





'''simple docstring'''

import argparse
import struct
import unittest
class     __lowerCAmelCase					:






       """simple docstring"""





       def __init__(							self       :		Optional[int]	,			lowerCAmelCase__       :		bytes					)   ->					None:

            '''simple docstring'''




            _UpperCamelCase       =	data

            # Initialize hash values
            _UpperCamelCase       =	[
                0X6a_09_e6_67,
                0Xbb_67_ae_85,
                0X3c_6e_f3_72,
                0Xa5_4f_f5_3a,
                0X51_0e_52_7f,
                0X9b_05_68_8c,
                0X1f_83_d9_ab,
                0X5b_e0_cd_19,
            ]

            # Initialize round constants
            _UpperCamelCase       =	[
                0X42_8a_2f_98,
                0X71_37_44_91,
                0Xb5_c0_fb_cf,
                0Xe9_b5_db_a5,
                0X39_56_c2_5b,
                0X59_f1_11_f1,
                0X92_3f_82_a4,
                0Xab_1c_5e_d5,
                0Xd8_07_aa_98,
                0X12_83_5b_01,
                0X24_31_85_be,
                0X55_0c_7d_c3,
                0X72_be_5d_74,
                0X80_de_b1_fe,
                0X9b_dc_06_a7,
                0Xc1_9b_f1_74,
                0Xe4_9b_69_c1,
                0Xef_be_47_86,
                0X0f_c1_9d_c6,
                0X24_0c_a1_cc,
                0X2d_e9_2c_6f,
                0X4a_74_84_aa,
                0X5c_b0_a9_dc,
                0X76_f9_88_da,
                0X98_3e_51_52,
                0Xa8_31_c6_6d,
                0Xb0_03_27_c8,
                0Xbf_59_7f_c7,
                0Xc6_e0_0b_f3,
                0Xd5_a7_91_47,
                0X06_ca_63_51,
                0X14_29_29_67,
                0X27_b7_0a_85,
                0X2e_1b_21_38,
                0X4d_2c_6d_fc,
                0X53_38_0d_13,
                0X65_0a_73_54,
                0X76_6a_0a_bb,
                0X81_c2_c9_2e,
                0X92_72_2c_85,
                0Xa2_bf_e8_a1,
                0Xa8_1a_66_4b,
                0Xc2_4b_8b_70,
                0Xc7_6c_51_a3,
                0Xd1_92_e8_19,
                0Xd6_99_06_24,
                0Xf4_0e_35_85,
                0X10_6a_a0_70,
                0X19_a4_c1_16,
                0X1e_37_6c_08,
                0X27_48_77_4c,
                0X34_b0_bc_b5,
                0X39_1c_0c_b3,
                0X4e_d8_aa_4a,
                0X5b_9c_ca_4f,
                0X68_2e_6f_f3,
                0X74_8f_82_ee,
                0X78_a5_63_6f,
                0X84_c8_78_14,
                0X8c_c7_02_08,
                0X90_be_ff_fa,
                0Xa4_50_6c_eb,
                0Xbe_f9_a3_f7,
                0Xc6_71_78_f2,
            ]

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





       @staticmethod
       def snake_case__						(							lowerCAmelCase__       :		bytes					)   ->					bytes:

            '''simple docstring'''




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





       def snake_case__						(							self       :		List[Any]					)   ->					None:

            '''simple docstring'''




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

                 _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase       =	self.hashes

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

                           _UpperCamelCase       =	(
                               words[index - 16] + sa + words[index - 7] + sa
                           ) % 0X1_00_00_00_00

