


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


UpperCAmelCase    =					"""▁"""

UpperCAmelCase    =					{"""vocab_file""": """spiece.model"""}

UpperCAmelCase    =					{
    """vocab_file""": {"""google/pegasus-xsum""": """https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model"""}
}

UpperCAmelCase    =					{
    """google/pegasus-xsum""": 512,
}


UpperCAmelCase    =					logging.get_logger(__name__)







class lowerCAmelCase_		(				lowerCamelCase__ ):

 '''simple docstring'''

 __snake_case				=						VOCAB_FILES_NAMES

 __snake_case				=						VOCAB_FILES_NAMES
 __snake_case				=						PRETRAINED_VOCAB_FILES_MAP
 __snake_case				=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __snake_case				=						["input_ids", "attention_mask"]



 def __init__(			self	,   _UpperCAmelCase	,   _UpperCAmelCase="<pad>"	,   _UpperCAmelCase="</s>"	,   _UpperCAmelCase="<unk>"	,   _UpperCAmelCase="<mask_2>"	,   _UpperCAmelCase="<mask_1>"	,   _UpperCAmelCase=None	,   _UpperCAmelCase=1_03	,   _UpperCAmelCase = None	,   **_UpperCAmelCase	,   ):
       snake_case_ =   offset
       if additional_special_tokens is not None:
             if not isinstance(_UpperCAmelCase	,   _UpperCAmelCase      ):
                   raise TypeError(
                       F'''additional_special_tokens should be of type {type(_UpperCAmelCase      )}, but is'''
                       F''' {type(_UpperCAmelCase      )}'''      )

             snake_case_ =   (
                 ([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(_UpperCAmelCase      )	,   self.offset - 1      )
             ]

             if len(set(_UpperCAmelCase      )      ) != len(_UpperCAmelCase      ):
                   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}.'''      )
             snake_case_ =   additional_special_tokens_extended
       else:
             snake_case_ =   [mask_token_sent] if mask_token_sent is not None else []
             additional_special_tokens += [F'''<unk_{i}>''' for i in range(2	,   self.offset      )]

       snake_case_ =   {} if sp_model_kwargs is None else sp_model_kwargs

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

       # add special tokens to encoder dict
       snake_case_ =   {
           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      )}      )

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



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



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   {self.convert_ids_to_tokens(_UpperCAmelCase      ): i for i in range(self.vocab_size      )}
       vocab.update(self.added_tokens_encoder      )
       return vocab



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



 def __setstate__(			self	,   _UpperCAmelCase      ):
       snake_case_ =   d

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

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



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



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



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



 def 		UpperCamelCase__  (			self	,   _UpperCAmelCase      ):
       snake_case_ =   []
       snake_case_ =   ''''''
       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(_UpperCAmelCase      ) + token
                   snake_case_ =   []
             else:
                   current_sub_tokens.append(_UpperCAmelCase      )
       out_string += self.sp_model.decode(_UpperCAmelCase      )
       return out_string.strip()



 def 		UpperCamelCase__  (			self	,   _UpperCAmelCase=False      ):
       return 1



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



 def 		UpperCamelCase__  (			self	,   _UpperCAmelCase	,   _UpperCAmelCase=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 		UpperCamelCase__  (			self	,   _UpperCAmelCase	,   _UpperCAmelCase = None      ):
       if not os.path.isdir(_UpperCAmelCase      ):
             logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
             return
       snake_case_ =   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      ) and os.path.isfile(self.vocab_file      ):
             copyfile(self.vocab_file	,   _UpperCAmelCase      )
       elif not os.path.isfile(self.vocab_file      ):
             with open(_UpperCAmelCase	,   '''wb'''      ) as fi:
                   snake_case_ =   self.sp_model.serialized_model_proto()
                   fi.write(_UpperCAmelCase      )

       return (out_vocab_file,)



def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						int:




      """simple docstring"""

      return int((input_a, input_a).count(0      ) == 0      )






def  __lowerCAmelCase					()->						None:




      """simple docstring"""

      assert and_gate(0      ,      0      ) == 0
      assert and_gate(0      ,      1      ) == 0
      assert and_gate(1      ,      0      ) == 0
      assert and_gate(1      ,      1      ) == 1


if __name__ == "__main__":
   test_and_gate()
   print(and_gate(1, 0))
   print(and_gate(0, 0))
   print(and_gate(0, 1))
   print(and_gate(1, 1))