

from __future__ import annotations

_UpperCamelCase 			=		tuple[int, int, int]
_UpperCamelCase 			=		tuple[str, str, str]


# used alphabet --------------------------
# from string.ascii_uppercase
_UpperCamelCase 			=		"ABCDEFGHIJKLMNOPQRSTUVWXYZ"

# -------------------------- default selection --------------------------
# rotors --------------------------
_UpperCamelCase 			=		"EGZWVONAHDCLFQMSIPJBYUKXTR"
_UpperCamelCase 			=		"FOBHMDKEXQNRAULPGSJVTYICZW"
_UpperCamelCase 			=		"ZJXESIUQLHAVRMDOYGTNFWPBKC"
# reflector --------------------------
_UpperCamelCase 			=		{
    "A": "N",
    "N": "A",
    "B": "O",
    "O": "B",
    "C": "P",
    "P": "C",
    "D": "Q",
    "Q": "D",
    "E": "R",
    "R": "E",
    "F": "S",
    "S": "F",
    "G": "T",
    "T": "G",
    "H": "U",
    "U": "H",
    "I": "V",
    "V": "I",
    "J": "W",
    "W": "J",
    "K": "X",
    "X": "K",
    "L": "Y",
    "Y": "L",
    "M": "Z",
    "Z": "M",
}

# -------------------------- extra rotors --------------------------
_UpperCamelCase 			=		"RMDJXFUWGISLHVTCQNKYPBEZOA"
_UpperCamelCase 			=		"SGLCPQWZHKXAREONTFBVIYJUDM"
_UpperCamelCase 			=		"HVSICLTYKQUBXDWAJZOMFGPREN"
_UpperCamelCase 			=		"RZWQHFMVDBKICJLNTUXAGYPSOE"
_UpperCamelCase 			=		"LFKIJODBEGAMQPXVUHYSTCZRWN"
_UpperCamelCase 			=		"KOAEGVDHXPQZMLFTYWJNBRCIUS"







def 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__						):
      # Checks if there are 3 unique rotors

      if (unique_rotsel := len(set(lowercase__						)						)) < 3:
            __lowerCAmelCase					:						Optional[Any]					=					f"""Please use 3 unique rotors (not {unique_rotsel})"""
            raise Exception(lowercase__						)

      # Checks if rotor positions are valid
      __lowerCAmelCase,							__lowerCAmelCase,							__lowerCAmelCase					:						Any					=					rotpos
      if not 0 < rotorposa <= len(lowercase__						):
            __lowerCAmelCase					:						Optional[Any]					=					f"""First rotor position is not within range of 1..26 ({rotorposa}"""
            raise ValueError(lowercase__						)
      if not 0 < rotorposa <= len(lowercase__						):
            __lowerCAmelCase					:						int					=					f"""Second rotor position is not within range of 1..26 ({rotorposa})"""
            raise ValueError(lowercase__						)
      if not 0 < rotorposa <= len(lowercase__						):
            __lowerCAmelCase					:						Dict					=					f"""Third rotor position is not within range of 1..26 ({rotorposa})"""
            raise ValueError(lowercase__						)

      # Validates string and returns dict
      __lowerCAmelCase					:						List[Any]					=					_plugboard(lowercase__						)

      return rotpos, rotsel, pbdict







def 		_lowercase (     lowercase__						):

      # tests the input string if it
      # a) is type string
      # b) has even length (so pairs can be made)
      if not isinstance(lowercase__   ,	lowercase__						):
            __lowerCAmelCase					:						Union[str, Any]					=					f"""Plugboard setting isn't type string ({type(lowercase__						)})"""
            raise TypeError(lowercase__						)
      elif len(lowercase__						) % 2 != 0:
            __lowerCAmelCase					:						List[Any]					=					f"""Odd number of symbols ({len(lowercase__						)})"""
            raise Exception(lowercase__						)
      elif pbstring == "":
            return {}

      pbstring.replace(''' '''   ,	''''''						)

      # Checks if all characters are unique
      __lowerCAmelCase					:						Any					=					set()
      for i in pbstring:
            if i not in abc:
                  __lowerCAmelCase					:						Optional[int]					=					f"""'{i}' not in list of symbols"""
                  raise Exception(lowercase__						)
            elif i in tmppbl:
                  __lowerCAmelCase					:						int					=					f"""Duplicate symbol ({i})"""
                  raise Exception(lowercase__						)
            else:
                  tmppbl.add(lowercase__						)
      del tmppbl