                      # Compression
                      _UpperCamelCase       =	self.ror(lowerCAmelCase__	,			6					) ^ self.ror(lowerCAmelCase__	,			11					) ^ self.ror(lowerCAmelCase__	,			25					)
                      _UpperCamelCase       =	(e & f) ^ ((~e & 0Xff_ff_ff_ff) & g)
                      _UpperCamelCase       =	(
                          h + sa + ch + self.round_constants[index] + words[index]
                      ) % 0X1_00_00_00_00
                      _UpperCamelCase       =	self.ror(lowerCAmelCase__	,			2					) ^ self.ror(lowerCAmelCase__	,			13					) ^ self.ror(lowerCAmelCase__	,			22					)
                      _UpperCamelCase       =	(a & b) ^ (a & c) ^ (b & c)
                      _UpperCamelCase       =	(sa + maj) % 0X1_00_00_00_00

                      _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase       =	(
                          g,
                          f,
                          e,
                          ((d + tempa) % 0X1_00_00_00_00),
                          c,
                          b,
                          a,
                          ((tempa + tempa) % 0X1_00_00_00_00),
                      )

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

                 # Modify final values
                 _UpperCamelCase       =	[
                     ((element + mutated_hash_values[index]) % 0X1_00_00_00_00)
                     for index, element in enumerate(self.hashes					)
                 ]

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







       def snake_case__						(							self       :		int	,			lowerCAmelCase__       :		int	,			lowerCAmelCase__       :		int					)   ->					int:

            '''simple docstring'''




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

class     __lowerCAmelCase					(   unittest.TestCase			):






       """simple docstring"""





       def snake_case__						(							self       :		str					)   ->					None:

            '''simple docstring'''




            import hashlib

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







def  a__    (    )		->		None:





     """simple docstring"""

     import doctest

     doctest.testmod()

     _UpperCamelCase       =	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'''				)

     _UpperCamelCase       =	parser.parse_args()

     _UpperCamelCase       =	args.input_string

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

     print(SHAaaa(lowercase				).hash				)


if __name__ == "__main__":
      main()










'''simple docstring'''

import unittest

import numpy as np

from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask


if is_flax_available():
   from transformers.models.roberta.modeling_flax_roberta import (
       FlaxRobertaForCausalLM,
       FlaxRobertaForMaskedLM,
       FlaxRobertaForMultipleChoice,
       FlaxRobertaForQuestionAnswering,
       FlaxRobertaForSequenceClassification,
       FlaxRobertaForTokenClassification,
       FlaxRobertaModel,
   )
class     __lowerCAmelCase					(   unittest.TestCase			):






       """simple docstring"""





       def __init__(							self       :		Tuple	,			lowerCAmelCase__       :		Tuple	,			lowerCAmelCase__       :		Union[str, Any]=13	,			lowerCAmelCase__       :		Union[str, Any]=7	,			lowerCAmelCase__       :		str=True	,			lowerCAmelCase__       :		Tuple=True	,			lowerCAmelCase__       :		Dict=True	,			lowerCAmelCase__       :		Dict=True	,			lowerCAmelCase__       :		int=99	,			lowerCAmelCase__       :		str=32	,			lowerCAmelCase__       :		str=5	,			lowerCAmelCase__       :		str=4	,			lowerCAmelCase__       :		str=37	,			lowerCAmelCase__       :		int="gelu"	,			lowerCAmelCase__       :		Optional[Any]=0.1	,			lowerCAmelCase__       :		int=0.1	,			lowerCAmelCase__       :		Optional[int]=512	,			lowerCAmelCase__       :		Dict=16	,			lowerCAmelCase__       :		List[Any]=2	,			lowerCAmelCase__       :		Any=0.02	,			lowerCAmelCase__       :		Union[str, Any]=4	,			)   ->					Dict:

            '''simple docstring'''




