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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowercase__		:str   =    "▁"

lowercase__		:List[str]   =    {"vocab_file": "spiece.model"}

lowercase__		:List[Any]   =    {
    "vocab_file": {"google/pegasus-xsum": "https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model"}
}

lowercase__		:Optional[int]   =    {
    "google/pegasus-xsum": 512,
}


lowercase__		:str   =    logging.get_logger(__name__)







class 				lowercase		(					SCREAMING_SNAKE_CASE__		):
							lowercase_       :       Dict       					=VOCAB_FILES_NAMES

							lowercase_       :       Optional[Any]       					=VOCAB_FILES_NAMES
							lowercase_       :       List[str]       					=PRETRAINED_VOCAB_FILES_MAP
							lowercase_       :       List[Any]       					=PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_       :       List[str]       					=['''input_ids''', '''attention_mask''']




							def __init__(				self   ,A__   ,A__="<pad>"   ,A__="</s>"   ,A__="<unk>"   ,A__="<mask_2>"   ,A__="<mask_1>"   ,A__=None   ,A__=1_0_3   ,A__ = None   ,**A__   ,):
												lowercase							=						offset
												if additional_special_tokens is not None:
																	if not isinstance(A__   ,A__):
																						raise TypeError(
																						    f'additional_special_tokens should be of type {type(A__)}, but is'
																						    f' {type(A__)}')

																	lowercase							=						(
																	    ([mask_token_sent] + additional_special_tokens)
																	    if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
																	    else additional_special_tokens
																	)
																	# fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
																	additional_special_tokens_extended += [
																	    f'<unk_{i}>' for i in range(len(A__)   ,self.offset - 1)
																	]

																	if len(set(A__)) != len(A__):
																						raise ValueError(
																						    '''Please make sure that the provided additional_special_tokens do not contain an incorrectly'''
																						    f' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.')
																	lowercase							=						additional_special_tokens_extended
												else:
																	lowercase							=						[mask_token_sent] if mask_token_sent is not None else []
																	additional_special_tokens += [f'<unk_{i}>' for i in range(2   ,self.offset)]

												lowercase							=						{} if sp_model_kwargs is None else sp_model_kwargs

												super().__init__(
												    eos_token=A__   ,unk_token=A__   ,mask_token=A__   ,pad_token=A__   ,mask_token_sent=A__   ,offset=A__   ,additional_special_tokens=A__   ,sp_model_kwargs=self.sp_model_kwargs   ,**A__   ,)
												lowercase							=						mask_token_sent
												lowercase							=						vocab_file
												lowercase							=						spm.SentencePieceProcessor(**self.sp_model_kwargs)
												self.sp_model.Load(A__)

												# add special tokens to encoder dict
												lowercase							=						{
												    0: self.pad_token,
												    1: self.eos_token,
												}

												if self.mask_token_sent is not None:
																	self.encoder.update(
																	    {
																	        2: self.mask_token_sent,
																	        3: self.mask_token,
																	    })

												if self.offset > 0:
																	# entries 2-104 are only used for pretraining and called <mask_1>, <mask_2>, unk_2, ...unk_102
																	# mask_token_sent is already added to list -> so start at 1
																	self.encoder.update({i + 3: additional_special_tokens[i] for i in range(1   ,self.offset - 1)})

												lowercase							=						{v: k for k, v in self.encoder.items()}




							@property
							def  A__      (				self):
												return len(self.sp_model) + self.offset




							def  A__      (				self):
												lowercase							=						{self.convert_ids_to_tokens(A__): i for i in range(self.vocab_size)}
												vocab.update(self.added_tokens_encoder)
												return vocab




							def __getstate__(				self):
												lowercase							=						self.__dict__.copy()
												lowercase							=						None
												return state




							def __setstate__(				self   ,A__):
												lowercase							=						d

												# for backward compatibility
												if not hasattr(self   ,'''sp_model_kwargs'''):
																	lowercase							=						{}

												lowercase							=						spm.SentencePieceProcessor(**self.sp_model_kwargs)
												self.sp_model.Load(self.vocab_file)




							def  A__      (				self   ,A__):
												return self.sp_model.encode(A__   ,out_type=A__)




