code: 
  
  
  
  
  
  
  from typing import Optional
  
  from ..utils.logging import get_logger
  from .audio_classificiation import AudioClassification
  from .automatic_speech_recognition import AutomaticSpeechRecognition
  from .base import TaskTemplate
  from .image_classification import ImageClassification
  from .language_modeling import LanguageModeling
  from .question_answering import QuestionAnsweringExtractive
  from .summarization import Summarization
  from .text_classification import TextClassification
  
  
  lowerCamelCase			:							Dict       =[
      '''AutomaticSpeechRecognition''',
      '''AudioClassification''',
      '''ImageClassification''',
      '''LanguageModeling''',
      '''QuestionAnsweringExtractive''',
      '''Summarization''',
      '''TaskTemplate''',
      '''TextClassification''',
  ]
  
  lowerCamelCase			:							Dict       =get_logger(__name__)
  
  
  lowerCamelCase			:							Optional[int]       ={
      AutomaticSpeechRecognition.task: AutomaticSpeechRecognition,
      AudioClassification.task: AudioClassification,
      ImageClassification.task: ImageClassification,
      LanguageModeling.task: LanguageModeling,
      QuestionAnsweringExtractive.task: QuestionAnsweringExtractive,
      Summarization.task: Summarization,
      TextClassification.task: TextClassification,
  }
  
  
  
  
  
  
  
  def 	SCREAMING_SNAKE_CASE							(      __lowerCAmelCase    )				->			Optional[TaskTemplate]:
       UpperCamelCase__    :     Union[str, Any]        =						task_template_dict.get("task"    )
       if task_name is None:
            logger.warning(f'Couldn\'t find template for task \'{task_name}\'. Available templates: {list(__lowerCAmelCase    )}'    )
            return None
       UpperCamelCase__    :     Tuple        =						NAMEaTEMPLATE.get(__lowerCAmelCase    )
       return template.from_dict(__lowerCAmelCase    )
style_context: 
  
  
  
  
  
  
  import os
  import unittest
  
  from transformers import MPNetTokenizerFast
  from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
  from transformers.testing_utils import require_tokenizers, slow
  
  from ...test_tokenization_common import TokenizerTesterMixin
  
  
  
  
  
  @require_tokenizers
  class     __a						(					A__ ,     unittest.TestCase ):
   _lowerCAmelCase : str 				=				MPNetTokenizer
   _lowerCAmelCase : List[str] 				=				MPNetTokenizerFast
   _lowerCAmelCase : List[Any] 				=				True
   _lowerCAmelCase : Union[str, Any] 				=				True
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     List[Any]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        super().setUp()
  
        UpperCamelCase__    :     List[Any]        =						[
            "[UNK]",
            "[CLS]",
            "[SEP]",
            "[PAD]",
            "[MASK]",
            "want",
            "##want",
            "##ed",
            "wa",
            "un",
            "runn",
            "##ing",
            ",",
            "low",
            "lowest",
        ]
        UpperCamelCase__    :     int        =						os.path.join(self.tmpdirname							,     VOCAB_FILES_NAMES["vocab_file"]		)
        with open(self.vocab_file							,     "w"							,     encoding="utf-8"		) as vocab_writer:
             vocab_writer.write("".join([x + "\n" for x in vocab_tokens]		)		)
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Tuple							,     SCREAMING_SNAKE_CASE      :     List[str]		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     List[str]        =						"UNwant\u00E9d,running"
        UpperCamelCase__    :     List[str]        =						"unwanted, running"
        return input_text, output_text
  
  
  
  
  
  
  
   def       __lowercase      (	self      :     Any		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     str        =						self.tokenizer_class(self.vocab_file		)
  
        UpperCamelCase__    :     Any        =						tokenizer.tokenize("UNwant\u00E9d,running"		)
        self.assertListEqual(SCREAMING_SNAKE_CASE							,     ["un", "##want", "##ed", ",", "runn", "##ing"]		)
        self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE		)							,     [9, 6, 7, 12, 10, 11]		)
  
  
  
  
  
  
  
   @slow
   def       __lowercase      (	self      :     str		):
  
  
        '''simple docstring'''
  
  
  
  
  
  
        UpperCamelCase__    :     Union[str, Any]        =						self.tokenizer_class.from_pretrained("microsoft/mpnet-base"		)
  
        UpperCamelCase__    :     Optional[int]        =						tokenizer.encode("sequence builders"							,     add_special_tokens=SCREAMING_SNAKE_CASE		)
        UpperCamelCase__    :     Optional[int]        =						tokenizer.encode("multi-sequence build"							,     add_special_tokens=SCREAMING_SNAKE_CASE		)
  
        UpperCamelCase__    :     Tuple        =						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE		)
        UpperCamelCase__    :     Optional[int]        =						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE		)
  
        assert encoded_sentence == [0] + text + [2]
        assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]