'''simple docstring'''

import argparse
import struct
import unittest


class 				_lowercase	:
      '''simple docstring'''


      def __init__(				self					,lowerCamelCase_							)			->			None:
         UpperCAmelCase__							:				List[Any]   				=  data

         # Initialize hash values
         UpperCAmelCase__							:				Tuple   				=  [
             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
         UpperCAmelCase__							:				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,
         ]

         UpperCAmelCase__							:				str   				=  self.preprocessing(self.data							)
         self.final_hash()




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




      def 		lowerCAmelCase__					(				self							)			->			None:
         UpperCAmelCase__							:				Optional[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
            UpperCAmelCase__							:				Union[str, Any]   				=  list(struct.unpack('''>16L'''					,lowerCAmelCase_							)							)
            # add 48 0-ed integers
            words += [0] * 48

            UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__							:				Union[str, Any]   				=  self.hashes

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

                  UpperCAmelCase__							:				Any   				=  (
                      words[index - 16] + sa + words[index - 7] + sa
                  ) % 0x100_000_000

               # Compression
               UpperCAmelCase__							:				str   				=  self.ror(lowerCAmelCase_					,6							) ^ self.ror(lowerCAmelCase_					,11							) ^ self.ror(lowerCAmelCase_					,25							)
               UpperCAmelCase__							:				List[str]   				=  (e & f) ^ ((~e & 0xff_fff_fff) & g)
               UpperCAmelCase__							:				Union[str, Any]   				=  (
                   h + sa + ch + self.round_constants[index] + words[index]
               ) % 0x100_000_000
               UpperCAmelCase__							:				Union[str, Any]   				=  self.ror(lowerCAmelCase_					,2							) ^ self.ror(lowerCAmelCase_					,13							) ^ self.ror(lowerCAmelCase_					,22							)
               UpperCAmelCase__							:				int   				=  (a & b) ^ (a & c) ^ (b & c)
               UpperCAmelCase__							:				str   				=  (sa + maj) % 0x100_000_000

               UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__				,      UpperCAmelCase__							:				Dict   				=  (
                   g,
                   f,
                   e,
                   ((d + tempa) % 0x100_000_000),
                   c,
                   b,
                   a,
                   ((tempa + tempa) % 0x100_000_000),
               )

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

            # Modify final values
            UpperCAmelCase__							:				Tuple   				=  [
                ((element + mutated_hash_values[index]) % 0x100_000_000)
                for index, element in enumerate(self.hashes							)
            ]

         UpperCAmelCase__							:				Union[str, Any]   				=  ''''''.join([hex(lowerCAmelCase_							)[2:].zfill(8							) for value in self.hashes]							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_							)			->			int:
         return 0xff_fff_fff & (value << (32 - rotations)) | (value >> rotations)




class 				_lowercase	(      unittest.TestCase   ):
      '''simple docstring'''


      def 		lowerCAmelCase__					(				self							)			->			None:
         import hashlib

         UpperCAmelCase__							:				int   				=  bytes('''Test String'''					,'''utf-8'''							)
         self.assertEqual(SHAaaa(lowerCAmelCase_							).hash					,hashlib.shaaaa(lowerCAmelCase_							).hexdigest()							)







def __UpperCamelCase(   ):
   '''simple docstring'''
   import doctest

   doctest.testmod()

   UpperCAmelCase__							:				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'''    )

   UpperCAmelCase__							:				List[Any]   				=  parser.parse_args()

   UpperCAmelCase__							:				Optional[Any]   				=  args.input_string

   # hash input should be a bytestring
   if args.input_file:
      with open(args.input_file  ,			'''rb'''    ) as f:
         UpperCAmelCase__							:				Union[str, Any]   				=  f.read()
   else:
      UpperCAmelCase__							:				Any   				=  bytes(lowercase__  ,			'''utf-8'''    )

   print(SHAaaa(lowercase__    ).hash    )


if __name__ == "__main__":
  main()





'''simple docstring'''

import torch

from transformers import AutoModel


class 				_lowercase	(      torch.nn.Module   ):
      '''simple docstring'''


      def __init__(				self					,lowerCamelCase_="sayef/fsner-bert-base-uncased"							)			->			Dict:



         '''simple docstring'''



         super(lowerCamelCase_					,self							).__init__()

         UpperCAmelCase__							:				Union[str, Any]   				=  AutoModel.from_pretrained(lowerCamelCase_					,return_dict=lowerCamelCase_							)
         UpperCAmelCase__							:				str   				=  torch.nn.CosineSimilarity(3					,1e-08							)
         UpperCAmelCase__							:				int   				=  torch.nn.Softmax(dim=1							)




      def 		lowerCAmelCase__					(				self					,**lowerCamelCase_							)			->			Optional[Any]:



         '''simple docstring'''



         return self.bert(**lowerCamelCase_							).last_hidden_state




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			str:



         '''simple docstring'''



         return token_embeddings.sum(2					,keepdim=lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_=1							)			->			int:



         '''simple docstring'''



         return self.softmax(T * self.cos(lowerCamelCase_					,lowerCamelCase_							)							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_							)			->			Tuple:



         '''simple docstring'''



         UpperCAmelCase__							:				List[Any]   				=  W_supports['''sizes'''].tolist()
         UpperCAmelCase__							:				Union[str, Any]   				=  W_supports['''start_token_id'''].item()
         UpperCAmelCase__							:				int   				=  W_supports['''end_token_id'''].item()

         del W_supports["sizes"]
         del W_supports["start_token_id"]
         del W_supports["end_token_id"]

         UpperCAmelCase__							:				Any   				=  self.BERT(**lowerCamelCase_							)
         UpperCAmelCase__							:				Any   				=  self.BERT(**lowerCamelCase_							)

         UpperCAmelCase__							:				Any   				=  None
         UpperCAmelCase__							:				Tuple   				=  None

         UpperCAmelCase__							:				Dict   				=  W_supports['''input_ids'''] == start_token_id
         UpperCAmelCase__							:				Any   				=  W_supports['''input_ids'''] == end_token_id

         for i, size in enumerate(lowerCamelCase_							):
            if i == 0:
               UpperCAmelCase__							:				int   				=  0
            else:
               UpperCAmelCase__							:				str   				=  support_sizes[i - 1]

            UpperCAmelCase__							:				Dict   				=  S[s : s + size][start_token_masks[s : s + size]]
            UpperCAmelCase__							:				Union[str, Any]   				=  S[s : s + size][end_token_masks[s : s + size]]

            UpperCAmelCase__							:				int   				=  torch.matmul(q[i]					,s_start.T							).sum(1							).softmax(0							)
            UpperCAmelCase__							:				int   				=  torch.matmul(q[i]					,s_end.T							).sum(1							).softmax(0							)

            if p_starts is not None:
               UpperCAmelCase__							:				str   				=  torch.vstack((p_starts, p_start)							)
               UpperCAmelCase__							:				Optional[int]   				=  torch.vstack((p_ends, p_end)							)
            else:
               UpperCAmelCase__							:				Union[str, Any]   				=  p_start
               UpperCAmelCase__							:				int   				=  p_end

         return p_starts, p_ends




