





"""simple docstring"""




import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


a						: Tuple     	=			get_tests_dir('''fixtures/test_sentencepiece_no_bos.model''')


@require_sentencepiece
@require_tokenizers
class        __UpperCamelCase				(						_lowerCAmelCase		,       unittest.TestCase						):
							lowerCamelCase   :					Optional[Any]      					=PegasusTokenizer
							lowerCamelCase   :					int      					=PegasusTokenizerFast
							lowerCamelCase   :					Optional[Any]      					=True
							lowerCamelCase   :					Union[str, Any]      					=True






							def     __a   (   self      )	-> Union[str, Any]:
								super().setUp()

								# We have a SentencePiece fixture for testing
								a      :		int	=				PegasusTokenizer(_lowerCamelCase      )
								tokenizer.save_pretrained(self.tmpdirname      )






							@cached_property
							def     __a   (   self      )	-> Optional[Any]:
								return PegasusTokenizer.from_pretrained("google/pegasus-large"      )






							def     __a   (   self      ,					**lowerCAmelCase__      )	-> Any:
								return PegasusTokenizer.from_pretrained(self.tmpdirname      ,					**_lowerCamelCase      )






							def     __a   (   self      ,					lowerCAmelCase__      )	-> int:
								return ("This is a test", "This is a test")






							def     __a   (   self      )	-> int:
								a      :		Optional[int]	=				"</s>"
								a      :		Any	=				1

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(_lowerCamelCase      )      ,					_lowerCamelCase      )
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(_lowerCamelCase      )      ,					_lowerCamelCase      )






							def     __a   (   self      )	-> Union[str, Any]:
								a      :		Optional[Any]	=				list(self.get_tokenizer().get_vocab().keys()      )

								self.assertEqual(vocab_keys[0]      ,					"<pad>"      )
								self.assertEqual(vocab_keys[1]      ,					"</s>"      )
								self.assertEqual(vocab_keys[-1]      ,					"v"      )
								self.assertEqual(len(_lowerCamelCase      )      ,					1103      )






							def     __a   (   self      )	-> Union[str, Any]:
								self.assertEqual(self.get_tokenizer().vocab_size      ,					1103      )






							def     __a   (   self      )	-> Tuple:
								a      :		Union[str, Any]	=				self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
								a      :		List[str]	=				self.tokenizer_class.from_pretrained(self.tmpdirname      )
								a      :		Dict	=				(
								    "Let\'s see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important"
								    " </s> <pad> <pad> <pad>"
								)
								a      :		Dict	=				rust_tokenizer([raw_input_str]      ,					return_tensors=_lowerCamelCase      ,					add_special_tokens=_lowerCamelCase      ).input_ids[0]
								a      :		Tuple	=				py_tokenizer([raw_input_str]      ,					return_tensors=_lowerCamelCase      ,					add_special_tokens=_lowerCamelCase      ).input_ids[0]
								self.assertListEqual(_lowerCamelCase      ,					_lowerCamelCase      )






							def     __a   (   self      )	-> str:
								a      :		Tuple	=				self._large_tokenizer
								# <mask_1> masks whole sentence while <mask_2> masks single word
								a      :		List[str]	=				"<mask_1> To ensure a <mask_2> flow of bank resolutions."
								a      :		List[Any]	=				[2, 413, 615, 114, 3, 1971, 113, 1679, 1_0710, 107, 1]
								a      :		Optional[int]	=				tokenizer([raw_input_str]      ,					return_tensors=_lowerCamelCase      ).input_ids[0]
								self.assertListEqual(_lowerCamelCase      ,					_lowerCamelCase      )






							def     __a   (   self      )	-> Dict:
								a      :		str	=				self._large_tokenizer
								# The tracebacks for the following asserts are **better** without messages or self.assertEqual
								assert tokenizer.vocab_size == 9_6103
								assert tokenizer.pad_token_id == 0
								assert tokenizer.eos_token_id == 1
								assert tokenizer.offset == 103
								assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
								assert tokenizer.unk_token == "<unk>"
								assert tokenizer.model_max_length == 1024
								a      :		Any	=				"To ensure a smooth flow of bank resolutions."
								a      :		Optional[int]	=				[413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
								a      :		Optional[Any]	=				tokenizer([raw_input_str]      ,					return_tensors=_lowerCamelCase      ).input_ids[0]
								self.assertListEqual(_lowerCamelCase      ,					_lowerCamelCase      )
								assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]      ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]






