Levenshtein distance, working at the word level instead of the phoneme level. The WER is a valuable tool for comparing different systems as well as for evaluating improvements within one system. This kind of measurement, however, provides no details on the nature of translation errors and further work is therefore required to identify the main source(s) of error and to focus any research effort.

This problem is solved by first aligning the recognized word sequence with the reference (spoken) word sequence using dynamic string alignment. Examination of this issue is seen through a theory called the power law that states the correlation between perplexity and word error rate.

Word error rate can then be computed as:

WER = (S + D + I) / N = (S + D + I) / (S + D + C)

where

S is the number of substitutions,
D is the number of deletions,
I is the number of insertions,
C is the number of correct words,
N is the number of words in the reference (N=S+D+C).

This value indicates the average number of errors per reference word. The lower the value, the better the
performance of the ASR system with a WER of 0 being a perfect score.
"""

_lowerCAmelCase						=		"""
Compute WER score of transcribed segments against references.

Args:
    references: List of references for each speech input.
    predictions: List of transcriptions to score.
    concatenate_texts (bool, default=False): Whether to concatenate all input texts or compute WER iteratively.

Returns:
    (float): the word error rate

Examples:

    >>> predictions = [\"this is the prediction\", \"there is an other sample\"]
    >>> references = [\"this is the reference\", \"there is another one\"]
    >>> wer = datasets.load_metric(\"wer\")
    >>> wer_score = wer.compute(predictions=predictions, references=references)
    >>> print(wer_score)
    0.5
"""







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

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      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',
          ]    ,)







  def __lowerCamelCase		(		self    ,_A=None    ,_A=None    ,_A=False      ):
      '''simple docstring'''

      if concatenate_texts:
          return compute_measures(_A    ,_A      )["wer"]
      else:
          _lowerCAmelCase       :   List[str]  =    0
          _lowerCAmelCase       :   Any  =    0
          for prediction, reference in zip(_A    ,_A      ):
              _lowerCAmelCase       :   List[str]  =    compute_measures(_A    ,_A      )
              incorrect += measures["substitutions"] + measures["deletions"] + measures["insertions"]
              total += measures["substitutions"] + measures["deletions"] + measures["hits"]
          return incorrect / total








"""simple docstring"""






import argparse
import struct
import unittest







class 	__UpperCamelCase    :

  def __init__(		self    ,_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   Optional[int]  =    data

      # Initialize hash values
      _lowerCAmelCase       :   Any  =    [
          0x6A09_E667,
          0xBB67_AE85,
          0x3C6E_F372,
          0xA54F_F53A,
          0x510E_527F,
          0x9B05_688C,
          0x1F83_D9AB,
          0x5BE0_CD19,
      ]

      # Initialize round constants
      _lowerCAmelCase       :   str  =    [
          0x428A_2F98,
          0x7137_4491,
          0xB5C0_FBCF,
          0xE9B5_DBA5,
          0x3956_C25B,
          0x59F1_11F1,
          0x923F_82A4,
          0xAB1C_5ED5,
          0xD807_AA98,
          0x1283_5B01,
          0x2431_85BE,
          0x550C_7DC3,
          0x72BE_5D74,
          0x80DE_B1FE,
          0x9BDC_06A7,
          0xC19B_F174,
          0xE49B_69C1,
          0xEFBE_4786,
          0x0FC1_9DC6,
          0x240C_A1CC,
          0x2DE9_2C6F,
          0x4A74_84AA,
          0x5CB0_A9DC,
          0x76F9_88DA,
          0x983E_5152,
          0xA831_C66D,
          0xB003_27C8,
          0xBF59_7FC7,
          0xC6E0_0BF3,
          0xD5A7_9147,
          0x06CA_6351,
          0x1429_2967,
          0x27B7_0A85,
          0x2E1B_2138,
          0x4D2C_6DFC,
          0x5338_0D13,
          0x650A_7354,
          0x766A_0ABB,
          0x81C2_C92E,
          0x9272_2C85,
          0xA2BF_E8A1,
          0xA81A_664B,
          0xC24B_8B70,
          0xC76C_51A3,
          0xD192_E819,
          0xD699_0624,
          0xF40E_3585,
          0x106A_A070,
          0x19A4_C116,
          0x1E37_6C08,
          0x2748_774C,
          0x34B0_BCB5,
          0x391C_0CB3,
          0x4ED8_AA4A,
          0x5B9C_CA4F,
          0x682E_6FF3,
          0x748F_82EE,
          0x78A5_636F,
          0x84C8_7814,
          0x8CC7_0208,
          0x90BE_FFFA,
          0xA450_6CEB,
          0xBEF9_A3F7,
          0xC671_78F2,
      ]

      _lowerCAmelCase       :   Any  =    self.preprocessing(self.data      )
      self.final_hash()