            _UpperCamelCase       =	parent
            _UpperCamelCase       =	batch_size
            _UpperCamelCase       =	seq_length
            _UpperCamelCase       =	is_training
            _UpperCamelCase       =	use_attention_mask
            _UpperCamelCase       =	use_token_type_ids
            _UpperCamelCase       =	use_labels
            _UpperCamelCase       =	vocab_size
            _UpperCamelCase       =	hidden_size
            _UpperCamelCase       =	num_hidden_layers
            _UpperCamelCase       =	num_attention_heads
            _UpperCamelCase       =	intermediate_size
            _UpperCamelCase       =	hidden_act
            _UpperCamelCase       =	hidden_dropout_prob
            _UpperCamelCase       =	attention_probs_dropout_prob
            _UpperCamelCase       =	max_position_embeddings
            _UpperCamelCase       =	type_vocab_size
            _UpperCamelCase       =	type_sequence_label_size
            _UpperCamelCase       =	initializer_range
            _UpperCamelCase       =	num_choices





       def snake_case__						(							self       :		Optional[int]					)   ->					Optional[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	ids_tensor([self.batch_size, self.seq_length]	,			self.vocab_size					)

            _UpperCamelCase       =	None
            if self.use_attention_mask:
                 _UpperCamelCase       =	random_attention_mask([self.batch_size, self.seq_length]					)

            _UpperCamelCase       =	None
            if self.use_token_type_ids:
                 _UpperCamelCase       =	ids_tensor([self.batch_size, self.seq_length]	,			self.type_vocab_size					)

            _UpperCamelCase       =	RobertaConfig(
                vocab_size=self.vocab_size	,			hidden_size=self.hidden_size	,			num_hidden_layers=self.num_hidden_layers	,			num_attention_heads=self.num_attention_heads	,			intermediate_size=self.intermediate_size	,			hidden_act=self.hidden_act	,			hidden_dropout_prob=self.hidden_dropout_prob	,			attention_probs_dropout_prob=self.attention_probs_dropout_prob	,			max_position_embeddings=self.max_position_embeddings	,			type_vocab_size=self.type_vocab_size	,			is_decoder=lowerCAmelCase__	,			initializer_range=self.initializer_range	,			)

            return config, input_ids, token_type_ids, attention_mask





       def snake_case__						(							self       :		Optional[int]					)   ->					Any:

            '''simple docstring'''




            _UpperCamelCase       =	self.prepare_config_and_inputs()
            _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase       =	config_and_inputs
            _UpperCamelCase       =	{'''input_ids''': input_ids, '''token_type_ids''': token_type_ids, '''attention_mask''': attention_mask}
            return config, inputs_dict







       def snake_case__						(							self       :		List[str]					)   ->					Any:

            '''simple docstring'''




            _UpperCamelCase       =	self.prepare_config_and_inputs()
            _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase   ,    _UpperCamelCase       =	config_and_inputs

            _UpperCamelCase       =	True
            _UpperCamelCase       =	floats_tensor([self.batch_size, self.seq_length, self.hidden_size]					)
            _UpperCamelCase       =	ids_tensor([self.batch_size, self.seq_length]	,			vocab_size=2					)

            return (
                config,
                input_ids,
                token_type_ids,
                encoder_hidden_states,
                encoder_attention_mask,
            )

@require_flax
class     __lowerCAmelCase					(   __magic_name__						,						unittest.TestCase			):






       """simple docstring"""
       _snake_case     :					Optional[int]						    =   True

       _snake_case     :					Optional[Any]						    =   (
           (
               FlaxRobertaModel,
               FlaxRobertaForCausalLM,
               FlaxRobertaForMaskedLM,
               FlaxRobertaForSequenceClassification,
               FlaxRobertaForTokenClassification,
               FlaxRobertaForMultipleChoice,
               FlaxRobertaForQuestionAnswering,
           )
           if is_flax_available()
           else ()
       )





       def snake_case__						(							self       :		Dict					)   ->					List[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	FlaxRobertaModelTester(self					)







       @slow
       def snake_case__						(							self       :		List[str]					)   ->					Union[str, Any]:

            '''simple docstring'''




            for model_class_name in self.all_model_classes:
                 _UpperCamelCase       =	model_class_name.from_pretrained('''roberta-base'''	,			from_pt=lowerCAmelCase__					)
                 _UpperCamelCase       =	model(np.ones((1, 1)					)					)
                 self.assertIsNotNone(lowerCAmelCase__					)



