





import os
import random
import sys

from . import cryptomath_module as cryptoMath  # noqa: N812
from . import rabin_miller as rabinMiller  # noqa: N812







def        __lowerCamelCase (							)		->    List[Any]:






  """simple docstring"""

  print("""Making key files..."""   )
  make_key_files("""rsa"""   ,					1_0_2_4   )
  print("""Key files generation successful."""   )







def        __lowerCamelCase (							__a       :int   )		->    List[str]:






  """simple docstring"""

  print("""Generating prime p..."""   )
  A__  				=       rabinMiller.generate_large_prime(lowerCAmelCase__   )
  print("""Generating prime q..."""   )
  A__  				=       rabinMiller.generate_large_prime(lowerCAmelCase__   )
  A__  				=       p * q

  print("""Generating e that is relatively prime to (p - 1) * (q - 1)..."""   )
  while True:
    A__  				=       random.randrange(2 ** (key_size - 1)   ,					2 ** (key_size)   )
    if cryptoMath.gcd(lowerCAmelCase__   ,					(p - 1) * (q - 1)   ) == 1:
      break

  print("""Calculating d that is mod inverse of e..."""   )
  A__  				=       cryptoMath.find_mod_inverse(lowerCAmelCase__   ,					(p - 1) * (q - 1)   )

  A__  				=       (n, e)
  A__  				=       (n, d)
  return (public_key, private_key)







def        __lowerCamelCase (							__a       :str   ,					__a       :int   )		->    Any:






  """simple docstring"""

  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()

  A__  				=       generate_key(lowerCAmelCase__   )
  print(F'\nWriting public key to file {name}_pubkey.txt...'   )
  with open(F'{name}_pubkey.txt'   ,					"""w"""   ) as out_file:
    out_file.write(F'{key_size},{public_key[0]},{public_key[1]}'   )

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


if __name__ == "__main__":
     main()










from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A   : Tuple			=				logging.get_logger(__name__)

A   : Optional[int]			=				{
    '''roberta-base''': '''https://huggingface.co/roberta-base/resolve/main/config.json''',
    '''roberta-large''': '''https://huggingface.co/roberta-large/resolve/main/config.json''',
    '''roberta-large-mnli''': '''https://huggingface.co/roberta-large-mnli/resolve/main/config.json''',
    '''distilroberta-base''': '''https://huggingface.co/distilroberta-base/resolve/main/config.json''',
    '''roberta-base-openai-detector''': '''https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json''',
    '''roberta-large-openai-detector''': '''https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json''',
}


class   A      (SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''




			__lowerCamelCase     :	Union[str, Any]          =   '''roberta'''






			def __init__(      self       :   Any							,     __lowerCAmelCase       :   Tuple=5_02_65							,     __lowerCAmelCase       :   Optional[int]=7_68							,     __lowerCAmelCase       :   Union[str, Any]=12							,     __lowerCAmelCase       :   Dict=12							,     __lowerCAmelCase       :   Optional[Any]=30_72							,     __lowerCAmelCase       :   Any="gelu"							,     __lowerCAmelCase       :   Optional[Any]=0.1							,     __lowerCAmelCase       :   Optional[int]=0.1							,     __lowerCAmelCase       :   Optional[Any]=5_12							,     __lowerCAmelCase       :   int=2							,     __lowerCAmelCase       :   List[str]=0.0_2							,     __lowerCAmelCase       :   Dict=1e-12							,     __lowerCAmelCase       :   Optional[int]=1							,     __lowerCAmelCase       :   Tuple=0							,     __lowerCAmelCase       :   int=2							,     __lowerCAmelCase       :   Dict="absolute"							,     __lowerCAmelCase       :   Optional[Any]=True							,     __lowerCAmelCase       :   Union[str, Any]=None							,     **__lowerCAmelCase       :   str							,     )     ->     str:







					"""simple docstring"""






					super().__init__(pad_token_id=__lowerCAmelCase							,     bos_token_id=__lowerCAmelCase							,     eos_token_id=__lowerCAmelCase							,     **__lowerCAmelCase       )

					A__  				=       vocab_size
					A__  				=       hidden_size
					A__  				=       num_hidden_layers
					A__  				=       num_attention_heads
					A__  				=       hidden_act
					A__  				=       intermediate_size
					A__  				=       hidden_dropout_prob
					A__  				=       attention_probs_dropout_prob
					A__  				=       max_position_embeddings
					A__  				=       type_vocab_size
					A__  				=       initializer_range
					A__  				=       layer_norm_eps
					A__  				=       position_embedding_type
					A__  				=       use_cache
					A__  				=       classifier_dropout


class   A      (SCREAMING_SNAKE_CASE   ):
			'''simple docstring'''




			@property
			def        a_	(      self       :   int       )     ->     Mapping[str, Mapping[int, str]]:







					"""simple docstring"""






					if self.task == "multiple-choice":
							A__  				=       {0: """batch""", 1: """choice""", 2: """sequence"""}
					else:
							A__  				=       {0: """batch""", 1: """sequence"""}
					return OrderedDict(
					    [
					        ("""input_ids""", dynamic_axis),
					        ("""attention_mask""", dynamic_axis),
					    ]       )



