






"""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


UpperCamelCase_	:				List[str]										= logging.get_logger(__name__)

UpperCamelCase_	:				List[Any]										= {"""vocab_file""": """spiece.model"""}

UpperCamelCase_	:				Any										= {
    """vocab_file""": {
        """bert_for_seq_generation""": (
            """https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model"""
        ),
    }
}

UpperCamelCase_	:				str										= {"""bert_for_seq_generation""": 512}


class      _lowercase (     lowerCAmelCase						):
      _a   :     Dict								=   VOCAB_FILES_NAMES
      _a   :     str								=   PRETRAINED_VOCAB_FILES_MAP
      _a   :     Union[str, Any]								=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _a   :     List[int]								=   []
      _a   :     List[Any]								=   ['''input_ids''', '''attention_mask''']


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





            """simple docstring"""







            __snake_case      :    Tuple  			={} if sp_model_kwargs is None else sp_model_kwargs

            # Add extra_ids to the special token list
            super().__init__(
                bos_token=a							,   eos_token=a							,   unk_token=a							,   pad_token=a							,   sep_token=a							,   sp_model_kwargs=self.sp_model_kwargs							,   **a							,   )

            __snake_case      :    str  			=vocab_file

            __snake_case      :    Dict  			=spm.SentencePieceProcessor(**self.sp_model_kwargs						)
            self.sp_model.Load(a						)


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





            """simple docstring"""







            return self.sp_model.get_piece_size()


      def _UpperCamelCase						(    self				:	Tuple						):





            """simple docstring"""







            __snake_case      :    List[str]  			={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				:	Optional[int]						):





            """simple docstring"""







            __snake_case      :    Optional[Any]  			=self.__dict__.copy()
            __snake_case      :    Optional[Any]  			=None
            return state


      def __setstate__(    self				:	Any							,   a				:	Optional[Any]						):





            """simple docstring"""







            __snake_case      :    int  			=d

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

            __snake_case      :    Dict  			=spm.SentencePieceProcessor(**self.sp_model_kwargs						)
            self.sp_model.Load(self.vocab_file						)


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





            """simple docstring"""







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


      def _UpperCamelCase						(    self				:	str							,   a				:	Dict						):





            """simple docstring"""







            return self.sp_model.piece_to_id(a						)


      def _UpperCamelCase						(    self				:	Dict							,   a				:	List[Any]						):





            """simple docstring"""







            __snake_case      :    Optional[int]  			=self.sp_model.IdToPiece(a						)
            return token


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





            """simple docstring"""







            __snake_case      :    Any  			=[]
            __snake_case      :    Union[str, Any]  			=''''''
            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
                        __snake_case      :    List[str]  			=[]
                  else:
                        current_sub_tokens.append(a						)
            out_string += self.sp_model.decode(a						)
            return out_string.strip()







      def _UpperCamelCase						(    self				:	Union[str, Any]							,   a				:	str							,   a				:	Optional[str] = None						):





            """simple docstring"""







            if not os.path.isdir(a						):
                  logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''						)
                  return
            __snake_case      :    Optional[int]  			=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:
                        __snake_case      :    Dict  			=self.sp_model.serialized_model_proto()
                        fi.write(a						)

            return (out_vocab_file,)










"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


UpperCamelCase_	:				str										= {"""processing_layoutxlm""": ["""LayoutXLMProcessor"""]}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase_	:				Union[str, Any]										= ["""LayoutXLMTokenizer"""]

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase_	:				Optional[int]										= ["""LayoutXLMTokenizerFast"""]

if TYPE_CHECKING:
    from .processing_layoutxlm import LayoutXLMProcessor

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_layoutxlm import LayoutXLMTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_layoutxlm_fast import LayoutXLMTokenizerFast

else:
    import sys

    UpperCamelCase_	:				List[Any]										= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


