"""simple docstring"""







import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
       from .tokenization_mbart import MBartTokenizer
else:
       __SCREAMING_SNAKE_CASE								=None


__SCREAMING_SNAKE_CASE								=logging.get_logger(__name__)


__SCREAMING_SNAKE_CASE								={"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

__SCREAMING_SNAKE_CASE								={
    "vocab_file": {
        "facebook/mbart-large-en-ro": (
            "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model"
        ),
        "facebook/mbart-large-cc25": (
            "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "facebook/mbart-large-en-ro": "https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json",
        "facebook/mbart-large-cc25": "https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json",
    },
}

__SCREAMING_SNAKE_CASE								={
    "facebook/mbart-large-en-ro": 1024,
    "facebook/mbart-large-cc25": 1024,
}

# fmt: off
__SCREAMING_SNAKE_CASE								=["ar_AR", "cs_CZ", "de_DE", "en_XX", "es_XX", "et_EE", "fi_FI", "fr_XX", "gu_IN", "hi_IN", "it_IT", "ja_XX", "kk_KZ", "ko_KR", "lt_LT", "lv_LV", "my_MM", "ne_NP", "nl_XX", "ro_RO", "ru_RU", "si_LK", "tr_TR", "vi_VN", "zh_CN"]







class  UpperCamelCase	(    lowercase_						):
   lowercase							=						VOCAB_FILES_NAMES
   lowercase							=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowercase							=						PRETRAINED_VOCAB_FILES_MAP
   lowercase							=						['input_ids', 'attention_mask']
   lowercase							=						MBartTokenizer

   lowercase							=						[]
   lowercase							=						[]
   def __init__(    self  ,__UpperCamelCase=None  ,__UpperCamelCase=None  ,__UpperCamelCase="<s>"  ,__UpperCamelCase="</s>"  ,__UpperCamelCase="</s>"  ,__UpperCamelCase="<s>"  ,__UpperCamelCase="<unk>"  ,__UpperCamelCase="<pad>"  ,__UpperCamelCase="<mask>"  ,__UpperCamelCase=None  ,__UpperCamelCase=None  ,__UpperCamelCase=None  ,**__UpperCamelCase  ,)			->   str:


        '''simple docstring'''


        lowercase_			:       List[Any]									=			AddedToken(__UpperCamelCase  ,lstrip=__UpperCamelCase  ,rstrip=__UpperCamelCase    ) if isinstance(__UpperCamelCase  ,__UpperCamelCase    ) else mask_token

        super().__init__(
            vocab_file=__UpperCamelCase  ,tokenizer_file=__UpperCamelCase  ,bos_token=__UpperCamelCase  ,eos_token=__UpperCamelCase  ,sep_token=__UpperCamelCase  ,cls_token=__UpperCamelCase  ,unk_token=__UpperCamelCase  ,pad_token=__UpperCamelCase  ,mask_token=__UpperCamelCase  ,src_lang=__UpperCamelCase  ,tgt_lang=__UpperCamelCase  ,additional_special_tokens=__UpperCamelCase  ,**__UpperCamelCase  ,)

        lowercase_			:       Optional[int]									=			vocab_file
        lowercase_			:       str									=			False if not self.vocab_file else True

        lowercase_			:       Union[str, Any]									=			FAIRSEQ_LANGUAGE_CODES.copy()

        if additional_special_tokens is not None:
             # Only add those special tokens if they are not already there.
             _additional_special_tokens.extend(
                 [t for t in additional_special_tokens if t not in _additional_special_tokens]    )

        self.add_special_tokens({'additional_special_tokens': _additional_special_tokens}    )
        lowercase_			:       List[Any]									=			{
            lang_code: self.convert_tokens_to_ids(__UpperCamelCase    ) for lang_code in FAIRSEQ_LANGUAGE_CODES
        }

        lowercase_			:       int									=			src_lang if src_lang is not None else 'en_XX'
        lowercase_			:       Optional[Any]									=			self.convert_tokens_to_ids(self._src_lang    )
        lowercase_			:       Optional[int]									=			tgt_lang
        self.set_src_lang_special_tokens(self._src_lang    )
   @property
   def     _UpperCAmelCase     (    self    )			->   str:


        '''simple docstring'''


        return self._src_lang
   @src_lang.setter
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   None:


        '''simple docstring'''


        lowercase_			:       Union[str, Any]									=			new_src_lang
        self.set_src_lang_special_tokens(self._src_lang    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = None    )			->   List[int]:


        '''simple docstring'''


        if token_ids_a is None:
             return self.prefix_tokens + token_ids_a + self.suffix_tokens
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = None    )			->   List[int]:


        '''simple docstring'''


        lowercase_			:       Union[str, Any]									=			[self.sep_token_id]
        lowercase_			:       Any									=			[self.cls_token_id]

        if token_ids_a is None:
             return len(cls + token_ids_a + sep    ) * [0]
        return len(cls + token_ids_a + sep + sep + token_ids_a + sep    ) * [0]
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase  ,__UpperCamelCase  ,__UpperCamelCase  ,**__UpperCamelCase    )			->   List[str]:


        '''simple docstring'''


        if src_lang is None or tgt_lang is None:
             raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'    )
        lowercase_			:       Tuple									=			src_lang
        lowercase_			:       int									=			self(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase  ,return_tensors=__UpperCamelCase  ,**__UpperCamelCase    )
        lowercase_			:       List[str]									=			self.convert_tokens_to_ids(__UpperCamelCase    )
        lowercase_			:       Dict									=			tgt_lang_id
        return inputs
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = "en_XX"  ,__UpperCamelCase = None  ,__UpperCamelCase = "ro_RO"  ,**__UpperCamelCase  ,)			->   BatchEncoding:


        '''simple docstring'''


        lowercase_			:       List[str]									=			src_lang
        lowercase_			:       Optional[Any]									=			tgt_lang
        return super().prepare_seqaseq_batch(__UpperCamelCase  ,__UpperCamelCase  ,**__UpperCamelCase    )
   def     _UpperCAmelCase     (    self    )			->   Optional[int]:


        '''simple docstring'''


        return self.set_src_lang_special_tokens(self.src_lang    )
   def     _UpperCAmelCase     (    self    )			->   int:


        '''simple docstring'''


        return self.set_tgt_lang_special_tokens(self.tgt_lang    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   None:


        '''simple docstring'''


        lowercase_			:       Dict									=			self.convert_tokens_to_ids(__UpperCamelCase    )
        lowercase_			:       Tuple									=			[]
        lowercase_			:       Union[str, Any]									=			[self.eos_token_id, self.cur_lang_code]

        lowercase_			:       Union[str, Any]									=			self.convert_ids_to_tokens(self.prefix_tokens    )
        lowercase_			:       Any									=			self.convert_ids_to_tokens(self.suffix_tokens    )

        lowercase_			:       int									=			processors.TemplateProcessing(
            single=prefix_tokens_str + ['$A'] + suffix_tokens_str  ,pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str  ,special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str  ,self.prefix_tokens + self.suffix_tokens    )    )  ,)
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   None:


        '''simple docstring'''


        lowercase_			:       List[str]									=			self.convert_tokens_to_ids(__UpperCamelCase    )
        lowercase_			:       Any									=			[]
        lowercase_			:       List[Any]									=			[self.eos_token_id, self.cur_lang_code]

        lowercase_			:       Any									=			self.convert_ids_to_tokens(self.prefix_tokens    )
        lowercase_			:       List[Any]									=			self.convert_ids_to_tokens(self.suffix_tokens    )

        lowercase_			:       Optional[Any]									=			processors.TemplateProcessing(
            single=prefix_tokens_str + ['$A'] + suffix_tokens_str  ,pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str  ,special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str  ,self.prefix_tokens + self.suffix_tokens    )    )  ,)







   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = None    )			->   Tuple[str]:


        '''simple docstring'''


        if not self.can_save_slow_tokenizer:
             raise ValueError(
                 'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
                 'tokenizer.'    )

        if not os.path.isdir(__UpperCamelCase    ):
             logger.error(f'''Vocabulary path ({save_directory}) should be a directory.'''    )
             return
        lowercase_			:       Any									=			os.path.join(
            __UpperCamelCase  ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )

        if os.path.abspath(self.vocab_file    ) != os.path.abspath(__UpperCamelCase    ):
             copyfile(self.vocab_file  ,__UpperCamelCase    )

        return (out_vocab_file,)


"""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     lowercase__( ):
     print('Making key files...'   )
     make_key_files('rsa'  ,    10_24   )
     print('Key files generation successful.'   )



def     lowercase__( __SCREAMING_SNAKE_CASE							:  int   ):
     print('Generating prime p...'   )
     lowercase_			:       List[str]									=			rabinMiller.generate_large_prime(__SCREAMING_SNAKE_CASE   )
     print('Generating prime q...'   )
     lowercase_			:       int									=			rabinMiller.generate_large_prime(__SCREAMING_SNAKE_CASE   )
     lowercase_			:       Union[str, Any]									=			p * q

     print('Generating e that is relatively prime to (p - 1) * (q - 1)...'   )
     while True:
          lowercase_			:       str									=			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...'   )
     lowercase_			:       List[str]									=			cryptoMath.find_mod_inverse(__SCREAMING_SNAKE_CASE  ,    (p - 1) * (q - 1)   )

     lowercase_			:       Any									=			(n, e)
     lowercase_			:       int									=			(n, d)
     return (public_key, private_key)



def     lowercase__( __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()

     lowercase_							,						lowercase_			:       int									=			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()