  @staticmethod
  def __lowerCamelCase		(		_A      ):
      '''simple docstring'''

      _lowerCAmelCase       :   int  =    b'\x80' + (b'\x00' * (63 - (len(_A      ) + 8) % 64))
      _lowerCAmelCase       :   Any  =    struct.pack('>Q'    ,(len(_A      ) * 8)      )
      return data + padding + big_endian_integer

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      _lowerCAmelCase       :   List[Any]  =    [
          self.preprocessed_data[x : x + 64]
          for x in range(0    ,len(self.preprocessed_data      )    ,64      )
      ]

      for block in self.blocks:
          # Convert the given block into a list of 4 byte integers
          _lowerCAmelCase       :   int  =    list(struct.unpack('>16L'    ,_A      )      )
          # add 48 0-ed integers
          words += [0] * 48

          _lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase       :   Tuple  =    self.hashes

          for index in range(0    ,64      ):
              if index > 15:
                  # modify the zero-ed indexes at the end of the array
                  _lowerCAmelCase       :   List[str]  =    (
                      self.ror(words[index - 15]    ,7      )
                      ^ self.ror(words[index - 15]    ,18      )
                      ^ (words[index - 15] >> 3)
                  )
                  _lowerCAmelCase       :   Tuple  =    (
                      self.ror(words[index - 2]    ,17      )
                      ^ self.ror(words[index - 2]    ,19      )
                      ^ (words[index - 2] >> 10)
                  )

                  _lowerCAmelCase       :   str  =    (
                      words[index - 16] + sa + words[index - 7] + sa
                  ) % 0x1_0000_0000

              # Compression
              _lowerCAmelCase       :   Optional[Any]  =    self.ror(_A    ,6      ) ^ self.ror(_A    ,11      ) ^ self.ror(_A    ,25      )
              _lowerCAmelCase       :   int  =    (e & f) ^ ((~e & 0xFFFF_FFFF) & g)
              _lowerCAmelCase       :   int  =    (
                  h + sa + ch + self.round_constants[index] + words[index]
              ) % 0x1_0000_0000
              _lowerCAmelCase       :   Union[str, Any]  =    self.ror(_A    ,2      ) ^ self.ror(_A    ,13      ) ^ self.ror(_A    ,22      )
              _lowerCAmelCase       :   Any  =    (a & b) ^ (a & c) ^ (b & c)
              _lowerCAmelCase       :   Any  =    (sa + maj) % 0x1_0000_0000

              _lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase,					_lowerCAmelCase       :   Tuple  =    (
                  g,
                  f,
                  e,
                  ((d + tempa) % 0x1_0000_0000),
                  c,
                  b,
                  a,
                  ((tempa + tempa) % 0x1_0000_0000),
              )

          _lowerCAmelCase       :   Any  =    [a, b, c, d, e, f, g, h]

          # Modify final values
          _lowerCAmelCase       :   int  =    [
              ((element + mutated_hash_values[index]) % 0x1_0000_0000)
              for index, element in enumerate(self.hashes      )
          ]

      _lowerCAmelCase       :   List[str]  =    ''.join([hex(_A      )[2:].zfill(8      ) for value in self.hashes]      )







  def __lowerCamelCase		(		self    ,_A    ,_A      ):
      '''simple docstring'''

      return 0xFFFF_FFFF & (value << (32 - rotations)) | (value >> rotations)







class 	__UpperCamelCase    (    unittest.TestCase						):

  def __lowerCamelCase		(		self      ):
      '''simple docstring'''

      import hashlib

      _lowerCAmelCase       :   Any  =    bytes('Test String'    ,'utf-8'      )
      self.assertEqual(SHAaaa(_A      ).hash    ,hashlib.shaaaa(_A      ).hexdigest()      )





def 		lowerCamelCase__		(					):

    '''simple docstring'''



    import doctest

    doctest.testmod()

    _lowerCAmelCase       :   Optional[Any]  =    argparse.ArgumentParser()
    parser.add_argument(
        '-s' ,   '--string' ,   dest='input_string' ,   default='Hello World!! Welcome to Cryptography' ,   help='Hash the string' ,   )
    parser.add_argument(
        '-f' ,   '--file' ,   dest='input_file' ,   help='Hash contents of a file'   )

    _lowerCAmelCase       :   Tuple  =    parser.parse_args()

    _lowerCAmelCase       :   List[str]  =    args.input_string

    # hash input should be a bytestring
    if args.input_file:
        with open(args.input_file ,   'rb'   ) as f:
            _lowerCAmelCase       :   int  =    f.read()
    else:
        _lowerCAmelCase       :   int  =    bytes(_lowerCamelCase ,   'utf-8'   )

    print(SHAaaa(_lowerCamelCase   ).hash   )


if __name__ == "__main__":
 main()





