'''simple docstring'''




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


snake_case	=      logging.get_logger(__name__)

snake_case	=      '▁'

snake_case	=      {'vocab_file': 'sentencepiece.bpe.model'}

snake_case	=      {
    'vocab_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model',
    }
}

snake_case	=      {
    'facebook/xglm-564M': 2048,
}





class 							SCREAMING_SNAKE_CASE (					UpperCAmelCase_			):
  """simple docstring"""







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



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


        """simple docstring"""



        _lowerCAmelCase		 = {} if sp_model_kwargs is None else sp_model_kwargs

        # Compatibility with the original tokenizer
        _lowerCAmelCase		 = 7
        _lowerCAmelCase		 = [F"<madeupword{i}>" for i in range(self.num_madeup_words       )]

        _lowerCAmelCase		 = kwargs.get('additional_special_tokens'       ,       []       )
        kwargs["additional_special_tokens"] += [
            word for word in madeup_words if word not in kwargs["additional_special_tokens"]
        ]

        super().__init__(
            bos_token=__a       ,       eos_token=__a       ,       unk_token=__a       ,       sep_token=__a       ,       cls_token=__a       ,       pad_token=__a       ,       sp_model_kwargs=self.sp_model_kwargs       ,       **__a       ,       )

        _lowerCAmelCase		 = spm.SentencePieceProcessor(**self.sp_model_kwargs       )
        self.sp_model.Load(str(__a       )       )
        _lowerCAmelCase		 = vocab_file

        # Original fairseq vocab and spm vocab must be "aligned":
        # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
        # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
        # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
        # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

        # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
        _lowerCAmelCase		 = 1

        # Mimic fairseq token-to-id alignment for the first 4 token
        _lowerCAmelCase		 = {'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

        _lowerCAmelCase		 = len(self.sp_model       )
        _lowerCAmelCase		 = {F"<madeupword{i}>": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words       )}
        self.fairseq_tokens_to_ids.update(__a       )

        _lowerCAmelCase		 = {v: k for k, v in self.fairseq_tokens_to_ids.items()}



  def __getstate__(	self :       Optional[int]       ):


        """simple docstring"""



        _lowerCAmelCase		 = self.__dict__.copy()
        _lowerCAmelCase		 = None
        _lowerCAmelCase		 = self.sp_model.serialized_model_proto()
        return state



  def __setstate__(	self :       Optional[int]       ,       __lowerCAmelCase :       Optional[int]       ):


        """simple docstring"""



        _lowerCAmelCase		 = d

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

        _lowerCAmelCase		 = spm.SentencePieceProcessor(**self.sp_model_kwargs       )
        self.sp_model.LoadFromSerializedProto(self.sp_model_proto       )



  def 	a (	self :       Optional[int]       ,       __lowerCAmelCase :       str       ,       __lowerCAmelCase :       Optional[Any] = None       ):


        """simple docstring"""



        if token_ids_a is None:
              return [self.sep_token_id] + token_ids_a
        _lowerCAmelCase		 = [self.sep_token_id]
        return sep + token_ids_a + sep + sep + token_ids_a



  def 	a (	self :       Union[str, Any]       ,       __lowerCAmelCase :       Union[str, Any]       ,       __lowerCAmelCase :       List[Any] = None       ,       __lowerCAmelCase :       Optional[int] = False       ):


        """simple docstring"""



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

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



  def 	a (	self :       str       ,       __lowerCAmelCase :       List[str]       ,       __lowerCAmelCase :       Tuple = None       ):


        """simple docstring"""



        _lowerCAmelCase		 = [self.sep_token_id]

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



  @property
  def 	a (	self :       Dict       ):


        """simple docstring"""



        return len(self.sp_model       ) + self.fairseq_offset + self.num_madeup_words



  def 	a (	self :       Optional[int]       ):


        """simple docstring"""



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



  def 	a (	self :       Optional[int]       ,       __lowerCAmelCase :       Optional[Any]       ):


        """simple docstring"""



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



  def 	a (	self :       Union[str, Any]       ,       __lowerCAmelCase :       int       ):


        """simple docstring"""



        if token in self.fairseq_tokens_to_ids:
              return self.fairseq_tokens_to_ids[token]
        _lowerCAmelCase		 = self.sp_model.PieceToId(__a       )

        # Need to return unknown token if the SP model returned 0
        return spm_id + self.fairseq_offset if spm_id else self.unk_token_id



  def 	a (	self :       Any       ,       __lowerCAmelCase :       Any       ):


        """simple docstring"""



        if index in self.fairseq_ids_to_tokens:
              return self.fairseq_ids_to_tokens[index]
        return self.sp_model.IdToPiece(index - self.fairseq_offset       )



  def 	a (	self :       Dict       ,       __lowerCAmelCase :       Union[str, Any]       ):


        """simple docstring"""



        _lowerCAmelCase		 = ''.join(__a       ).replace(__a       ,       ' '       ).strip()
        return out_string



  def 	a (	self :       Optional[int]       ,       __lowerCAmelCase :       Any       ,       __lowerCAmelCase :       Optional[int] = None       ):


        """simple docstring"""



        if not os.path.isdir(__a       ):
              logger.error(F"Vocabulary path ({save_directory}) should be a directory"       )
              return
        _lowerCAmelCase		 = 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		 = self.sp_model.serialized_model_proto()
                    fi.write(__a       )

        return (out_vocab_file,)










from ..utils import DummyObject, requires_backends





class  lowerCamelCase__	(    metaclass=UpperCAmelCase_):
     """simple docstring"""



     _A      =      ['transformers', 'torch', 'note_seq']







     def __init__(self					,      *__a					,      **__a     ):






           '''simple docstring'''



           requires_backends(self					,      ["transformers", "torch", "note_seq"]     )







     @classmethod
     def     _a   (cls					,      *__a					,      **__a     ):






           '''simple docstring'''



           requires_backends(cls					,      ["transformers", "torch", "note_seq"]     )







     @classmethod
     def     _a   (cls					,      *__a					,      **__a     ):






           '''simple docstring'''



           requires_backends(cls					,      ["transformers", "torch", "note_seq"]     )