
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:
 lowerCamelCase_				:							List[str]       =    None


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

lowerCamelCase_				:							Optional[Any]       =    {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

lowerCamelCase_				:							str       =    {
    """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""",
    },
}

lowerCamelCase_				:							int       =    {
    """facebook/xglm-564M""": 2_048,
}







class  _lowerCamelCase			(_a					):
     lowercase__				  =			VOCAB_FILES_NAMES
     lowercase__				  =			PRETRAINED_VOCAB_FILES_MAP
     lowercase__				  =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowercase__				  =			["""input_ids""", """attention_mask"""]
     lowercase__				  =			XGLMTokenizer

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

            __snake_case						       =   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__(
                SCREAMING_SNAKE_CASE_							,       tokenizer_file=SCREAMING_SNAKE_CASE_							,       bos_token=SCREAMING_SNAKE_CASE_							,       eos_token=SCREAMING_SNAKE_CASE_							,       sep_token=SCREAMING_SNAKE_CASE_							,       cls_token=SCREAMING_SNAKE_CASE_							,       unk_token=SCREAMING_SNAKE_CASE_							,       pad_token=SCREAMING_SNAKE_CASE_							,       **SCREAMING_SNAKE_CASE_							,       )

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

     def 						__lowerCamelCase				(  self							,       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_ = None    ):

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

     def 						__lowerCamelCase				(  self							,       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_ = None    ):
            __snake_case						       =   [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 						__lowerCamelCase				(  self							,       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_ = 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(SCREAMING_SNAKE_CASE_    ):
                   logger.error(f'''Vocabulary path ({save_directory}) should be a directory.'''    )
                   return
            __snake_case						       =   os.path.join(
                SCREAMING_SNAKE_CASE_							,       (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )

            if os.path.abspath(self.vocab_file    ) != os.path.abspath(SCREAMING_SNAKE_CASE_    ):
                   copyfile(self.vocab_file							,       SCREAMING_SNAKE_CASE_    )

            return (out_vocab_file,)







import warnings

from ...utils import logging
from .image_processing_detr import DetrImageProcessor


_UpperCamelCase       :				Tuple           =			logging.get_logger(__name__)







class 		_lowerCAmelCase(		_a):

  """simple docstring"""







  def __init__(   self    ,							*UpperCAmelCase    ,							**UpperCAmelCase      )->   None:
     warnings.warn(
         '''The class DetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
         ''' Please use DetrImageProcessor instead.'''    ,							UpperCAmelCase    ,							)
     super().__init__(*UpperCAmelCase    ,							**UpperCAmelCase      )

