code: 
  
  import os
  from shutil import copyfile
  from typing import List, Optional, Tuple
  
  from ...tokenization_utils import AddedToken
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import is_sentencepiece_available, logging
  
  
  if is_sentencepiece_available():
  			from .tokenization_xlm_roberta import XLMRobertaTokenizer
  else:
  			UpperCAmelCase_       :				int		   =      None
  
  
  UpperCAmelCase_       :				List[Any]		   =      logging.get_logger(__name__)
  
  UpperCAmelCase_       :				Tuple		   =      {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}
  
  UpperCAmelCase_       :				Optional[Any]		   =      {
      '''vocab_file''': {
          '''xlm-roberta-base''': '''https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model''',
          '''xlm-roberta-large''': '''https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model''',
          '''xlm-roberta-large-finetuned-conll02-dutch''': (
              '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'''
          ),
          '''xlm-roberta-large-finetuned-conll02-spanish''': (
              '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'''
          ),
          '''xlm-roberta-large-finetuned-conll03-english''': (
              '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'''
          ),
          '''xlm-roberta-large-finetuned-conll03-german''': (
              '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'''
          ),
      },
      '''tokenizer_file''': {
          '''xlm-roberta-base''': '''https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json''',
          '''xlm-roberta-large''': '''https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json''',
          '''xlm-roberta-large-finetuned-conll02-dutch''': (
              '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json'''
          ),
          '''xlm-roberta-large-finetuned-conll02-spanish''': (
              '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json'''
          ),
          '''xlm-roberta-large-finetuned-conll03-english''': (
              '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json'''
          ),
          '''xlm-roberta-large-finetuned-conll03-german''': (
              '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json'''
          ),
      },
  }
  
  UpperCAmelCase_       :				Any		   =      {
      '''xlm-roberta-base''': 512,
      '''xlm-roberta-large''': 512,
      '''xlm-roberta-large-finetuned-conll02-dutch''': 512,
      '''xlm-roberta-large-finetuned-conll02-spanish''': 512,
      '''xlm-roberta-large-finetuned-conll03-english''': 512,
      '''xlm-roberta-large-finetuned-conll03-german''': 512,
  }
  
  
  
  
  
  
  class     lowerCamelCase_			(  _lowercase  ):
  	_lowercase		:      str    				=							VOCAB_FILES_NAMES
  	_lowercase		:      List[str]    				=							PRETRAINED_VOCAB_FILES_MAP
  	_lowercase		:      Tuple    				=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  	_lowercase		:      Union[str, Any]    				=							['''input_ids''', '''attention_mask''']
  	_lowercase		:      int    				=							XLMRobertaTokenizer
  
  
  
  
  	def __init__(    self	:    Optional[Any]				,			__A	:    Any=None				,			__A	:    Optional[Any]=None				,			__A	:    List[str]="<s>"				,			__A	:    Any="</s>"				,			__A	:    Any="</s>"				,			__A	:    int="<s>"				,			__A	:    List[str]="<unk>"				,			__A	:    List[str]="<pad>"				,			__A	:    int="<mask>"				,			**__A	:    Optional[int]				,			):
  		# Mask token behave like a normal word, i.e. include the space before it
  		__A   : str								= AddedToken(__A				,			lstrip=__A				,			rstrip=__A       ) if isinstance(__A				,			__A       ) else mask_token
  
  		super().__init__(
  		    __A				,			tokenizer_file=__A				,			bos_token=__A				,			eos_token=__A				,			sep_token=__A				,			cls_token=__A				,			unk_token=__A				,			pad_token=__A				,			mask_token=__A				,			**__A				,			)
  
  		__A   : Optional[int]								= vocab_file
  		__A   : Dict								= False if not self.vocab_file else True
  
  
  
  
  	def 					lowerCAmelCase_					(    self	:    Optional[Any]				,			__A	:    List[int]				,			__A	:    Optional[List[int]] = None       ):
  
  		if token_ids_a is None:
  			return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
  		__A   : str								= [self.cls_token_id]
  		__A   : List[str]								= [self.sep_token_id]
  		return cls + token_ids_a + sep + sep + token_ids_a + sep
  
  
  
  
  	def 					lowerCAmelCase_					(    self	:    Any				,			__A	:    List[int]				,			__A	:    Optional[List[int]] = None       ):
  		__A   : Optional[int]								= [self.sep_token_id]
  		__A   : List[Any]								= [self.cls_token_id]
  
  		if token_ids_a is None:
  			return len(cls + token_ids_a + sep       ) * [0]
  		return len(cls + token_ids_a + sep + sep + token_ids_a + sep       ) * [0]
  
  
  
  
  	def 					lowerCAmelCase_					(    self	:    List[Any]				,			__A	:    str				,			__A	:    Optional[str] = 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
  		__A   : List[str]								= 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,)
  
  
  
  
  
  
style_context: 
  
  import unittest
  from pathlib import Path
  
  from transformers import is_vision_available, load_tool
  from transformers.testing_utils import get_tests_dir
  
  from .test_tools_common import ToolTesterMixin
  
  
  if is_vision_available():
  			from PIL import Image
  
  
  
  
  
  
  class     lowerCamelCase_			(  unittest.TestCase	,			_lowercase  ):
  
  
  
  
  	def 					lowerCAmelCase_					(    self	:    Dict       ):
  		__A   : str								= load_tool("""image-captioning"""       )
  		self.tool.setup()
  		__A   : Dict								= load_tool("""image-captioning"""				,			remote=__A       )
  
  
  
  
  	def 					lowerCAmelCase_					(    self	:    Optional[int]       ):
  		__A   : List[Any]								= Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""       )       ) / """000000039769.png"""       )
  		__A   : Optional[Any]								= self.tool(__A       )
  		self.assertEqual(__A				,			"""two cats sleeping on a couch"""       )
  
  
  
  
  	def 					lowerCAmelCase_					(    self	:    Dict       ):
  		__A   : Any								= Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""       )       ) / """000000039769.png"""       )
  		__A   : List[str]								= self.remote_tool(__A       )
  		self.assertEqual(__A				,			"""two cats sleeping on a couch"""       )
  
  
  
  
  	def 					lowerCAmelCase_					(    self	:    Union[str, Any]       ):
  		__A   : Optional[Any]								= Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""       )       ) / """000000039769.png"""       )
  		__A   : str								= self.tool(image=__A       )
  		self.assertEqual(__A				,			"""two cats sleeping on a couch"""       )
  
  
  
  
  	def 					lowerCAmelCase_					(    self	:    str       ):
  		__A   : Dict								= Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO"""       )       ) / """000000039769.png"""       )
  		__A   : List[Any]								= self.remote_tool(image=__A       )
  		self.assertEqual(__A				,			"""two cats sleeping on a couch"""       )
  
  
  
  
  
  