
import argparse
import struct
import unittest







class      A__							:






				def __init__(						self					:      Optional[Any]    ,     a					:      bytes   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Optional[Any]         =		data

							# Initialize hash values
							lowerCAmelCase__      :      Optional[int]         =		[
							    0X6a_09e_667,
							    0Xbb_67a_e85,
							    0X3c_6ef_372,
							    0Xa5_4ff_53a,
							    0X51_0e5_27f,
							    0X9b_056_88c,
							    0X1f_83d_9ab,
							    0X5b_e0c_d19,
							]

							# Initialize round constants
							lowerCAmelCase__      :      Union[str, Any]         =		[
							    0X42_8a2_f98,
							    0X71_374_491,
							    0Xb5_c0f_bcf,
							    0Xe9_b5d_ba5,
							    0X39_56c_25b,
							    0X59_f11_1f1,
							    0X92_3f8_2a4,
							    0Xab_1c5_ed5,
							    0Xd8_07a_a98,
							    0X12_835_b01,
							    0X24_318_5be,
							    0X55_0c7_dc3,
							    0X72_be5_d74,
							    0X80_deb_1fe,
							    0X9b_dc0_6a7,
							    0Xc1_9bf_174,
							    0Xe4_9b6_9c1,
							    0Xef_be4_786,
							    0X0f_c19_dc6,
							    0X24_0ca_1cc,
							    0X2d_e92_c6f,
							    0X4a_748_4aa,
							    0X5c_b0a_9dc,
							    0X76_f98_8da,
							    0X98_3e5_152,
							    0Xa8_31c_66d,
							    0Xb0_032_7c8,
							    0Xbf_597_fc7,
							    0Xc6_e00_bf3,
							    0Xd5_a79_147,
							    0X06_ca6_351,
							    0X14_292_967,
							    0X27_b70_a85,
							    0X2e_1b2_138,
							    0X4d_2c6_dfc,
							    0X53_380_d13,
							    0X65_0a7_354,
							    0X76_6a0_abb,
							    0X81_c2c_92e,
							    0X92_722_c85,
							    0Xa2_bfe_8a1,
							    0Xa8_1a6_64b,
							    0Xc2_4b8_b70,
							    0Xc7_6c5_1a3,
							    0Xd1_92e_819,
							    0Xd6_990_624,
							    0Xf4_0e3_585,
							    0X10_6aa_070,
							    0X19_a4c_116,
							    0X1e_376_c08,
							    0X27_487_74c,
							    0X34_b0b_cb5,
							    0X39_1c0_cb3,
							    0X4e_d8a_a4a,
							    0X5b_9cc_a4f,
							    0X68_2e6_ff3,
							    0X74_8f8_2ee,
							    0X78_a56_36f,
							    0X84_c87_814,
							    0X8c_c70_208,
							    0X90_bef_ffa,
							    0Xa4_506_ceb,
							    0Xbe_f9a_3f7,
							    0Xc6_717_8f2,
							]

							lowerCAmelCase__      :      Optional[int]         =		self.preprocessing(self.data   )
							self.final_hash()






				@staticmethod
				def 							_lowerCamelCase		(						a					:      bytes   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Optional[int]         =		b'\x80' + (b'\x00' * (63 - (len(a   ) + 8) % 64))
							lowerCAmelCase__      :      Dict         =		struct.pack('>Q'    ,     (len(a   ) * 8)   )
							return data + padding + big_endian_integer






				def 							_lowerCamelCase		(						self					:      List[Any]   ):






							'''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__      :      Dict         =		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__      :      str         =		(
																    self.ror(words[index - 15]    ,     7   )
																    ^ self.ror(words[index - 15]    ,     18   )
																    ^ (words[index - 15] >> 3)
																)
																lowerCAmelCase__      :      Union[str, Any]         =		(
																    self.ror(words[index - 2]    ,     17   )
																    ^ self.ror(words[index - 2]    ,     19   )
																    ^ (words[index - 2] >> 10)
																)

																lowerCAmelCase__      :      int         =		(
																    words[index - 16] + sa + words[index - 7] + sa
																) % 0X100_000_000

