
import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class UpperCAmelCase   (						SCREAMING_SNAKE_CASE__							,							unittest.TestCase   ):





   '''simple docstring'''
   __UpperCamelCase		:    Optional[int] 				=    LayoutLMTokenizer
   __UpperCamelCase		:    List[Any] 				=    LayoutLMTokenizerFast
   __UpperCamelCase		:    int 				=    True
   __UpperCamelCase		:    Any 				=    True


   def  __magic_name__				(					self     :							Tuple     ):

      """simple docstring"""
      super().setUp()

      _A:  Union[str, Any]					=       [
          '''[UNK]''',
          '''[CLS]''',
          '''[SEP]''',
          '''want''',
          '''##want''',
          '''##ed''',
          '''wa''',
          '''un''',
          '''runn''',
          '''##ing''',
          ''',''',
          '''low''',
          '''lowest''',
      ]
      _A:  Optional[Any]					=       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  __magic_name__				(					self     :							int			,			**lowerCAmelCase_     :							Union[str, Any]     ):

      """simple docstring"""
      return LayoutLMTokenizer.from_pretrained(self.tmpdirname			,			**lowerCAmelCase_     )


   def  __magic_name__				(					self     :							int			,			lowerCAmelCase_     :							List[str]     ):

      """simple docstring"""
      _A:  Dict					=       '''UNwant\u00E9d,running'''
      _A:  Union[str, Any]					=       '''unwanted, running'''
      return input_text, output_text


   def  __magic_name__				(					self     :							Any     ):

      """simple docstring"""
      _A:  List[str]					=       self.tokenizer_class(self.vocab_file     )

      _A:  Tuple					=       tokenizer.tokenize('''UNwant\u00E9d,running'''     )
      self.assertListEqual(lowerCAmelCase_			,			['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing''']     )
      self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_     )			,			[7, 4, 5, 1_0, 8, 9]     )


   def  __magic_name__				(					self     :							Optional[Any]     ):

      """simple docstring"""
      pass





from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Sequence, Value
from .base import TaskTemplate






@dataclass(frozen=SCREAMING_SNAKE_CASE__   )
class UpperCAmelCase   (						SCREAMING_SNAKE_CASE__   ):





   '''simple docstring'''
   # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
   __UpperCamelCase		:    str 				=    field(default='''question-answering-extractive'''							,							metadata={'''include_in_asdict_even_if_is_default''': True}   )
   __UpperCamelCase		:    ClassVar[Features] 				=    Features({'''question''': Value('''string'''   ), '''context''': Value('''string'''   )}   )
   __UpperCamelCase		:    ClassVar[Features] 				=    Features(
       {
           '''answers''': Sequence(
               {
                   '''text''': Value('''string'''   ),
                   '''answer_start''': Value('''int32'''   ),
               }   )
       }   )
   __UpperCamelCase		:    str 				=    "question"
   __UpperCamelCase		:    str 				=    "context"
   __UpperCamelCase		:    str 				=    "answers"


   @property
   def  __magic_name__				(					self     :							List[str]     ):

      """simple docstring"""
      return {self.question_column: "question", self.context_column: "context", self.answers_column: "answers"}



