


'''simple docstring'''

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

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


if is_sentencepiece_available():
       from .tokenization_xlm_roberta import XLMRobertaTokenizer
else:
       __lowercase:		Dict    						=  None


__lowercase:		str    						=  logging.get_logger(__name__)

__lowercase:		Optional[int]    						=  {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

__lowercase:		Optional[int]    						=  {
    "vocab_file": {
        "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large-finetuned-conll02-dutch": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll02-spanish": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-english": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-german": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json",
        "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json",
        "xlm-roberta-large-finetuned-conll02-dutch": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json"
        ),
        "xlm-roberta-large-finetuned-conll02-spanish": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json"
        ),
        "xlm-roberta-large-finetuned-conll03-english": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json"
        ),
        "xlm-roberta-large-finetuned-conll03-german": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json"
        ),
    },
}

__lowercase:		Union[str, Any]    						=  {
    "xlm-roberta-base": 512,
    "xlm-roberta-large": 512,
    "xlm-roberta-large-finetuned-conll02-dutch": 512,
    "xlm-roberta-large-finetuned-conll02-spanish": 512,
    "xlm-roberta-large-finetuned-conll03-english": 512,
    "xlm-roberta-large-finetuned-conll03-german": 512,
}







class 			UpperCAmelCase			(							SCREAMING_SNAKE_CASE__):
 _lowerCamelCase			:       Union[str, Any]            =       VOCAB_FILES_NAMES
 _lowerCamelCase			:       Optional[int]            =       PRETRAINED_VOCAB_FILES_MAP
 _lowerCamelCase			:       str            =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCamelCase			:       List[str]            =       ['input_ids', 'attention_mask']
 _lowerCamelCase			:       Dict            =       XLMRobertaTokenizer

 def __init__(			self			:						List[str],       a_			:						List[str]=None,       a_			:						Any=None,       a_			:						Any="<s>",       a_			:						List[str]="</s>",       a_			:						int="</s>",       a_			:						Dict="<s>",       a_			:						Tuple="<unk>",       a_			:						List[str]="<pad>",       a_			:						str="<mask>",       **a_			:						str,       ):





    """simple docstring"""



    UpperCamelCase__			    =    AddedToken(a_,       lstrip=a_,       rstrip=a_       ) if isinstance(a_,       a_       ) else mask_token

    super().__init__(
        a_,       tokenizer_file=a_,       bos_token=a_,       eos_token=a_,       sep_token=a_,       cls_token=a_,       unk_token=a_,       pad_token=a_,       mask_token=a_,       **a_,       )

    UpperCamelCase__			    =    vocab_file
    UpperCamelCase__			    =    False if not self.vocab_file else True

 def 		lowercase_    (			self			:						int,       a_			:						List[int],       a_			:						Optional[List[int]] = None       ):





    """simple docstring"""



    if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
    UpperCamelCase__			    =    [self.cls_token_id]
    UpperCamelCase__			    =    [self.sep_token_id]
    return cls + token_ids_a + sep + sep + token_ids_a + sep

 def 		lowercase_    (			self			:						List[str],       a_			:						List[int],       a_			:						Optional[List[int]] = None       ):





    """simple docstring"""



    UpperCamelCase__			    =    [self.sep_token_id]
    UpperCamelCase__			    =    [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 		lowercase_    (			self			:						Dict,       a_			:						str,       a_			:						Optional[str] = None       ):





    """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(a_       ):
       logger.error(f'Vocabulary path ({save_directory}) should be a directory.'       )
       return
    UpperCamelCase__			    =    os.path.join(
        a_,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]       )

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

    return (out_vocab_file,)

'''simple docstring'''







from __future__ import annotations

import random
import string


class       lowerCAmelCase			:




		def __init__(					self       ,    UpperCamelCase = None   ):
								_SCREAMING_SNAKE_CASE					=			passcode or self.__passcode_creator()
								_SCREAMING_SNAKE_CASE					=			self.__make_key_list()
								_SCREAMING_SNAKE_CASE					=			self.__make_shift_key()




		def __str__(					self   ):
								return "".join(self.__passcode   )




		def      lowercase							(					self       ,    UpperCamelCase   ):
								for i in range(1       ,    len(UpperCamelCase   )       ,    2   ):
														iterlist[i] *= -1
								return iterlist




		def      lowercase							(					self   ):
								_SCREAMING_SNAKE_CASE					=			string.ascii_letters + string.digits
								_SCREAMING_SNAKE_CASE					=			[random.choice(UpperCamelCase   ) for _ in range(random.randint(10       ,    20   )   )]
								return password




		def      lowercase							(					self   ):
								_SCREAMING_SNAKE_CASE					=			(
								    string.ascii_letters + string.digits + string.punctuation + " \t\n"
								)

								_SCREAMING_SNAKE_CASE					=			[]

								# creates points known as breakpoints to break the key_list_options at those
								# points and pivot each substring
								_SCREAMING_SNAKE_CASE					=			sorted(set(self.__passcode   )   )
								_SCREAMING_SNAKE_CASE					=			[]

								# algorithm for creating a new shuffled list, keys_l, out of key_list_options
								for i in key_list_options:
														temp_list.extend(UpperCamelCase   )

														# checking breakpoints at which to pivot temporary sublist and add it into
														# keys_l
														if i in breakpoints or i == key_list_options[-1]:
																				keys_l.extend(temp_list[::-1]   )
																				temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
								return keys_l




		def      lowercase							(					self   ):
								_SCREAMING_SNAKE_CASE					=			sum(self.__neg_pos([ord(UpperCamelCase   ) for x in self.__passcode]   )   )
								return num if num > 0 else len(self.__passcode   )




		def      lowercase							(					self       ,    UpperCamelCase   ):
								_SCREAMING_SNAKE_CASE					=			""

								# decoding shift like Caesar cipher algorithm implementing negative shift or
								# reverse shift or left shift
								for i in encoded_message:
														_SCREAMING_SNAKE_CASE					=			self.__key_list.index(UpperCamelCase   )
														decoded_message += self.__key_list[
														    (position - self.__shift_key) % -len(self.__key_list   )
														]

								return decoded_message




		def      lowercase							(					self       ,    UpperCamelCase   ):
								_SCREAMING_SNAKE_CASE					=			""

								# encoding shift like Caesar cipher algorithm implementing positive shift or
								# forward shift or right shift
								for i in plaintext:
														_SCREAMING_SNAKE_CASE					=			self.__key_list.index(UpperCamelCase   )
														encoded_message += self.__key_list[
														    (position + self.__shift_key) % len(self.__key_list   )
														]

								return encoded_message



def       _a		(						_SCREAMING_SNAKE_CASE		: str = "Hello, this is a modified Caesar cipher"	):
						_SCREAMING_SNAKE_CASE					=			ShuffledShiftCipher()
						return cipa.decrypt(cipa.encrypt(_SCREAMING_SNAKE_CASE	)	)


if __name__ == "__main__":
						import doctest

						doctest.testmod()