													# Compression
													lowerCAmelCase__      :      Tuple         =		self.ror(a    ,     6   ) ^ self.ror(a    ,     11   ) ^ self.ror(a    ,     25   )
													lowerCAmelCase__      :      List[Any]         =		(e & f) ^ ((~e & 0Xff_fff_fff) & g)
													lowerCAmelCase__      :      str         =		(
													    h + sa + ch + self.round_constants[index] + words[index]
													) % 0X100_000_000
													lowerCAmelCase__      :      List[str]         =		self.ror(a    ,     2   ) ^ self.ror(a    ,     13   ) ^ self.ror(a    ,     22   )
													lowerCAmelCase__      :      List[Any]         =		(a & b) ^ (a & c) ^ (b & c)
													lowerCAmelCase__      :      int         =		(sa + maj) % 0X100_000_000

													lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      ,				lowerCAmelCase__      :      Union[str, Any]         =		(
													    g,
													    f,
													    e,
													    ((d + tempa) % 0X100_000_000),
													    c,
													    b,
													    a,
													    ((tempa + tempa) % 0X100_000_000),
													)

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

										# Modify final values
										lowerCAmelCase__      :      str         =		[
										    ((element + mutated_hash_values[index]) % 0X100_000_000)
										    for index, element in enumerate(self.hashes   )
										]

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






				def 							_lowerCamelCase		(						self					:      Optional[Any]    ,     a					:      int    ,     a					:      int   ):






							'''simple docstring'''







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







class      A__							(     unittest.TestCase	):






				def 							_lowerCamelCase		(						self					:      Optional[Any]   ):






							'''simple docstring'''







							import hashlib

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






def  lowerCAmelCase__			(  )				->		None:
			import doctest

			doctest.testmod()

			lowerCAmelCase__      :      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__      :      Any         =		parser.parse_args()

			lowerCAmelCase__      :      int         =		args.input_string

			# hash input should be a bytestring
			if args.input_file:
						with open(args.input_file       ,							'rb'     ) as f:
									lowerCAmelCase__      :      Optional[Any]         =		f.read()
			else:
						lowerCAmelCase__      :      Optional[int]         =		bytes(SCREAMING_SNAKE_CASE_       ,							'utf-8'     )

			print(SHAaaa(SCREAMING_SNAKE_CASE_     ).hash     )


if __name__ == "__main__":
					main()

import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
					from transformers.models.rag.configuration_rag import RagConfig
					from transformers.models.rag.tokenization_rag import RagTokenizer







@require_faiss
@require_torch
class      A__							(     __magic_name__	):






				def 							_lowerCamelCase		(						self					:      Tuple   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Optional[Any]         =		tempfile.mkdtemp()
							lowerCAmelCase__      :      Dict         =		8

							# DPR tok
							lowerCAmelCase__      :      str         =		[
							    '[UNK]',
							    '[CLS]',
							    '[SEP]',
							    '[PAD]',
							    '[MASK]',
							    'want',
							    '##want',
							    '##ed',
							    'wa',
							    'un',
							    'runn',
							    '##ing',
							    ',',
							    'low',
							    'lowest',
							]
							lowerCAmelCase__      :      List[str]         =		os.path.join(self.tmpdirname    ,     'dpr_tokenizer'   )
							os.makedirs(a    ,     exist_ok=a   )
							lowerCAmelCase__      :      Union[str, Any]         =		os.path.join(a    ,     DPR_VOCAB_FILES_NAMES['vocab_file']   )
							with open(self.vocab_file    ,     'w'    ,     encoding='utf-8'   ) as vocab_writer:
										vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]   )   )

							# BART tok
							lowerCAmelCase__      :      Optional[Any]         =		[
							    'l',
							    'o',
							    'w',
							    'e',
							    'r',
							    's',
							    't',
							    'i',
							    'd',
							    'n',
							    '\u0120',
							    '\u0120l',
							    '\u0120n',
							    '\u0120lo',
							    '\u0120low',
							    'er',
							    '\u0120lowest',
							    '\u0120newer',
							    '\u0120wider',
							    '<unk>',
							]
							lowerCAmelCase__      :      str         =		dict(zip(a    ,     range(len(a   )   )   )   )
							lowerCAmelCase__      :      int         =		['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
							lowerCAmelCase__      :      Dict         =		{'unk_token': '<unk>'}