							@require_torch
							def     __a   (   self      )	-> Union[str, Any]:
								a      :		List[str]	=				["This is going to be way too long." * 150, "short example"]
								a      :		Any	=				["not super long but more than 5 tokens", "tiny"]
								a      :		str	=				self._large_tokenizer(_lowerCamelCase      ,					padding=_lowerCamelCase      ,					truncation=_lowerCamelCase      ,					return_tensors="pt"      )
								a      :		str	=				self._large_tokenizer(
								    text_target=_lowerCamelCase      ,					max_length=5      ,					padding=_lowerCamelCase      ,					truncation=_lowerCamelCase      ,					return_tensors="pt"      )

								assert batch.input_ids.shape == (2, 1024)
								assert batch.attention_mask.shape == (2, 1024)
								assert targets["input_ids"].shape == (2, 5)
								assert len(_lowerCamelCase      ) == 2  # input_ids, attention_mask.






							@slow
							def     __a   (   self      )	-> Optional[int]:
								a      :		int	=				{"input_ids": [[3_8979, 143, 1_8485, 606, 130, 2_6669, 8_7686, 121, 5_4189, 1129, 111, 2_6669, 8_7686, 121, 9114, 1_4787, 121, 1_3249, 158, 592, 956, 121, 1_4621, 3_1576, 143, 6_2613, 108, 9688, 930, 4_3430, 1_1562, 6_2613, 304, 108, 1_1443, 897, 108, 9314, 1_7415, 6_3399, 108, 1_1443, 7614, 1_8316, 118, 4284, 7148, 1_2430, 143, 1400, 2_5703, 158, 111, 4284, 7148, 1_1772, 143, 2_1297, 1064, 158, 122, 204, 3506, 1754, 1133, 1_4787, 1581, 115, 3_3224, 4482, 111, 1355, 110, 2_9173, 317, 5_0833, 108, 2_0147, 9_4665, 111, 7_7198, 107, 1], [110, 6_2613, 117, 638, 112, 1133, 121, 2_0098, 1355, 7_9050, 1_3872, 135, 1596, 5_3541, 1352, 141, 1_3039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [139, 1235, 2799, 1_8289, 1_7780, 204, 109, 9474, 1296, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
								# fmt: on

								self.tokenizer_integration_test_util(
								    expected_encoding=_lowerCamelCase      ,					model_name="google/bigbird-pegasus-large-arxiv"      ,					revision="ba85d0851d708441f91440d509690f1ab6353415"      ,					)


@require_sentencepiece
@require_tokenizers
class        __UpperCamelCase				(						_lowerCAmelCase		,       unittest.TestCase						):
							lowerCamelCase   :					str      					=PegasusTokenizer
							lowerCamelCase   :					Union[str, Any]      					=PegasusTokenizerFast
							lowerCamelCase   :					Any      					=True
							lowerCamelCase   :					str      					=True






							def     __a   (   self      )	-> Optional[Any]:
								super().setUp()

								# We have a SentencePiece fixture for testing
								a      :		Optional[Any]	=				PegasusTokenizer(_lowerCamelCase      ,					offset=0      ,					mask_token_sent=_lowerCamelCase      ,					mask_token="[MASK]"      )
								tokenizer.save_pretrained(self.tmpdirname      )