      # Created the dictionary
      __lowerCAmelCase					:						Optional[int]					=					{}
      for j in range(0   ,	len(lowercase__						) - 1   ,	2						):
            __lowerCAmelCase					:						Tuple					=					pbstring[j + 1]
            __lowerCAmelCase					:						int					=					pbstring[j]

      return pb







def 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__ = (rotora, rotora, rotora)   ,	lowercase__ = ""   ,	):
      __lowerCAmelCase					:						List[Any]					=					text.upper()
      __lowerCAmelCase,							__lowerCAmelCase,							__lowerCAmelCase					:						Optional[int]					=					_validator(
          lowercase__   ,	lowercase__   ,	plugb.upper()						)

      __lowerCAmelCase,							__lowerCAmelCase,							__lowerCAmelCase					:						Optional[int]					=					rotor_position
      __lowerCAmelCase,							__lowerCAmelCase,							__lowerCAmelCase					:						List[str]					=					rotor_selection
      rotorposa -= 1
      rotorposa -= 1
      rotorposa -= 1

      __lowerCAmelCase					:						Optional[Any]					=					[]

      # encryption/decryption process --------------------------
      for symbol in text:
            if symbol in abc:
                  # 1st plugboard --------------------------
                  if symbol in plugboard:
                        __lowerCAmelCase					:						Any					=					plugboard[symbol]

                  # rotor ra --------------------------
                  __lowerCAmelCase					:						List[str]					=					abc.index(lowercase__						) + rotorposa
                  __lowerCAmelCase					:						Dict					=					rotora[index % len(lowercase__						)]

                  # rotor rb --------------------------
                  __lowerCAmelCase					:						Optional[int]					=					abc.index(lowercase__						) + rotorposa
                  __lowerCAmelCase					:						Optional[Any]					=					rotora[index % len(lowercase__						)]

                  # rotor rc --------------------------
                  __lowerCAmelCase					:						int					=					abc.index(lowercase__						) + rotorposa
                  __lowerCAmelCase					:						Any					=					rotora[index % len(lowercase__						)]

                  # reflector --------------------------
                  # this is the reason you don't need another machine to decipher

                  __lowerCAmelCase					:						Any					=					reflector[symbol]

                  # 2nd rotors
                  __lowerCAmelCase					:						int					=					abc[rotora.index(lowercase__						) - rotorposa]
                  __lowerCAmelCase					:						Dict					=					abc[rotora.index(lowercase__						) - rotorposa]
                  __lowerCAmelCase					:						Optional[Any]					=					abc[rotora.index(lowercase__						) - rotorposa]

                  # 2nd plugboard
                  if symbol in plugboard:
                        __lowerCAmelCase					:						str					=					plugboard[symbol]

                  # moves/resets rotor positions
                  rotorposa += 1
                  if rotorposa >= len(lowercase__						):
                        __lowerCAmelCase					:						List[Any]					=					0
                        rotorposa += 1
                  if rotorposa >= len(lowercase__						):
                        __lowerCAmelCase					:						List[str]					=					0
                        rotorposa += 1
                  if rotorposa >= len(lowercase__						):
                        __lowerCAmelCase					:						Optional[Any]					=					0

        # else:
        #    pass
        #    Error could be also raised
        #    raise ValueError(
        #       'Invalid symbol('+repr(symbol)+')')
            result.append(lowercase__						)

      return "".join(lowercase__						)


if __name__ == "__main__":
 _UpperCamelCase 			=		"This is my Python script that emulates the Enigma machine from WWII."
 _UpperCamelCase 			=		(1, 1, 1)
 _UpperCamelCase 			=		"pictures"
 _UpperCamelCase 			=		(rotora, rotora, rotora)
 _UpperCamelCase 			=		enigma(message, rotor_pos, rotor_sel, pb)

 print("Encrypted message:", en)
 print("Decrypted message:", enigma(en, rotor_pos, rotor_sel, pb))





import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging


if is_torch_available():
 import torch


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation


_UpperCamelCase 			=		logging.get_logger(__name__)
_UpperCamelCase 			=		{"vocab_file": "spiece.model"}

_UpperCamelCase 			=		{
    "vocab_file": {
        "AI-Sweden/gpt-sw3-126m": "https://huggingface.co/AI-Sweden/gpt-sw3-126m/resolve/main/spiece.model",
        "AI-Sweden/gpt-sw3-350m": "https://huggingface.co/AI-Sweden/gpt-sw3-350m/resolve/main/spiece.model",
        "AI-Sweden/gpt-sw3-1.6b": "https://huggingface.co/AI-Sweden/gpt-sw3-1.6b/resolve/main/spiece.model",
        "AI-Sweden/gpt-sw3-6.7b": "https://huggingface.co/AI-Sweden/gpt-sw3-6.7b/resolve/main/spiece.model",
        "AI-Sweden/gpt-sw3-20b": "https://huggingface.co/AI-Sweden/gpt-sw3-20b/resolve/main/spiece.model",
    }
}