							lowerCAmelCase__      :      Dict         =		os.path.join(self.tmpdirname    ,     'bart_tokenizer'   )
							os.makedirs(a    ,     exist_ok=a   )
							lowerCAmelCase__      :      Optional[Any]         =		os.path.join(a    ,     BART_VOCAB_FILES_NAMES['vocab_file']   )
							lowerCAmelCase__      :      Any         =		os.path.join(a    ,     BART_VOCAB_FILES_NAMES['merges_file']   )
							with open(self.vocab_file    ,     'w'    ,     encoding='utf-8'   ) as fp:
										fp.write(json.dumps(a   ) + '\n'   )
							with open(self.merges_file    ,     'w'    ,     encoding='utf-8'   ) as fp:
										fp.write('\n'.join(a   )   )






				def 							_lowerCamelCase		(						self					:      Optional[Any]   ):






							'''simple docstring'''







							return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname    ,     'dpr_tokenizer'   )   )






				def 							_lowerCamelCase		(						self					:      Any   ):






							'''simple docstring'''







							return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname    ,     'bart_tokenizer'   )   )






				def 							_lowerCamelCase		(						self					:      Optional[Any]   ):






							'''simple docstring'''







							shutil.rmtree(self.tmpdirname   )






				@require_tokenizers
				def 							_lowerCamelCase		(						self					:      Any   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Union[str, Any]         =		os.path.join(self.tmpdirname    ,     'rag_tokenizer'   )
							lowerCAmelCase__      :      Any         =		RagConfig(question_encoder=DPRConfig().to_dict()    ,     generator=BartConfig().to_dict()   )
							lowerCAmelCase__      :      Any         =		RagTokenizer(question_encoder=self.get_dpr_tokenizer()    ,     generator=self.get_bart_tokenizer()   )
							rag_config.save_pretrained(a   )
							rag_tokenizer.save_pretrained(a   )
							lowerCAmelCase__      :      List[str]         =		RagTokenizer.from_pretrained(a    ,     config=a   )
							self.assertIsInstance(new_rag_tokenizer.question_encoder    ,     a   )
							self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()    ,     rag_tokenizer.question_encoder.get_vocab()   )
							self.assertIsInstance(new_rag_tokenizer.generator    ,     a   )
							self.assertEqual(new_rag_tokenizer.generator.get_vocab()    ,     rag_tokenizer.generator.get_vocab()   )






				@slow
				def 							_lowerCamelCase		(						self					:      int   ):






							'''simple docstring'''







							lowerCAmelCase__      :      Union[str, Any]         =		RagTokenizer.from_pretrained('facebook/rag-token-nq'   )
							lowerCAmelCase__      :      Any         =		[
							    'who got the first nobel prize in physics',
							    'when is the next deadpool movie being released',
							    'which mode is used for short wave broadcast service',
							    'who is the owner of reading football club',
							    'when is the next scandal episode coming out',
							    'when is the last time the philadelphia won the superbowl',
							    'what is the most current adobe flash player version',
							    'how many episodes are there in dragon ball z',
							    'what is the first step in the evolution of the eye',
							    'where is gall bladder situated in human body',
							    'what is the main mineral in lithium batteries',
							    'who is the president of usa right now',
							    'where do the greasers live in the outsiders',
							    'panda is a national animal of which country',
							    'what is the name of manchester united stadium',
							]
							lowerCAmelCase__      :      List[str]         =		tokenizer(a   )
							self.assertIsNotNone(a   )






				@slow
				def 							_lowerCamelCase		(						self					:      List[Any]   ):






							'''simple docstring'''







							lowerCAmelCase__      :      List[str]         =		RagTokenizer.from_pretrained('facebook/rag-sequence-nq'   )
							lowerCAmelCase__      :      List[str]         =		[
							    'who got the first nobel prize in physics',
							    'when is the next deadpool movie being released',
							    'which mode is used for short wave broadcast service',
							    'who is the owner of reading football club',
							    'when is the next scandal episode coming out',
							    'when is the last time the philadelphia won the superbowl',
							    'what is the most current adobe flash player version',
							    'how many episodes are there in dragon ball z',
							    'what is the first step in the evolution of the eye',
							    'where is gall bladder situated in human body',
							    'what is the main mineral in lithium batteries',
							    'who is the president of usa right now',
							    'where do the greasers live in the outsiders',
							    'panda is a national animal of which country',
							    'what is the name of manchester united stadium',
							]
							lowerCAmelCase__      :      int         =		tokenizer(a   )
							self.assertIsNotNone(a   )