code: 
  '''simple docstring'''
  
  import inspect
  import json
  import os
  import tempfile
  import unittest
  
  from transformers.models.speech_to_text_a import SpeechaTextaTokenizer
  from transformers.models.speech_to_text_a.tokenization_speech_to_text_a import VOCAB_FILES_NAMES
  
  from ...test_tokenization_common import TokenizerTesterMixin
  
  
  class   a_  (_a							,			unittest.TestCase    ):
         __lowerCAmelCase    :				Dict    =      SpeechaTextaTokenizer
         __lowerCAmelCase    :				Tuple    =      False
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           super().setUp()
  
           _lowerCAmelCase       :  Tuple   				=					"""<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab""".split(""" """  )
           _lowerCAmelCase       :  Dict   				=					["""he re</w> 123""", """here a 1456"""]
           _lowerCAmelCase       :  Dict   				=					dict(zip(snake_case_   ,   range(len(snake_case_  )  )  )  )
  
           _lowerCAmelCase       :  Union[str, Any]   				=					{"""pad_token""": """<pad>""", """unk_token""": """<unk>""", """bos_token""": """<s>""", """eos_token""": """</s>"""}
  
           _lowerCAmelCase       :  List[Any]   				=					tempfile.mkdtemp()
           _lowerCAmelCase       :  Dict   				=					os.path.join(self.tmpdirname   ,   VOCAB_FILES_NAMES["""vocab_file"""]  )
           _lowerCAmelCase       :  str   				=					os.path.join(self.tmpdirname   ,   VOCAB_FILES_NAMES["""merges_file"""]  )
  
           with open(self.vocab_file   ,   """w"""   ,   encoding="""utf-8"""  ) as fp:
             fp.write(json.dumps(snake_case_  ) + """\n"""  )
  
           with open(self.merges_file   ,   """w"""  ) as fp:
             fp.write("""\n""".join(snake_case_  )  )
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           _lowerCAmelCase       :  Optional[Any]   				=					list(self.get_tokenizer().get_vocab().keys()  )
  
           self.assertEqual(vocab_keys[0]   ,   """<s>"""  )
           self.assertEqual(vocab_keys[1]   ,   """<pad>"""  )
           self.assertEqual(vocab_keys[-1]   ,   """vocab"""  )
           self.assertEqual(len(snake_case_  )   ,   1_4  )
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           self.assertEqual(self.get_tokenizer().vocab_size   ,   1_4  )
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           _lowerCAmelCase       :  Dict   				=					SpeechaTextaTokenizer.from_pretrained(self.tmpdirname  )
  
           # make sure @@ is correctly concatenated
           _lowerCAmelCase       :  Union[str, Any]   				=					[4, 6, 8, 7, 1_0]  # ["here@@", "couple", "words", "of@@", "the"]
           _lowerCAmelCase       :  Union[str, Any]   				=					tokenizer.decode(snake_case_  )
  
           self.assertTrue(output_string == """herecouple words ofthe"""  )
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           _lowerCAmelCase       :  str   				=					SpeechaTextaTokenizer.from_pretrained(self.tmpdirname  )
  
           with tempfile.TemporaryDirectory() as tmp_dirname:
             tokenizer.save_pretrained(snake_case_  )
             os.remove(os.path.join(snake_case_   ,   """merges.txt"""  )  )
  
             # load tokenizer without merges file should not throw an error
             _lowerCAmelCase       :  str   				=					SpeechaTextaTokenizer.from_pretrained(snake_case_  )
  
           with tempfile.TemporaryDirectory() as tmp_dirname:
             # save tokenizer and load again
             tokenizer.save_pretrained(snake_case_  )
             _lowerCAmelCase       :  Optional[Any]   				=					SpeechaTextaTokenizer.from_pretrained(snake_case_  )
  
           self.assertIsNotNone(snake_case_  )
  
  
  
  
  
  
  
         def 							__UpperCamelCase       (     self  ):
           if not self.test_slow_tokenizer:
             return
  
           _lowerCAmelCase       :  Any   				=					inspect.signature(self.tokenizer_class.__init__  )
           _lowerCAmelCase       :  List[str]   				=					self.get_tokenizer()
  
           for parameter_name, parameter in signature.parameters.items():
             if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
               self.assertIn(snake_case_   ,   tokenizer.init_kwargs  )
  
  
  
style_context: 
  '''simple docstring'''
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  UpperCamelCase_     			=       {
      """configuration_deformable_detr""": ["""DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DeformableDetrConfig"""],
  }
  
  try:
       if not is_vision_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       UpperCamelCase_     			=       ["""DeformableDetrFeatureExtractor"""]
       UpperCamelCase_     			=       ["""DeformableDetrImageProcessor"""]
  
  try:
       if not is_torch_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       UpperCamelCase_     			=       [
           """DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """DeformableDetrForObjectDetection""",
           """DeformableDetrModel""",
           """DeformableDetrPreTrainedModel""",
       ]
  
  
  if TYPE_CHECKING:
       from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig
  
       try:
            if not is_vision_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
            from .image_processing_deformable_detr import DeformableDetrImageProcessor
  
       try:
            if not is_torch_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .modeling_deformable_detr import (
                DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
                DeformableDetrForObjectDetection,
                DeformableDetrModel,
                DeformableDetrPreTrainedModel,
            )
  
  else:
       import sys
  
       UpperCamelCase_     			=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
  