
'''simple docstring'''







import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


if TYPE_CHECKING:
      from ... import PreTrainedTokenizerBase, TensorType

_snake_case				:   List[str]     =				logging.get_logger(__name__)


class 			lowerCAmelCase (				_UpperCAmelCase			):
  a							:					List[Any]       =					"""vision-encoder-decoder"""
  a							:					int       =					True




  def __init__(				self					,						**UpperCamelCase      ):
        super().__init__(**lowerCamelCase_      )
        if "encoder" not in kwargs or "decoder" not in kwargs:
              raise ValueError(
                  F'A configuraton of type {self.model_type} cannot be instantiated because '
                  F'not both `encoder` and `decoder` sub-configurations are passed, but only {kwargs}'      )

        _SCREAMING_SNAKE_CASE				= kwargs.pop("encoder"      )
        _SCREAMING_SNAKE_CASE				= encoder_config.pop("model_type"      )
        _SCREAMING_SNAKE_CASE				= kwargs.pop("decoder"      )
        _SCREAMING_SNAKE_CASE				= decoder_config.pop("model_type"      )

        _SCREAMING_SNAKE_CASE				= AutoConfig.for_model(lowerCamelCase_					,						**lowerCamelCase_      )
        _SCREAMING_SNAKE_CASE				= AutoConfig.for_model(lowerCamelCase_					,						**lowerCamelCase_      )
        _SCREAMING_SNAKE_CASE				= True




  @classmethod
  def     lowercase       (				cls					,						UpperCamelCase					,						UpperCamelCase					,						**UpperCamelCase      ):
        logger.info("Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"      )
        _SCREAMING_SNAKE_CASE				= True
        _SCREAMING_SNAKE_CASE				= True

        return cls(encoder=encoder_config.to_dict()					,						decoder=decoder_config.to_dict()					,						**lowerCamelCase_      )




  def     lowercase       (				self      ):
        _SCREAMING_SNAKE_CASE				= copy.deepcopy(self.__dict__      )
        _SCREAMING_SNAKE_CASE				= self.encoder.to_dict()
        _SCREAMING_SNAKE_CASE				= self.decoder.to_dict()
        _SCREAMING_SNAKE_CASE				= self.__class__.model_type
        return output


class 			lowerCAmelCase (				_UpperCAmelCase			):
  a							:					List[str]       =					version.parse("""1.11"""			)




  @property
  def     lowercase       (				self      ):
        return OrderedDict(
            [
                ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
            ]      )




  @property
  def     lowercase       (				self      ):
        return 1e-4




  @property
  def     lowercase       (				self      ):
        return OrderedDict({"last_hidden_state": {0: "batch", 1: "encoder_sequence"}}      )


class 			lowerCAmelCase (				_UpperCAmelCase			):




  @property
  def     lowercase       (				self      ):
        _SCREAMING_SNAKE_CASE				= OrderedDict()
        _SCREAMING_SNAKE_CASE				= {0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
        _SCREAMING_SNAKE_CASE				= {0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
        _SCREAMING_SNAKE_CASE				= {0: '''batch''', 1: '''encoder_sequence'''}

        return common_inputs




  def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase = -1					,						UpperCamelCase = -1					,						UpperCamelCase = False					,						UpperCamelCase = None					,						):
        import torch

        _SCREAMING_SNAKE_CASE				= OrderedDict()

        _SCREAMING_SNAKE_CASE				= super().generate_dummy_inputs(
            lowerCamelCase_					,						batch_size=lowerCamelCase_					,						seq_length=lowerCamelCase_					,						is_pair=lowerCamelCase_					,						framework=lowerCamelCase_      )

        _SCREAMING_SNAKE_CASE				= dummy_input['''input_ids'''].shape
        _SCREAMING_SNAKE_CASE				= (batch, encoder_sequence, self._config.encoder_hidden_size)
        _SCREAMING_SNAKE_CASE				= dummy_input.pop("input_ids"      )
        _SCREAMING_SNAKE_CASE				= dummy_input.pop("attention_mask"      )
        _SCREAMING_SNAKE_CASE				= torch.zeros(lowerCamelCase_      )

        return common_inputs


class 			lowerCAmelCase (				_UpperCAmelCase			):




  @property
  def     lowercase       (				self      ):
        pass




  def     lowercase       (				self					,						UpperCamelCase      ):
        return VisionEncoderDecoderEncoderOnnxConfig(lowerCamelCase_      )




  def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase					,						UpperCamelCase = "default"      ):
        _SCREAMING_SNAKE_CASE				= encoder_config.hidden_size
        return VisionEncoderDecoderDecoderOnnxConfig(lowerCamelCase_					,						lowerCamelCase_      )

'''simple docstring'''







import os
import random
import sys

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



def 			_a		(	):
						print("Making key files..."  )
						make_key_files("rsa"	,			1024  )
						print("Key files generation successful."  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   int  ):
						print("Generating prime p..."  )
						_SCREAMING_SNAKE_CASE				= rabinMiller.generate_large_prime(_SCREAMING_SNAKE_CASE  )
						print("Generating prime q..."  )
						_SCREAMING_SNAKE_CASE				= rabinMiller.generate_large_prime(_SCREAMING_SNAKE_CASE  )
						_SCREAMING_SNAKE_CASE				= p * q

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

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

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



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str	,			_SCREAMING_SNAKE_CASE		:   int  ):
						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()

						_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE				= generate_key(_SCREAMING_SNAKE_CASE  )
						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()