_UpperCamelCase 			=		{
    "AI-Sweden/gpt-sw3-126m": 2048,
    "AI-Sweden/gpt-sw3-350m": 2048,
    "AI-Sweden/gpt-sw3-1.6b": 2048,
    "AI-Sweden/gpt-sw3-6.7b": 2048,
    "AI-Sweden/gpt-sw3-20b": 2048,
}







class   __lowercase      (_UpperCAmelCase ):
 _UpperCamelCase			  =  VOCAB_FILES_NAMES
 _UpperCamelCase			  =  PRETRAINED_VOCAB_FILES_MAP
 _UpperCamelCase			  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _UpperCamelCase			  =  ["""input_ids""", """attention_mask"""]
 def __init__(							self      ,							A_      ,							A_=False      ,							A_=False      ,							A_=False      ,							A_=None      ,							A_=None      ,							A_=None      ,							A_=None      ,							A_ = None      ,							**A_      ,							)					->None:



       '''simple docstring'''





       __lowerCAmelCase					:						Optional[int]					=					{} if sp_model_kwargs is None else sp_model_kwargs

       __lowerCAmelCase					:						int					=					kwargs.get('''name_or_path'''					)
       if name_or_path is None:
             logger.warning(
                 '''name_or_path not provided, will work for all GPTSw3 models except gpt-sw3-7b,'''
                 ''' you are testing the model, this can safely be ignored'''					)
             __lowerCAmelCase					:						Union[str, Any]					=					'''None'''

       # Default definitions for our 2 tokenizer versions, with None-checks to enable proper testing
       __lowerCAmelCase					:						str					=					'''<|endoftext|>''' if eos_token is None else eos_token
       __lowerCAmelCase					:						Any					=					'''<unk>''' if unk_token is None else unk_token
       if "gpt-sw3-7b" in name_or_path:
             __lowerCAmelCase					:						Dict					=					unk_token if pad_token is None else pad_token
             __lowerCAmelCase					:						int					=					eos_token if bos_token is None else bos_token
       else:
             __lowerCAmelCase					:						Optional[int]					=					'''<pad>''' if pad_token is None else pad_token
             __lowerCAmelCase					:						List[str]					=					'''<s>''' if bos_token is None else bos_token

       super().__init__(
           do_lower_case=A_      ,							remove_space=A_      ,							keep_accents=A_      ,							bos_token=A_      ,							eos_token=A_      ,							unk_token=A_      ,							pad_token=A_      ,							sp_model_kwargs=self.sp_model_kwargs      ,							**A_      ,							)

       __lowerCAmelCase					:						Union[str, Any]					=					do_lower_case
       __lowerCAmelCase					:						Union[str, Any]					=					remove_space
       __lowerCAmelCase					:						int					=					keep_accents
       __lowerCAmelCase					:						Union[str, Any]					=					vocab_file

       __lowerCAmelCase					:						int					=					spm.SentencePieceProcessor(**self.sp_model_kwargs					)
       self.sp_model.Load(A_					)

       # Used for whitespace normalization in input texts
       # fmt : off
       __lowerCAmelCase					:						List[Any]					=					{''' ''', ''' ''', ''' ''', ''' ''', ''' ''', '''　''', ''' ''', ''' ''', ''' ''', ''' ''', '''￼''', ''''''}
       # fmt : on

       # Regular expression to remove non-printing characters (e.g. some unicode control chars) in preprocessing
       __lowerCAmelCase					:						int					=					re.compile(
           f"""[{"".join(map(A_      ,							list(range(0      ,							9					)					) + list(range(11      ,							32					)					) + list(range(127      ,							160					)					) + [160, 173, 8203]					)					)}]"""					)
 def __getstate__(							self					)					->Dict:



       '''simple docstring'''





       __lowerCAmelCase					:						Union[str, Any]					=					self.__dict__.copy()
       __lowerCAmelCase					:						List[Any]					=					None
       return state
 def __setstate__(							self      ,							A_					)					->Tuple:



       '''simple docstring'''





       __lowerCAmelCase					:						int					=					d

       # for backward compatibility
       if not hasattr(self      ,							'''sp_model_kwargs'''					):
             __lowerCAmelCase					:						List[Any]					=					{}

       __lowerCAmelCase					:						List[str]					=					spm.SentencePieceProcessor(**self.sp_model_kwargs					)
       self.sp_model.Load(self.vocab_file					)
 @property
 # Copied from transformers.models.albert.tokenization_albert.AlbertTokenizer.vocab_size
 def 	UpperCamelCase__  (							self					)					->int:



