
"""simple docstring"""

from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType

class __lowerCAmelCase	(   lowercase_    ):
     lowercase		     =		["image_processor", "tokenizer"]
     lowercase		     =		"Pix2StructImageProcessor"
     lowercase		     =		("T5Tokenizer", "T5TokenizerFast")





     def __init__(			self			,  __UpperCAmelCase			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= False
      super().__init__(lowerCamelCase_			,  lowerCamelCase_   )





     def __call__(			self			,  __UpperCAmelCase=None			,  __UpperCAmelCase = None			,  __UpperCAmelCase = True			,  __UpperCAmelCase = False			,  __UpperCAmelCase = None			,  __UpperCAmelCase = None			,  __UpperCAmelCase = 2048			,  __UpperCAmelCase = 0			,  __UpperCAmelCase = None			,  __UpperCAmelCase = None			,  __UpperCAmelCase = False			,  __UpperCAmelCase = False			,  __UpperCAmelCase = False			,  __UpperCAmelCase = False			,  __UpperCAmelCase = False			,  __UpperCAmelCase = True			,  __UpperCAmelCase = None			,  **__UpperCAmelCase			,  ):

      '''simple docstring'''




      if images is None and text is None:
       raise ValueError('You have to specify either images or text.'   )

      # Get only text
      if images is None and not self.image_processor.is_vqa:
       __UpperCamelCase       						= self.tokenizer
       __UpperCamelCase       						= self.tokenizer(
           text=lowerCamelCase_			,  add_special_tokens=lowerCamelCase_			,  padding=lowerCamelCase_			,  truncation=lowerCamelCase_			,  max_length=lowerCamelCase_			,  stride=lowerCamelCase_			,  pad_to_multiple_of=lowerCamelCase_			,  return_attention_mask=lowerCamelCase_			,  return_overflowing_tokens=lowerCamelCase_			,  return_special_tokens_mask=lowerCamelCase_			,  return_offsets_mapping=lowerCamelCase_			,  return_token_type_ids=lowerCamelCase_			,  return_length=lowerCamelCase_			,  verbose=lowerCamelCase_			,  return_tensors=lowerCamelCase_			,  **lowerCamelCase_			,  )
       return text_encoding

      if not self.image_processor.is_vqa:
       # add pixel_values
       __UpperCamelCase       						= self.image_processor(
           lowerCamelCase_			,  return_tensors=lowerCamelCase_			,  max_patches=lowerCamelCase_			,  **lowerCamelCase_   )
      else:
       # add pixel_values and bbox
       __UpperCamelCase       						= self.image_processor(
           lowerCamelCase_			,  return_tensors=lowerCamelCase_			,  max_patches=lowerCamelCase_			,  header_text=lowerCamelCase_			,  **lowerCamelCase_   )

      if text is not None and not self.image_processor.is_vqa:
       __UpperCamelCase       						= self.tokenizer(
           text=lowerCamelCase_			,  add_special_tokens=lowerCamelCase_			,  padding=lowerCamelCase_			,  truncation=lowerCamelCase_			,  max_length=lowerCamelCase_			,  stride=lowerCamelCase_			,  pad_to_multiple_of=lowerCamelCase_			,  return_attention_mask=lowerCamelCase_			,  return_overflowing_tokens=lowerCamelCase_			,  return_special_tokens_mask=lowerCamelCase_			,  return_offsets_mapping=lowerCamelCase_			,  return_token_type_ids=lowerCamelCase_			,  return_length=lowerCamelCase_			,  verbose=lowerCamelCase_			,  return_tensors=lowerCamelCase_			,  **lowerCamelCase_			,  )

       if "attention_mask" in text_encoding:
        __UpperCamelCase       						= text_encoding.pop('attention_mask'   )
       if "input_ids" in text_encoding:
        __UpperCamelCase       						= text_encoding.pop('input_ids'   )
      else:
       __UpperCamelCase       						= None

      if text_encoding is not None:
       encoding_image_processor.update(lowerCamelCase_   )

      return encoding_image_processor





     def 		UpperCAmelCase      (			self			,  *__UpperCAmelCase			,  **__UpperCAmelCase   ):

      '''simple docstring'''




      return self.tokenizer.batch_decode(*lowerCamelCase_			,  **lowerCamelCase_   )





     def 		UpperCAmelCase      (			self			,  *__UpperCAmelCase			,  **__UpperCAmelCase   ):

      '''simple docstring'''




      return self.tokenizer.decode(*lowerCamelCase_			,  **lowerCamelCase_   )







     @property
     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.tokenizer.model_input_names
      __UpperCamelCase       						= self.image_processor.model_input_names
      return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names   )   )





"""simple docstring"""

import argparse
import struct
import unittest

class __lowerCAmelCase	:





     def __init__(			self			,  __UpperCAmelCase   ):

      '''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 		UpperCAmelCase      (			__UpperCAmelCase   ):

      '''simple docstring'''




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





     def 		UpperCAmelCase      (			self   ):

      '''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'			,  __UpperCAmelCase   )   )
       # 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(__UpperCAmelCase			,  6   ) ^ self.ror(__UpperCAmelCase			,  11   ) ^ self.ror(__UpperCAmelCase			,  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(__UpperCAmelCase			,  2   ) ^ self.ror(__UpperCAmelCase			,  13   ) ^ self.ror(__UpperCAmelCase			,  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(__UpperCAmelCase   )[2:].zfill(8   ) for value in self.hashes]   )







     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase			,  __UpperCAmelCase   ):

      '''simple docstring'''




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


class __lowerCAmelCase	(   unittest.TestCase    ):





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      import hashlib

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






def 							A		(       )   ->			None:
 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(snake_case       ,      'utf-8'	)

 print(SHAaaa(snake_case	).hash	)


if __name__ == "__main__":
      main()



