

'''simple docstring'''
import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class      a__  (							_UpperCAmelCase  ,				unittest.TestCase  ):
   _SCREAMING_SNAKE_CASE   :					Dict     	=							FunnelTokenizer
   _SCREAMING_SNAKE_CASE   :					Union[str, Any]     	=							FunnelTokenizerFast
   _SCREAMING_SNAKE_CASE   :					Union[str, Any]     	=							True
   _SCREAMING_SNAKE_CASE   :					Tuple     	=							True


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      super().setUp()

      _lowercase      :				Optional[Any]      					=       [
          '''<unk>''',
          '''<cls>''',
          '''<sep>''',
          '''want''',
          '''##want''',
          '''##ed''',
          '''wa''',
          '''un''',
          '''runn''',
          '''##ing''',
          ''',''',
          '''low''',
          '''lowest''',
      ]
      _lowercase      :				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 						_lowerCamelCase       (			self      ,    **_UpperCamelCase  ):





      """simple docstring"""





      return FunnelTokenizer.from_pretrained(self.tmpdirname      ,    **_UpperCAmelCase  )


   def 						_lowerCamelCase       (			self      ,    **_UpperCamelCase  ):





      """simple docstring"""





      return FunnelTokenizerFast.from_pretrained(self.tmpdirname      ,    **_UpperCAmelCase  )


   def 						_lowerCamelCase       (			self      ,    _UpperCamelCase  ):





      """simple docstring"""





      _lowercase      :				Tuple      					=       '''UNwant\u00E9d,running'''
      _lowercase      :				Optional[int]      					=       '''unwanted, running'''
      return input_text, output_text


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				List[str]      					=       self.tokenizer_class(self.vocab_file  )

      _lowercase      :				Tuple      					=       tokenizer.tokenize("UNwant\u00E9d,running"  )
      self.assertListEqual(_UpperCAmelCase      ,    ["un", "##want", "##ed", ",", "runn", "##ing"]  )
      self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase  )      ,    [7, 4, 5, 10, 8, 9]  )






   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Union[str, Any]      					=       self.get_tokenizers(do_lower_case=_UpperCAmelCase  )
      for tokenizer in tokenizers:
         _lowercase      :				int      					=       tokenizer("UNwant\u00E9d,running"  )
         _lowercase      :				Union[str, Any]      					=       len(inputs["input_ids"]  ) - 1
         self.assertListEqual(inputs["token_type_ids"]      ,    [2] + [0] * sentence_len  )

         _lowercase      :				Union[str, Any]      					=       tokenizer("UNwant\u00E9d,running"      ,    "UNwant\u00E9d,running"  )
         self.assertListEqual(inputs["token_type_ids"]      ,    [2] + [0] * sentence_len + [1] * sentence_len  )









'''simple docstring'''
import logging

from transformers import PretrainedConfig


_snake_case         =  logging.getLogger(__name__)


_snake_case         =  {
    'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json',
}


class        a__  (							lowerCamelCase_  ):
   _SCREAMING_SNAKE_CASE   :					List[str]     	=							'bertabs'


   def __init__(			self      ,    _UpperCamelCase=30522      ,    _UpperCamelCase=512      ,    _UpperCamelCase=6      ,    _UpperCamelCase=512      ,    _UpperCamelCase=8      ,    _UpperCamelCase=512      ,    _UpperCamelCase=0.2      ,    _UpperCamelCase=6      ,    _UpperCamelCase=768      ,    _UpperCamelCase=8      ,    _UpperCamelCase=2048      ,    _UpperCamelCase=0.2      ,    **_UpperCamelCase      ,    ):





      """simple docstring"""





      super().__init__(**_UpperCamelCase  )

      _lowercase      :				List[str]      					=       vocab_size
      _lowercase      :				Tuple      					=       max_pos

      _lowercase      :				int      					=       enc_layers
      _lowercase      :				str      					=       enc_hidden_size
      _lowercase      :				Optional[Any]      					=       enc_heads
      _lowercase      :				Union[str, Any]      					=       enc_ff_size
      _lowercase      :				Tuple      					=       enc_dropout

      _lowercase      :				Dict      					=       dec_layers
      _lowercase      :				List[str]      					=       dec_hidden_size
      _lowercase      :				List[str]      					=       dec_heads
      _lowercase      :				str      					=       dec_ff_size
      _lowercase      :				str      					=       dec_dropout






