code: 
  
  
  
  
  
  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 	UpperCamelCase_     (     snake_case__     ,    unittest.TestCase       ):
  					_a			:	int							=				SpeechaTextaTokenizer
  					_a			:	List[Any]							=				False
  
  
  
  					def      __a    (		self    :    Union[str, Any]	):
  							super().setUp()
  
  							lowerCamelCase_  :    List[Any]   	=			'<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'.split(' '	)
  							lowerCamelCase_  :    Optional[Any]   	=			['he re</w> 123', 'here a 1456']
  							lowerCamelCase_  :    Optional[int]   	=			dict(zip(lowerCamelCase					,			range(len(lowerCamelCase	)	)	)	)
  
  							lowerCamelCase_  :    Dict   	=			{'pad_token': '<pad>', 'unk_token': '<unk>', 'bos_token': '<s>', 'eos_token': '</s>'}
  
  							lowerCamelCase_  :    List[str]   	=			tempfile.mkdtemp()
  							lowerCamelCase_  :    Optional[int]   	=			os.path.join(self.tmpdirname					,			VOCAB_FILES_NAMES['vocab_file']	)
  							lowerCamelCase_  :    Optional[int]   	=			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(lowerCamelCase	) + '\n'	)
  
  							with open(self.merges_file					,			'w'	) as fp:
  									fp.write('\n'.join(lowerCamelCase	)	)
  
  
  
  					def      __a    (		self    :    Union[str, Any]	):
  							lowerCamelCase_  :    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(lowerCamelCase	)					,			14	)
  
  
  
  					def      __a    (		self    :    List[str]	):
  							self.assertEqual(self.get_tokenizer().vocab_size					,			14	)
  
  
  
  					def      __a    (		self    :    Union[str, Any]	):
  							lowerCamelCase_  :    Union[str, Any]   	=			SpeechaTextaTokenizer.from_pretrained(self.tmpdirname	)
  
  							# make sure @@ is correctly concatenated
  							lowerCamelCase_  :    Tuple   	=			[4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
  							lowerCamelCase_  :    Union[str, Any]   	=			tokenizer.decode(lowerCamelCase	)
  
  							self.assertTrue(output_string == 'herecouple words ofthe'	)
  
  
  
  					def      __a    (		self    :    int	):
  							lowerCamelCase_  :    Union[str, Any]   	=			SpeechaTextaTokenizer.from_pretrained(self.tmpdirname	)
  
  							with tempfile.TemporaryDirectory() as tmp_dirname:
  									tokenizer.save_pretrained(lowerCamelCase	)
  									os.remove(os.path.join(lowerCamelCase					,			'merges.txt'	)	)
  
  									# load tokenizer without merges file should not throw an error
  									lowerCamelCase_  :    int   	=			SpeechaTextaTokenizer.from_pretrained(lowerCamelCase	)
  
  							with tempfile.TemporaryDirectory() as tmp_dirname:
  									# save tokenizer and load again
  									tokenizer.save_pretrained(lowerCamelCase	)
  									lowerCamelCase_  :    List[str]   	=			SpeechaTextaTokenizer.from_pretrained(lowerCamelCase	)
  
  							self.assertIsNotNone(lowerCamelCase	)
  
  
  
  
  
  					def      __a    (		self    :    Optional[int]	):
  
  
  
  
  
  
  
  							if not self.test_slow_tokenizer:
  									return
  
  							lowerCamelCase_  :    Union[str, 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(lowerCamelCase					,			tokenizer.init_kwargs	)
  
  
  
style_context: 
  
  
  
  
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  _lowercase		:     Dict 					=logging.get_logger(__name__)
  
  _lowercase		:     Any 					={
      """dandelin/vilt-b32-mlm""": """https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"""
  }
  
  
  
  
  
  
  class 	UpperCamelCase_     (     snake_case__       ):
  					_a			:	List[str]							=				'vilt'
  
  
  
  					def __init__(		self    :    int					,			lowerCamelCase    :    Any=3_05_22					,			lowerCamelCase    :    Union[str, Any]=2					,			lowerCamelCase    :    Optional[Any]=2					,			lowerCamelCase    :    str=40					,			lowerCamelCase    :    List[str]=7_68					,			lowerCamelCase    :    Optional[int]=12					,			lowerCamelCase    :    List[Any]=12					,			lowerCamelCase    :    List[str]=30_72					,			lowerCamelCase    :    Union[str, Any]="gelu"					,			lowerCamelCase    :    int=0.0					,			lowerCamelCase    :    str=0.0					,			lowerCamelCase    :    int=0.02					,			lowerCamelCase    :    Union[str, Any]=1E-12					,			lowerCamelCase    :    Dict=3_84					,			lowerCamelCase    :    List[str]=32					,			lowerCamelCase    :    Dict=3					,			lowerCamelCase    :    List[str]=True					,			lowerCamelCase    :    int=-1					,			lowerCamelCase    :    List[Any]=False					,			lowerCamelCase    :    Any=-1					,			**lowerCamelCase    :    str					,			):
  							super().__init__(tie_word_embeddings=lowerCamelCase					,			**lowerCamelCase	)
  
  							lowerCamelCase_  :    str   	=			vocab_size
  							lowerCamelCase_  :    Dict   	=			type_vocab_size
  							lowerCamelCase_  :    str   	=			modality_type_vocab_size
  							lowerCamelCase_  :    Optional[Any]   	=			max_position_embeddings
  
  							lowerCamelCase_  :    List[Any]   	=			hidden_size
  							lowerCamelCase_  :    Union[str, Any]   	=			num_hidden_layers
  							lowerCamelCase_  :    Any   	=			num_attention_heads
  							lowerCamelCase_  :    List[Any]   	=			intermediate_size
  							lowerCamelCase_  :    Union[str, Any]   	=			hidden_act
  							lowerCamelCase_  :    Any   	=			hidden_dropout_prob
  							lowerCamelCase_  :    Optional[int]   	=			attention_probs_dropout_prob
  							lowerCamelCase_  :    Any   	=			initializer_range
  							lowerCamelCase_  :    str   	=			layer_norm_eps
  
  							lowerCamelCase_  :    Optional[Any]   	=			image_size
  							lowerCamelCase_  :    List[Any]   	=			patch_size
  							lowerCamelCase_  :    Tuple   	=			num_channels
  							lowerCamelCase_  :    Optional[Any]   	=			qkv_bias
  							lowerCamelCase_  :    Optional[int]   	=			max_image_length
  							lowerCamelCase_  :    Optional[Any]   	=			num_images
  