

'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase__         =      logging.get_logger(__name__)

lowercase__         =      {
    '''microsoft/trocr-base-handwritten''': (
        '''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'''
    ),
    # See all TrOCR models at https://huggingface.co/models?filter=trocr
}




class 	A_			(    _UpperCAmelCase							):






     '''simple docstring'''



     UpperCAmelCase_						:     List[str]  		=  'trocr'
     UpperCAmelCase_						:     int  		=  ['past_key_values']
     UpperCAmelCase_						:     Tuple  		=  {
         'num_attention_heads': 'decoder_attention_heads',
         'hidden_size': 'd_model',
         'num_hidden_layers': 'decoder_layers',
     }


     def __init__(		self			:					Optional[int]					,      lowercase_			:					Optional[int]=50_265					,      lowercase_			:					Tuple=1_024					,      lowercase_			:					Union[str, Any]=12					,      lowercase_			:					Tuple=16					,      lowercase_			:					Any=4_096					,      lowercase_			:					Optional[int]="gelu"					,      lowercase_			:					int=512					,      lowercase_			:					Optional[Any]=0.1					,      lowercase_			:					Dict=0.0					,      lowercase_			:					str=0.0					,      lowercase_			:					Dict=2					,      lowercase_			:					Dict=0.02					,      lowercase_			:					str=0.0					,      lowercase_			:					Optional[int]=True					,      lowercase_			:					str=False					,      lowercase_			:					List[Any]=True					,      lowercase_			:					List[Any]=True					,      lowercase_			:					List[str]=1					,      lowercase_			:					Optional[int]=0					,      lowercase_			:					str=2					,      **lowercase_			:					Optional[Any]					,      )						->     Dict:
      UpperCAmelCase	:     Tuple						 =			vocab_size
      UpperCAmelCase	:     List[Any]						 =			d_model
      UpperCAmelCase	:     Dict						 =			decoder_layers
      UpperCAmelCase	:     List[Any]						 =			decoder_attention_heads
      UpperCAmelCase	:     Dict						 =			decoder_ffn_dim
      UpperCAmelCase	:     Dict						 =			activation_function
      UpperCAmelCase	:     Optional[int]						 =			max_position_embeddings
      UpperCAmelCase	:     str						 =			dropout
      UpperCAmelCase	:     Tuple						 =			attention_dropout
      UpperCAmelCase	:     Dict						 =			activation_dropout
      UpperCAmelCase	:     str						 =			init_std
      UpperCAmelCase	:     Optional[int]						 =			decoder_layerdrop
      UpperCAmelCase	:     List[Any]						 =			use_cache
      UpperCAmelCase	:     Union[str, Any]						 =			scale_embedding
      UpperCAmelCase	:     List[Any]						 =			use_learned_position_embeddings
      UpperCAmelCase	:     str						 =			layernorm_embedding

      super().__init__(
          pad_token_id=SCREAMING_SNAKE_CASE_					,      bos_token_id=SCREAMING_SNAKE_CASE_					,      eos_token_id=SCREAMING_SNAKE_CASE_					,      decoder_start_token_id=SCREAMING_SNAKE_CASE_					,      **SCREAMING_SNAKE_CASE_					,      )







'''simple docstring'''

import os
import random
import sys

from . import cryptomath_module as cryptomath
from . import rabin_miller

lowercase__         =      3




def 				UpperCamelCase(					UpperCAmelCase_     ):
 print('Generating primitive root of p'     )
 while True:
  UpperCAmelCase	:     Union[str, Any]						 =			random.randrange(3  ,	UpperCAmelCase_     )
  if pow(UpperCAmelCase_  ,	2  ,	UpperCAmelCase_     ) == 1:
   continue
  if pow(UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_     ) == 1:
   continue
  return g




def 				UpperCamelCase(					UpperCAmelCase_     ):
 print('Generating prime p...'     )
 UpperCAmelCase	:     str						 =			rabin_miller.generate_large_prime(UpperCAmelCase_     )  # select large prime number.
 UpperCAmelCase	:     List[str]						 =			primitive_root(UpperCAmelCase_     )  # one primitive root on modulo p.
 UpperCAmelCase	:     List[Any]						 =			random.randrange(3  ,	UpperCAmelCase_     )  # private_key -> have to be greater than 2 for safety.
 UpperCAmelCase	:     List[Any]						 =			cryptomath.find_mod_inverse(pow(UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_     )  ,	UpperCAmelCase_     )

 UpperCAmelCase	:     Tuple						 =			(key_size, e_a, e_a, p)
 UpperCAmelCase	:     Optional[int]						 =			(key_size, d)

 return public_key, private_key




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_     ):
 if os.path.exists(F"""{name}_pubkey.txt"""     ) or os.path.exists(F"""{name}_privkey.txt"""     ):
  print('\nWARNING:'     )
  print(
      F"""\"{name}_pubkey.txt\" or \"{name}_privkey.txt\" already exists. \n"""
      'Use a different name or delete these files and re-run this program.'     )
  sys.exit()

 UpperCAmelCase ,			UpperCAmelCase	:     Dict						 =			generate_key(UpperCAmelCase_     )
 print(F"""\nWriting public key to file {name}_pubkey.txt..."""     )
 with open(F"""{name}_pubkey.txt"""  ,	'w'     ) as fo:
  fo.write(F"""{public_key[0]},{public_key[1]},{public_key[2]},{public_key[3]}"""     )

 print(F"""Writing private key to file {name}_privkey.txt..."""     )
 with open(F"""{name}_privkey.txt"""  ,	'w'     ) as fo:
  fo.write(F"""{private_key[0]},{private_key[1]}"""     )




def 				UpperCamelCase(					):
 print('Making key files...'     )
 make_key_files('elgamal'  ,	20_48     )
 print('Key files generation successful'     )


if __name__ == "__main__":
 main()