       '''simple docstring'''





       return len(self.sp_model					)
 def 	UpperCamelCase__  (							self      ,							A_					)					->str:



       '''simple docstring'''





       __lowerCAmelCase					:						int					=					self.non_printing_characters_re.sub(''''''      ,							A_					)

       # Normalize whitespaces
       __lowerCAmelCase					:						List[str]					=					''''''.join([char if char not in self.whitespaces else ''' ''' for char in text]					)

       # NFC Unicode normalization
       __lowerCAmelCase					:						Tuple					=					unicodedata.normalize('''NFC'''      ,							A_					)
       return text
 def 	UpperCamelCase__  (							self      ,							A_      ,							**A_					)					->List[str]:



       '''simple docstring'''





       __lowerCAmelCase					:						int					=					self.preprocess_text(A_					)
       return self.sp_model.encode(A_      ,							out_type=A_					)
 def 	UpperCamelCase__  (							self      ,							A_					)					->int:



       '''simple docstring'''





       return self.sp_model.PieceToId(A_					)
 def 	UpperCamelCase__  (							self      ,							A_					)					->str:



       '''simple docstring'''





       return self.sp_model.IdToPiece(A_					)
 @staticmethod
 def 	UpperCamelCase__  (							A_					)					->str:



       '''simple docstring'''





       return out_string
 def 	UpperCamelCase__  (							self      ,							A_					)					->str:



       '''simple docstring'''





       __lowerCAmelCase					:						str					=					[]
       __lowerCAmelCase					:						Tuple					=					''''''
       __lowerCAmelCase					:						int					=					False
       for token in tokens:
             # make sure that special tokens are not decoded using sentencepiece model
             if token in self.all_special_tokens:
                   # TODO: Check if this is needed, as it ensures that decode(encode(doc)) != doc by adding extra whitespace in the decoded document
                   if not prev_is_special:
                         out_string += " "

                   out_string += self.sp_model.decode(A_					) + token
                   __lowerCAmelCase					:						Optional[Any]					=					True
                   __lowerCAmelCase					:						Optional[int]					=					[]
             else:
                   current_sub_tokens.append(A_					)
                   __lowerCAmelCase					:						str					=					False
       out_string += self.sp_model.decode(A_					)

       return out_string
 def 	UpperCamelCase__  (							self					)					->Dict[str, int]:



       '''simple docstring'''





       __lowerCAmelCase					:						str					=					{self.convert_ids_to_tokens(A_					): i for i in range(self.vocab_size					)}
       vocab.update(self.added_tokens_encoder					)
       return vocab
 def 	UpperCamelCase__  (							self      ,							A_      ,							A_ = None					)					->Tuple[str]:



       '''simple docstring'''





       if not os.path.isdir(A_					):
             logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""					)
             return
       __lowerCAmelCase					:						Any					=					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_					) and os.path.isfile(self.vocab_file					):
             copyfile(self.vocab_file      ,							A_					)
       elif not os.path.isfile(self.vocab_file					):
             with open(A_      ,							'''wb'''					) as fi:
                   __lowerCAmelCase					:						Dict					=					self.sp_model.serialized_model_proto()
                   fi.write(A_					)

       return (out_vocab_file,)
 def 	UpperCamelCase__  (							self      ,							A_      ,							A_ = False					)					->Union[List[int], List[List[int]], "torch.Tensor"]:



       '''simple docstring'''





       if isinstance(A_      ,							A_					):
             __lowerCAmelCase					:						Optional[Any]					=					self.preprocess_text(A_					)
             __lowerCAmelCase					:						Dict					=					self.sp_model.encode(A_					)
       else:
             __lowerCAmelCase					:						Dict					=					[self.preprocess_text(A_					) for t in text]
             __lowerCAmelCase					:						Optional[int]					=					self.sp_model.encode(A_					)

       if return_tensors is True or return_tensors == "pt":
             __lowerCAmelCase					:						Tuple					=					torch.tensor(A_					)

       return token_ids
 def 	UpperCamelCase__  (							self      ,							A_					)					->str:



       '''simple docstring'''





       return self.sp_model.decode(A_					)





 def 	UpperCamelCase__  (							self      ,							A_					)					->List[int]:



       '''simple docstring'''





       __lowerCAmelCase					:						int					=					[f"""User: {text}""" if is_user else f"""Bot: {text}""" for is_user, text in conversation.iter_texts()]
       __lowerCAmelCase					:						Any					=					(
           f"""{self.eos_token}{self.bos_token}""" + f"""{self.bos_token}""".join(A_					) + f"""{self.bos_token}Bot:"""
       )
       return self.encode(text=A_					)


