

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


a_    :						Any    		=      "▁"

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

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

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


a_    :						Optional[int]    		=      logging.get_logger(__name__)




class      UpperCamelCase (     SCREAMING_SNAKE_CASE   ):
    __UpperCamelCase         =VOCAB_FILES_NAMES

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

    def __init__(			self :      Optional[int]							,    snake_case__ :      Optional[Any]							,    snake_case__ :      List[str]="<pad>"							,    snake_case__ :      Union[str, Any]="</s>"							,    snake_case__ :      int="<unk>"							,    snake_case__ :      str="<mask_2>"							,    snake_case__ :      Tuple="<mask_1>"							,    snake_case__ :      Tuple=None							,    snake_case__ :      Dict=1_0_3							,    snake_case__ :      Optional[Dict[str, Any]] = None							,    **snake_case__ :      Dict							,    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			offset
     if additional_special_tokens is not None:
      if not isinstance(snake_case__							,    snake_case__    ):
       raise TypeError(
           F"""additional_special_tokens should be of type {type(snake_case__    )}, but is"""
           F""" {type(snake_case__    )}"""    )

      SCREAMING_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(snake_case__    )							,    self.offset - 1    )
      ]

      if len(set(snake_case__    )    ) != len(snake_case__    ):
       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}."""    )
      SCREAMING_SNAKE_CASE								=			additional_special_tokens_extended
     else:
      SCREAMING_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    )]

     SCREAMING_SNAKE_CASE								=			{} if sp_model_kwargs is None else sp_model_kwargs

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

     # add special tokens to encoder dict
     SCREAMING_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    )}    )

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

    @property
    def UpperCamelCase			(			self :      List[str]    ):

     """simple docstring"""






     return len(self.sp_model    ) + self.offset

    def UpperCamelCase			(			self :      List[str]    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			{self.convert_ids_to_tokens(snake_case__    ): i for i in range(self.vocab_size    )}
     vocab.update(self.added_tokens_encoder    )
     return vocab

    def __getstate__(			self :      Union[str, Any]    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			self.__dict__.copy()
     SCREAMING_SNAKE_CASE								=			None
     return state

    def __setstate__(			self :      str							,    snake_case__ :      List[Any]    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			d

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

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

    def UpperCamelCase			(			self :      Any							,    snake_case__ :      str    ):

     """simple docstring"""






     return self.sp_model.encode(snake_case__							,    out_type=snake_case__    )

    def UpperCamelCase			(			self :      Union[str, Any]							,    snake_case__ :      str    ):

     """simple docstring"""






     if token in self.decoder:
      return self.decoder[token]
     elif token in self.added_tokens_decoder:
      return self.added_tokens_decoder[token]
     SCREAMING_SNAKE_CASE								=			self.sp_model.piece_to_id(snake_case__    )
     return sp_id + self.offset

    def UpperCamelCase			(			self :      Optional[int]							,    snake_case__ :      int    ):

     """simple docstring"""






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

    def UpperCamelCase			(			self :      Tuple							,    snake_case__ :      str    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			[]
     SCREAMING_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(snake_case__    ) + token
       SCREAMING_SNAKE_CASE								=			[]
      else:
       current_sub_tokens.append(snake_case__    )
     out_string += self.sp_model.decode(snake_case__    )
     return out_string.strip()

    def UpperCamelCase			(			self :      Any							,    snake_case__ :      Any=False    ):

     """simple docstring"""






     return 1

    def UpperCamelCase			(			self :      List[Any]							,    snake_case__ :      List[str]    ):

     """simple docstring"""






     SCREAMING_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 :      Union[str, Any]							,    snake_case__ :      List							,    snake_case__ :      Optional[List] = None							,    snake_case__ :      bool = False    ):

     """simple docstring"""






     if already_has_special_tokens:
      return self._special_token_mask(snake_case__    )
     elif token_ids_a is None:
      return self._special_token_mask(snake_case__    ) + [1]
     else:
      return self._special_token_mask(token_ids_a + token_ids_a    ) + [1]

    def UpperCamelCase			(			self :      int							,    snake_case__ :      Tuple							,    snake_case__ :      Optional[int]=None    ):

     """simple docstring"""






     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 :      Tuple							,    snake_case__ :      str							,    snake_case__ :      Optional[str] = None    ):

     """simple docstring"""






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

     if os.path.abspath(self.vocab_file    ) != os.path.abspath(snake_case__    ) and os.path.isfile(self.vocab_file    ):
      copyfile(self.vocab_file							,    snake_case__    )
     elif not os.path.isfile(self.vocab_file    ):
      with open(snake_case__							,    'wb'    ) as fi:
       SCREAMING_SNAKE_CASE								=			self.sp_model.serialized_model_proto()
       fi.write(snake_case__    )

     return (out_vocab_file,)




from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer


a_    :						Optional[Any]    		=      logging.get_logger(__name__)

a_    :						Optional[Any]    		=      {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

a_    :						Any    		=      {
    "vocab_file": {
        "allegro/herbert-base-cased": "https://huggingface.co/allegro/herbert-base-cased/resolve/main/vocab.json"
    },
    "merges_file": {
        "allegro/herbert-base-cased": "https://huggingface.co/allegro/herbert-base-cased/resolve/main/merges.txt"
    },
}

a_    :						Union[str, Any]    		=      {"allegro/herbert-base-cased": 514}
a_    :						List[Any]    		=      {}




class      UpperCamelCase (     SCREAMING_SNAKE_CASE   ):
    __UpperCamelCase         =VOCAB_FILES_NAMES
    __UpperCamelCase         =PRETRAINED_VOCAB_FILES_MAP
    __UpperCamelCase         =PRETRAINED_INIT_CONFIGURATION
    __UpperCamelCase         =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __UpperCamelCase         =HerbertTokenizer

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

     """simple docstring"""






     super().__init__(
         snake_case__							,    snake_case__							,    tokenizer_file=snake_case__							,    cls_token=snake_case__							,    unk_token=snake_case__							,    pad_token=snake_case__							,    mask_token=snake_case__							,    sep_token=snake_case__							,    **snake_case__							,    )

    def UpperCamelCase			(			self :      Union[str, Any]							,    snake_case__ :      List[int]							,    snake_case__ :      Optional[List[int]] = None    ):

     """simple docstring"""






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

     return cls + token_ids_a + sep + token_ids_a + sep

    def UpperCamelCase			(			self :      Optional[Any]							,    snake_case__ :      List[int]							,    snake_case__ :      Optional[List[int]] = None							,    snake_case__ :      bool = False    ):

     """simple docstring"""






     if already_has_special_tokens:
      return super().get_special_tokens_mask(
          token_ids_a=snake_case__							,    token_ids_a=snake_case__							,    already_has_special_tokens=snake_case__    )

     if token_ids_a is None:
      return [1] + ([0] * len(snake_case__    )) + [1]
     return [1] + ([0] * len(snake_case__    )) + [1] + ([0] * len(snake_case__    )) + [1]

    def UpperCamelCase			(			self :      Optional[Any]							,    snake_case__ :      List[int]							,    snake_case__ :      Optional[List[int]] = None    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			[self.sep_token_id]
     SCREAMING_SNAKE_CASE								=			[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    ) * [0] + len(token_ids_a + sep    ) * [1]




    def UpperCamelCase			(			self :      Tuple							,    snake_case__ :      str							,    snake_case__ :      Optional[str] = None    ):

     """simple docstring"""






     SCREAMING_SNAKE_CASE								=			self._tokenizer.model.save(snake_case__							,    name=snake_case__    )
     return tuple(snake_case__    )

