





'''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:
    A						    =							None


A						    =							logging.get_logger(__name__)

A						    =							{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

A						    =							{
    '''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''',
    },
}

A						    =							{
    '''facebook/xglm-564M''': 20_48,
}



class 							__SCREAMING_SNAKE_CASE			(       lowerCAmelCase__      ):
      '''simple docstring'''



      lowerCAmelCase__       :      Union[str, Any] 		=		VOCAB_FILES_NAMES
      lowerCAmelCase__       :      List[Any] 		=		PRETRAINED_VOCAB_FILES_MAP
      lowerCAmelCase__       :      Tuple 		=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCAmelCase__       :      Optional[int] 		=		["input_ids", "attention_mask"]
      lowerCAmelCase__       :      str 		=		XGLMTokenizer

      def __init__(							self    : Optional[Any]   ,UpperCamelCase    : str=None   ,UpperCamelCase    : Dict=None   ,UpperCamelCase    : Dict="<s>"   ,UpperCamelCase    : Optional[int]="</s>"   ,UpperCamelCase    : Any="</s>"   ,UpperCamelCase    : Optional[Any]="<s>"   ,UpperCamelCase    : Any="<unk>"   ,UpperCamelCase    : Union[str, Any]="<pad>"   ,**UpperCamelCase    : Union[str, Any]   ,)		->  Any:
           # Compatibility with the original tokenizer
           _lowercase							:      Optional[int]  						=							7
           _lowercase							:      Dict  						=							[F'''<madeupword{i}>''' for i in range(self.num_madeup_words  )]

           _lowercase							:      Any  						=							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__(
               UpperCamelCase   ,tokenizer_file=UpperCamelCase   ,bos_token=UpperCamelCase   ,eos_token=UpperCamelCase   ,sep_token=UpperCamelCase   ,cls_token=UpperCamelCase   ,unk_token=UpperCamelCase   ,pad_token=UpperCamelCase   ,**UpperCamelCase   ,)

           _lowercase							:      Any  						=							vocab_file
           _lowercase							:      str  						=							False if not self.vocab_file else True

      def   _lowerCamelCase		(							self    : Optional[int]   ,UpperCamelCase    : List[int]   ,UpperCamelCase    : Optional[List[int]] = None  )		->  List[int]:

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

      def   _lowerCamelCase		(							self    : Optional[int]   ,UpperCamelCase    : List[int]   ,UpperCamelCase    : Optional[List[int]] = None  )		->  List[int]:
           _lowercase							:      Tuple  						=							[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    : Dict   ,UpperCamelCase    : str   ,UpperCamelCase    : Optional[str] = None  )		->  Tuple[str]:
           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(UpperCamelCase  ):
                logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''  )
                return
           _lowercase							:      str  						=							os.path.join(
               UpperCamelCase   ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']  )

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

           return (out_vocab_file,)






'''simple docstring'''







import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


A						    =							logging.get_logger(__name__)



class 							__SCREAMING_SNAKE_CASE			(       lowerCAmelCase__      ):
      '''simple docstring'''



      def __init__(							self    : Tuple   ,*UpperCamelCase    : str   ,**UpperCamelCase    : List[Any]  )		->  None:
           warnings.warn(
               'The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
               ' Please use MobileNetV2ImageProcessor instead.'   ,UpperCamelCase   ,)
           super().__init__(*UpperCamelCase   ,**UpperCamelCase  )