



"""simple docstring"""
import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


__SCREAMING_SNAKE_CASE     :  Any										=					logging.get_logger(__name__)


class 							lowerCamelCase_(      A__			):





					'''simple docstring'''



					def __init__(			self ,				*lowerCamelCase__ ,				**lowerCamelCase__      ):
									warnings.warn(
									    '''The class LayoutLMv3FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
									    ''' Please use LayoutLMv3ImageProcessor instead.''' ,				lowerCamelCase__ ,				)
									super().__init__(*lowerCamelCase__ ,				**lowerCamelCase__      )








"""simple docstring"""







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

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_xglm import XGLMTokenizer
else:
  _UpperCamelCase     			=  None


_UpperCamelCase     			=  logging.get_logger(__name__)

_UpperCamelCase     			=  {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

_UpperCamelCase     			=  {
    """vocab_file""": {
        """facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model""",
    },
    """tokenizer_file""": {
        """facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json""",
    },
}

_UpperCamelCase     			=  {
    """facebook/xglm-564M""": 2048,
}







class 					lowerCamelCase__					(       snake_case ):
    SCREAMING_SNAKE_CASE		=			VOCAB_FILES_NAMES
    SCREAMING_SNAKE_CASE		=			PRETRAINED_VOCAB_FILES_MAP
    SCREAMING_SNAKE_CASE		=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    SCREAMING_SNAKE_CASE		=			['''input_ids''', '''attention_mask''']
    SCREAMING_SNAKE_CASE		=			XGLMTokenizer






    def __init__( self	,A=None	,A=None	,A="<s>"	,A="</s>"	,A="</s>"	,A="<s>"	,A="<unk>"	,A="<pad>"	,**A	,):
          # Compatibility with the original tokenizer
          UpperCAmelCase							=       7
          UpperCAmelCase							=       [F'''<madeupword{i}>''' for i in range(self.num_madeup_words					)]

          UpperCAmelCase							=       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__(
              A	,tokenizer_file=A	,bos_token=A	,eos_token=A	,sep_token=A	,cls_token=A	,unk_token=A	,pad_token=A	,**A	,)

          UpperCAmelCase							=       vocab_file
          UpperCAmelCase							=       False if not self.vocab_file else True






    def 				_UpperCamelCase							( self	,A	,A = None					):

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






    def 				_UpperCamelCase							( self	,A	,A = None					):
          UpperCAmelCase							=       [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]






    def 				_UpperCamelCase							( self	,A	,A = None					):
          if not self.can_save_slow_tokenizer:
                raise ValueError(
                    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
                    """tokenizer."""					)

          if not os.path.isdir(A					):
                logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''					)
                return
          UpperCAmelCase							=       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					):
                copyfile(self.vocab_file	,A					)

          return (out_vocab_file,)



