'''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	):
    a__       :						Tuple          =  FunnelTokenizer
    a__       :						Union[str, Any]          =  FunnelTokenizerFast
    a__       :						str          =  True
    a__       :						Any          =  True



    def 					_lowercase						(self    :    str ):
         super().setUp()

         UpperCAmelCase_           =   [
             "<unk>",
             "<cls>",
             "<sep>",
             "want",
             "##want",
             "##ed",
             "wa",
             "un",
             "runn",
             "##ing",
             ",",
             "low",
             "lowest",
         ]
         UpperCAmelCase_           =   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    :    str   ,			**__a    :    str ):
         return FunnelTokenizer.from_pretrained(self.tmpdirname   ,			**__a )



    def 					_lowercase						(self    :    Optional[int]   ,			**__a    :    List[Any] ):
         return FunnelTokenizerFast.from_pretrained(self.tmpdirname   ,			**__a )



    def 					_lowercase						(self    :    Union[str, Any]   ,			__a    :    Dict ):
         UpperCAmelCase_           =   "UNwant\u00E9d,running"
         UpperCAmelCase_           =   "unwanted, running"
         return input_text, output_text



    def 					_lowercase						(self    :    Tuple ):
         UpperCAmelCase_           =   self.tokenizer_class(self.vocab_file )

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






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

              UpperCAmelCase_           =   tokenizer("UNwant\u00E9d,running"   ,			"UNwant\u00E9d,running" )
              self.assertListEqual(inputs["token_type_ids"]   ,			[2] + [0] * sentence_len + [1] * sentence_len )





'''simple docstring'''





from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest




@require_tokenizers
class        __A      ( UpperCamelCase__	):
    a__       :						Optional[Any]          =  DistilBertTokenizer
    a__       :						Any          =  DistilBertTokenizerFast
    a__       :						str          =  True



    @slow
    def 					_lowercase						(self    :    int ):
         UpperCAmelCase_           =   DistilBertTokenizer.from_pretrained("distilbert-base-uncased" )

         UpperCAmelCase_           =   tokenizer.encode("sequence builders"   ,			add_special_tokens=__a )
         UpperCAmelCase_           =   tokenizer.encode("multi-sequence build"   ,			add_special_tokens=__a )

         UpperCAmelCase_           =   tokenizer.build_inputs_with_special_tokens(__a )
         UpperCAmelCase_           =   tokenizer.build_inputs_with_special_tokens(__a   ,			__a )

         assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
         assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
             tokenizer.sep_token_id
         ]