							@cached_property
							def     __a   (   self      )	-> Union[str, Any]:
								return PegasusTokenizer.from_pretrained("google/bigbird-pegasus-large-arxiv"      )






							def     __a   (   self      ,					**lowerCAmelCase__      )	-> str:
								return PegasusTokenizer.from_pretrained(self.tmpdirname      ,					**_lowerCamelCase      )






							def     __a   (   self      ,					lowerCAmelCase__      )	-> Union[str, Any]:
								return ("This is a test", "This is a test")






							def     __a   (   self      )	-> Tuple:
								a      :		str	=				self.rust_tokenizer_class.from_pretrained(self.tmpdirname      )
								a      :		Optional[Any]	=				self.tokenizer_class.from_pretrained(self.tmpdirname      )
								a      :		Any	=				(
								    "Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"
								    " <pad> <pad> <pad>"
								)
								a      :		Any	=				rust_tokenizer([raw_input_str]      ,					return_tensors=_lowerCamelCase      ,					add_special_tokens=_lowerCamelCase      ).input_ids[0]
								a      :		Tuple	=				py_tokenizer([raw_input_str]      ,					return_tensors=_lowerCamelCase      ,					add_special_tokens=_lowerCamelCase      ).input_ids[0]
								self.assertListEqual(_lowerCamelCase      ,					_lowerCamelCase      )






							@require_torch
							def     __a   (   self      )	-> str:
								a      :		Optional[int]	=				["This is going to be way too long." * 1000, "short example"]
								a      :		Optional[int]	=				["not super long but more than 5 tokens", "tiny"]
								a      :		str	=				self._large_tokenizer(_lowerCamelCase      ,					padding=_lowerCamelCase      ,					truncation=_lowerCamelCase      ,					return_tensors="pt"      )
								a      :		str	=				self._large_tokenizer(
								    text_target=_lowerCamelCase      ,					max_length=5      ,					padding=_lowerCamelCase      ,					truncation=_lowerCamelCase      ,					return_tensors="pt"      )

								assert batch.input_ids.shape == (2, 4096)
								assert batch.attention_mask.shape == (2, 4096)
								assert targets["input_ids"].shape == (2, 5)
								assert len(_lowerCamelCase      ) == 2  # input_ids, attention_mask.






							def     __a   (   self      )	-> int:
								a      :		Any	=				(
								    "This is an example string that is used to test the original TF implementation against the HF"
								    " implementation"
								)

								a      :		Dict	=				self._large_tokenizer(_lowerCamelCase      ).input_ids

								self.assertListEqual(
								    _lowerCamelCase      ,					[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 2_5016, 3137, 464, 109, 2_6955, 3137, 1]      ,					)










"""simple docstring"""


import argparse
import struct
import unittest


class 					snake_case		:


   '''simple docstring'''

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

     '''simple docstring'''
     __A									= data

     # Initialize hash values
     __A									= [
         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
     __A									= [
         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,
     ]

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


   @staticmethod
   def 				_SCREAMING_SNAKE_CASE				(	_lowerCamelCase :     bytes  ):

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


   def 				_SCREAMING_SNAKE_CASE				(	self :     int  ):

     '''simple docstring'''
     # Convert into blocks of 64 bytes
     __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''',       _lowerCamelCase  )  )
       # 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
           ) % 0X100_000_000

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

         __A			,    __A			,    __A			,    __A			,    __A			,    __A			,    __A			,    __A									= (
             g,
             f,
             e,
             ((d + tempa) % 0X100_000_000),
             c,
             b,
             a,
             ((tempa + tempa) % 0X100_000_000),
         )

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

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

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






   def 				_SCREAMING_SNAKE_CASE				(	self :     Union[str, Any],       _lowerCamelCase :     int,       _lowerCamelCase :     int  ):

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





class 					snake_case		(							unittest.TestCase						):


   '''simple docstring'''

   def 				_SCREAMING_SNAKE_CASE				(	self :     Dict  ):

     '''simple docstring'''
     import hashlib

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





def 					lowerCAmelCase				(    ):




  """simple docstring"""







  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()