							def  A__      (				self   ,A__):
												if token in self.decoder:
																	return self.decoder[token]
												elif token in self.added_tokens_decoder:
																	return self.added_tokens_decoder[token]
												lowercase							=						self.sp_model.piece_to_id(A__)
												return sp_id + self.offset




							def  A__      (				self   ,A__):
												if index in self.encoder:
																	return self.encoder[index]
												elif index in self.added_tokens_encoder:
																	return self.added_tokens_encoder[index]
												else:
																	lowercase							=						self.sp_model.IdToPiece(index - self.offset)
												return token




							def  A__      (				self   ,A__):
												lowercase							=						[]
												lowercase							=						''''''
												for token in tokens:
																	# make sure that special tokens are not decoded using sentencepiece model
																	if token in self.all_special_tokens:
																						out_string += self.sp_model.decode(A__) + token
																						lowercase							=						[]
																	else:
																						current_sub_tokens.append(A__)
												out_string += self.sp_model.decode(A__)
												return out_string.strip()




							def  A__      (				self   ,A__=False):
												return 1




							def  A__      (				self   ,A__):
												lowercase							=						set(self.all_special_ids)  # call it once instead of inside list comp
												all_special_ids.remove(self.unk_token_id)  # <unk> is only sometimes special

												return [1 if x in all_special_ids else 0 for x in seq]




							def  A__      (				self   ,A__   ,A__ = None   ,A__ = False):
												if already_has_special_tokens:
																	return self._special_token_mask(A__)
												elif token_ids_a is None:
																	return self._special_token_mask(A__) + [1]
												else:
																	return self._special_token_mask(token_ids_a + token_ids_a) + [1]




							def  A__      (				self   ,A__   ,A__=None):
												if token_ids_a is None:
																	return token_ids_a + [self.eos_token_id]
												# We don't expect to process pairs, but leave the pair logic for API consistency
												return token_ids_a + token_ids_a + [self.eos_token_id]





							def  A__      (				self   ,A__   ,A__ = None):
												if not os.path.isdir(A__):
																	logger.error(f'Vocabulary path ({save_directory}) should be a directory')
																	return
												lowercase							=						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:
																						lowercase							=						self.sp_model.serialized_model_proto()
																						fi.write(A__)

												return (out_vocab_file,)








"""simple docstring"""





import math


def    _snake_case  (  ):
      lowerCAmelCase    :		Union[str, Any]				=      input('''Enter message: '''	)
      lowerCAmelCase    :		Optional[int]				=      int(input(f'''Enter key [2-{len(_snake_case	) - 1}]: '''	)	)
      lowerCAmelCase    :		str				=      input('''Encryption/Decryption [e/d]: '''	)

      if mode.lower().startswith('''e'''	):
            lowerCAmelCase    :		Any				=      encrypt_message(_snake_case       ,      _snake_case	)
      elif mode.lower().startswith('''d'''	):
            lowerCAmelCase    :		Union[str, Any]				=      decrypt_message(_snake_case       ,      _snake_case	)

      # Append pipe symbol (vertical bar) to identify spaces at the end.
      print(f'''Output:\n{text + "|"}'''	)


def    _snake_case  (  _snake_case :	int       ,      _snake_case :	str	):
      lowerCAmelCase    :		Optional[Any]				=      [''''''] * key
      for col in range(_snake_case	):
            lowerCAmelCase    :		Optional[Any]				=      col
            while pointer < len(_snake_case	):
                  cipher_text[col] += message[pointer]
                  pointer += key
      return "".join(_snake_case	)


def    _snake_case  (  _snake_case :	int       ,      _snake_case :	str	):
      lowerCAmelCase    :		Union[str, Any]				=      math.ceil(len(_snake_case	) / key	)
      lowerCAmelCase    :		str				=      key
      lowerCAmelCase    :		Any				=      (num_cols * num_rows) - len(_snake_case	)
      lowerCAmelCase    :		Dict				=      [''''''] * num_cols
      lowerCAmelCase    :		int				=      0
      lowerCAmelCase    :		int				=      0

      for symbol in message:
            plain_text[col] += symbol
            col += 1

            if (
                (col == num_cols)
                or (col == num_cols - 1)
                and (row >= num_rows - num_shaded_boxes)
            ):
                  lowerCAmelCase    :		int				=      0
                  row += 1

      return "".join(_snake_case	)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 main()


