




from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest





@require_tokenizers
class        lowerCamelCase__(   lowercase__):
      UpperCAmelCase__ :      List[Any]       						=  SqueezeBertTokenizer
      UpperCAmelCase__ :      Optional[int]       						=  SqueezeBertTokenizerFast
      UpperCAmelCase__ :      str       						=  True
      def      lowerCAmelCase__		(							self:					Any       ,			**UpperCamelCase_:					List[str]  ):
             return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname       ,			**UpperCamelCase_  )




      @slow
      def      lowerCAmelCase__		(							self:					List[Any]  ):
             __lowerCamelCase  =		SqueezeBertTokenizer.from_pretrained("""squeezebert/squeezebert-mnli-headless"""  )

             __lowerCamelCase  =		tokenizer.encode("""sequence builders"""       ,			add_special_tokens=UpperCamelCase_  )
             __lowerCamelCase  =		tokenizer.encode("""multi-sequence build"""       ,			add_special_tokens=UpperCamelCase_  )

             __lowerCamelCase  =		tokenizer.build_inputs_with_special_tokens(UpperCamelCase_  )
             __lowerCamelCase  =		tokenizer.build_inputs_with_special_tokens(UpperCamelCase_       ,			UpperCamelCase_  )

             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
             ]






import os
import unittest

import pytest
from parameterized import parameterized

from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device


# skipping in unittest tests

__lowerCamelCase								=      [(1,)]







def  _snake_case			(							)  ->  str:






      '''simple docstring'''







      UpperCAmelCase_	:						Optional[Any]					   =		bool(os.getenv("RUN_SLOW"       ,	0     )     )
      if run_slow:
            assert True
      else:
            assert False, "should have been skipped"







def  _snake_case			(							)  ->  Tuple:






      '''simple docstring'''







      UpperCAmelCase_	:						Union[str, Any]					   =		bool(os.getenv("RUN_SLOW"       ,	0     )     )
      if run_slow and torch_device == "cuda":
            assert True
      else:
            assert False, "should have been skipped"


@require_torch
class 	snake_case_			(unittest.TestCase	):




       """simple docstring"""






       @slow
       @require_torch_gpu
       def 			A_ (  self):

             """simple docstring"""





             check_slow_torch_cuda()



       @require_torch_gpu
       @slow
       def 			A_ (  self):

             """simple docstring"""





             check_slow_torch_cuda()



       @parameterized.expand(lowercase)
       @slow
       def 			A_ (  self  ,lowercase=None):

             """simple docstring"""





             check_slow()







@slow
@require_torch_gpu
def  _snake_case			(							)  ->  str:






      '''simple docstring'''







      check_slow_torch_cuda()







@require_torch_gpu
@slow
def  _snake_case			(							)  ->  Union[str, Any]:






      '''simple docstring'''







      check_slow_torch_cuda()







@slow
@pytest.mark.parametrize("param"       ,	[1]     )
def  _snake_case			(							__snake_case     )  ->  Optional[Any]:






      '''simple docstring'''







      check_slow()







@pytest.mark.parametrize("param"       ,	[1]     )
@slow
def  _snake_case			(							__snake_case     )  ->  Any:






      '''simple docstring'''







      check_slow()
