



import argparse
import struct
import unittest

class     _A       :



       def __init__(		self							:     Optional[int]     ,		__SCREAMING_SNAKE_CASE							:     bytes):


           '''simple docstring'''

           __a						       =				data

           # Initialize hash values
           __a						       =				[
               0x6A09E667,
               0xBB67AE85,
               0x3C6EF372,
               0xA54FF53A,
               0x510E527F,
               0x9B05688C,
               0x1F83D9AB,
               0x5BE0CD19,
           ]

           # Initialize round constants
           __a						       =				[
               0x428A2F98,
               0x71374491,
               0xB5C0FBCF,
               0xE9B5DBA5,
               0x3956C25B,
               0x59F111F1,
               0x923F82A4,
               0xAB1C5ED5,
               0xD807AA98,
               0x12835B01,
               0x243185BE,
               0x550C7DC3,
               0x72BE5D74,
               0x80DEB1FE,
               0x9BDC06A7,
               0xC19BF174,
               0xE49B69C1,
               0xEFBE4786,
               0x0FC19DC6,
               0x240CA1CC,
               0x2DE92C6F,
               0x4A7484AA,
               0x5CB0A9DC,
               0x76F988DA,
               0x983E5152,
               0xA831C66D,
               0xB00327C8,
               0xBF597FC7,
               0xC6E00BF3,
               0xD5A79147,
               0x06CA6351,
               0x14292967,
               0x27B70A85,
               0x2E1B2138,
               0x4D2C6DFC,
               0x53380D13,
               0x650A7354,
               0x766A0ABB,
               0x81C2C92E,
               0x92722C85,
               0xA2BFE8A1,
               0xA81A664B,
               0xC24B8B70,
               0xC76C51A3,
               0xD192E819,
               0xD6990624,
               0xF40E3585,
               0x106AA070,
               0x19A4C116,
               0x1E376C08,
               0x2748774C,
               0x34B0BCB5,
               0x391C0CB3,
               0x4ED8AA4A,
               0x5B9CCA4F,
               0x682E6FF3,
               0x748F82EE,
               0x78A5636F,
               0x84C87814,
               0x8CC70208,
               0x90BEFFFA,
               0xA4506CEB,
               0xBEF9A3F7,
               0xC67178F2,
           ]

           __a						       =				self.preprocessing(self.data)
           self.final_hash()



       @staticmethod
       def 		_lowerCamelCase			(		__SCREAMING_SNAKE_CASE							:     bytes):


           '''simple docstring'''

           __a						       =				B'''\x80''' + (B'''\x00''' * (63 - (len(__SCREAMING_SNAKE_CASE) + 8) % 64))
           __a						       =				struct.pack('''>Q'''     ,		(len(__SCREAMING_SNAKE_CASE) * 8))
           return data + padding + big_endian_integer



       def 		_lowerCamelCase			(		self							:     str):


           '''simple docstring'''

           __a						       =				[
               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
               __a						       =				list(struct.unpack('''>16L'''     ,		__SCREAMING_SNAKE_CASE))
               # add 48 0-ed integers
               words += [0] * 48

               __a       ,   __a       ,   __a       ,   __a       ,   __a       ,   __a       ,   __a       ,   __a						       =				self.hashes

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

                       __a						       =				(
                           words[index - 16] + sa + words[index - 7] + sa
                       ) % 0x100000000

                   # Compression
                   __a						       =				self.ror(__SCREAMING_SNAKE_CASE     ,		6) ^ self.ror(__SCREAMING_SNAKE_CASE     ,		11) ^ self.ror(__SCREAMING_SNAKE_CASE     ,		25)
                   __a						       =				(e & f) ^ ((~e & 0xFFFFFFFF) & g)
                   __a						       =				(
                       h + sa + ch + self.round_constants[index] + words[index]
                   ) % 0x100000000
                   __a						       =				self.ror(__SCREAMING_SNAKE_CASE     ,		2) ^ self.ror(__SCREAMING_SNAKE_CASE     ,		13) ^ self.ror(__SCREAMING_SNAKE_CASE     ,		22)
                   __a						       =				(a & b) ^ (a & c) ^ (b & c)
                   __a						       =				(sa + maj) % 0x100000000

                   __a       ,   __a       ,   __a       ,   __a       ,   __a       ,   __a       ,   __a       ,   __a						       =				(
                       g,
                       f,
                       e,
                       ((d + tempa) % 0x100000000),
                       c,
                       b,
                       a,
                       ((tempa + tempa) % 0x100000000),
                   )

               __a						       =				[a, b, c, d, e, f, g, h]

               # Modify final values
               __a						       =				[
                   ((element + mutated_hash_values[index]) % 0x100000000)
                   for index, element in enumerate(self.hashes)
               ]

           __a						       =				''''''.join([hex(__SCREAMING_SNAKE_CASE)[2:].zfill(8) for value in self.hashes])





       def 		_lowerCamelCase			(		self							:     int     ,		__SCREAMING_SNAKE_CASE							:     int     ,		__SCREAMING_SNAKE_CASE							:     int):


           '''simple docstring'''

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


class     _A       (	unittest.TestCase    ):



       def 		_lowerCamelCase			(		self							:     Optional[int]):


           '''simple docstring'''

           import hashlib

           __a						       =				bytes('''Test String'''     ,		'''utf-8''')
           self.assertEqual(SHAaaa(__SCREAMING_SNAKE_CASE).hash     ,		hashlib.shaaaa(__SCREAMING_SNAKE_CASE).hexdigest())





def      __snake_case	(			):
    import doctest

    doctest.testmod()

    __a						       =				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'''				)

    __a						       =				parser.parse_args()

    __a						       =				args.input_string

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

    print(SHAaaa(_UpperCAmelCase				).hash				)


if __name__ == "__main__":
 main()










"""simple docstring"""
import datasets

from .evaluate import evaluate


A:   Optional[Any]								=		"\\n@article{hendrycks2021cuad,\n      title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n      author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n      journal={arXiv preprint arXiv:2103.06268},\n      year={2021}\n}\n"

A:   Optional[int]								=		"\nThis metric wrap the official scoring script for version 1 of the Contract\nUnderstanding Atticus Dataset (CUAD).\nContract Understanding Atticus Dataset (CUAD) v1 is a corpus of more than 13,000 labels in 510\ncommercial legal contracts that have been manually labeled to identify 41 categories of important\nclauses that lawyers look for when reviewing contracts in connection with corporate transactions.\n"

A:   int								=		"\nComputes CUAD scores (EM, F1, AUPR, Precision@80%Recall, and Precision@90%Recall).\nArgs:\n    predictions: List of question-answers dictionaries with the following key-values:\n        - 'id': id of the question-answer pair as given in the references (see below)\n        - 'prediction_text': list of possible texts for the answer, as a list of strings\n        depending on a threshold on the confidence probability of each prediction.\n    references: List of question-answers dictionaries with the following key-values:\n        - 'id': id of the question-answer pair (see above),\n        - 'answers': a Dict in the CUAD dataset format\n            {\n                'text': list of possible texts for the answer, as a list of strings\n                'answer_start': list of start positions for the answer, as a list of ints\n            }\n            Note that answer_start values are not taken into account to compute the metric.\nReturns:\n    'exact_match': Exact match (the normalized answer exactly match the gold answer)\n    'f1': The F-score of predicted tokens versus the gold answer\n    'aupr': Area Under the Precision-Recall curve\n    'prec_at_80_recall': Precision at 80% recall\n    'prec_at_90_recall': Precision at 90% recall\nExamples:\n    >>> predictions = [{'prediction_text': ['The seller:', 'The buyer/End-User: Shenzhen LOHAS Supply Chain Management Co., Ltd.'], 'id': 'LohaCompanyltd_20191209_F-1_EX-10.16_11917878_EX-10.16_Supply Agreement__Parties'}]\n    >>> references = [{'answers': {'answer_start': [143, 49], 'text': ['The seller:', 'The buyer/End-User: Shenzhen LOHAS Supply Chain Management Co., Ltd.']}, 'id': 'LohaCompanyltd_20191209_F-1_EX-10.16_11917878_EX-10.16_Supply Agreement__Parties'}]\n    >>> cuad_metric = datasets.load_metric(\"cuad\")\n    >>> results = cuad_metric.compute(predictions=predictions, references=references)\n    >>> print(results)\n    {'exact_match': 100.0, 'f1': 100.0, 'aupr': 0.0, 'prec_at_80_recall': 1.0, 'prec_at_90_recall': 1.0}\n"



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

   def 	SCREAMING_SNAKE_CASE     (   self						)  ->      Optional[Any]:





    '''simple docstring'''




    return datasets.MetricInfo(
        description=_DESCRIPTION      ,     citation=_CITATION      ,     inputs_description=_KWARGS_DESCRIPTION      ,     features=datasets.Features(
            {
                """predictions""": {
                    """id""": datasets.Value("""string"""						),
                    """prediction_text""": datasets.features.Sequence(datasets.Value("""string"""						)						),
                },
                """references""": {
                    """id""": datasets.Value("""string"""						),
                    """answers""": datasets.features.Sequence(
                        {
                            """text""": datasets.Value("""string"""						),
                            """answer_start""": datasets.Value("""int32"""						),
                        }						),
                },
            }						)      ,     codebase_urls=["""https://www.atticusprojectai.org/cuad"""]      ,     reference_urls=["""https://www.atticusprojectai.org/cuad"""]      ,     )




   def 	SCREAMING_SNAKE_CASE     (   self      ,     _SCREAMING_SNAKE_CASE      ,     _SCREAMING_SNAKE_CASE						)  ->      Dict:





    '''simple docstring'''




    UpperCAmelCase	:					int	=	{prediction["""id"""]: prediction["""prediction_text"""] for prediction in predictions}
    UpperCAmelCase	:					Tuple	=	[
        {
            """paragraphs""": [
                {
                    """qas""": [
                        {
                            """answers""": [{"""text""": answer_text} for answer_text in ref["""answers"""]["""text"""]],
                            """id""": ref["""id"""],
                        }
                        for ref in references
                    ]
                }
            ]
        }
    ]
    UpperCAmelCase	:					Optional[Any]	=	evaluate(dataset=_SCREAMING_SNAKE_CASE      ,     predictions=_SCREAMING_SNAKE_CASE						)
    return score
