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       ( _SCREAMING_SNAKE_CASE,					unittest.TestCase    ):
  
  
  
  
  
  
   """simple docstring"""
  
  
  
  
   __lowerCAmelCase				      =						SpeechaTextaTokenizer
   __lowerCAmelCase				      =						False
  
  
   def    SCREAMING_SNAKE_CASE							(	self		)      ->  Optional[int]:
       super().setUp()
  
       a					='''<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab'''.split(''' '''		)
       a					=['''he re</w> 123''', '''here a 1456''']
       a					=dict(zip(__A				,					range(len(__A		)		)		)		)
  
       a					={'''pad_token''': '''<pad>''', '''unk_token''': '''<unk>''', '''bos_token''': '''<s>''', '''eos_token''': '''</s>'''}
  
       a					=tempfile.mkdtemp()
       a					=os.path.join(self.tmpdirname				,					VOCAB_FILES_NAMES['''vocab_file''']		)
       a					=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(__A		) + '''\n'''		)
  
       with open(self.merges_file				,					'''w'''		) as fp:
           fp.write('''\n'''.join(__A		)		)
  
  
   def    SCREAMING_SNAKE_CASE							(	self		)      ->  List[Any]:
       a					=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(__A		)				,					14		)
  
  
   def    SCREAMING_SNAKE_CASE							(	self		)      ->  Dict:
       self.assertEqual(self.get_tokenizer().vocab_size				,					14		)
  
  
   def    SCREAMING_SNAKE_CASE							(	self		)      ->  Any:
       a					=SpeechaTextaTokenizer.from_pretrained(self.tmpdirname		)
  
       # make sure @@ is correctly concatenated
       a					=[4, 6, 8, 7, 10]  # ["here@@", "couple", "words", "of@@", "the"]
       a					=tokenizer.decode(__A		)
  
       self.assertTrue(output_string == '''herecouple words ofthe'''		)
  
  
   def    SCREAMING_SNAKE_CASE							(	self		)      ->  Tuple:
       a					=SpeechaTextaTokenizer.from_pretrained(self.tmpdirname		)
  
       with tempfile.TemporaryDirectory() as tmp_dirname:
           tokenizer.save_pretrained(__A		)
           os.remove(os.path.join(__A				,					'''merges.txt'''		)		)
  
           # load tokenizer without merges file should not throw an error
           a					=SpeechaTextaTokenizer.from_pretrained(__A		)
  
       with tempfile.TemporaryDirectory() as tmp_dirname:
           # save tokenizer and load again
           tokenizer.save_pretrained(__A		)
           a					=SpeechaTextaTokenizer.from_pretrained(__A		)
  
       self.assertIsNotNone(__A		)
  
  
  
  
  
   def    SCREAMING_SNAKE_CASE							(	self		)      ->  Optional[int]:
       if not self.test_slow_tokenizer:
           return
  
       a					=inspect.signature(self.tokenizer_class.__init__		)
       a					=self.get_tokenizer()
  
       for parameter_name, parameter in signature.parameters.items():
           if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
               self.assertIn(__A				,					tokenizer.init_kwargs		)
style_context: 
  
  
  """simple docstring"""
  
  
  
  
  
  
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowerCamelCase_     :     int    		=						logging.get_logger(__name__)
  
  lowerCamelCase_     :     Optional[Any]    		=						{
      """dandelin/vilt-b32-mlm""": """https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"""
  }
  
  
  
  
  
  
  class    __A       ( _SCREAMING_SNAKE_CASE    ):
  
  
  
  
  
  
   """simple docstring"""
  
  
  
  
   __lowerCAmelCase				      =						"vilt"
  
  
   def __init__(	self				,					__A=3_0522				,					__A=2				,					__A=2				,					__A=40				,					__A=768				,					__A=12				,					__A=12				,					__A=3072				,					__A="gelu"				,					__A=0.0				,					__A=0.0				,					__A=0.02				,					__A=1E-1_2				,					__A=384				,					__A=32				,					__A=3				,					__A=True				,					__A=-1				,					__A=False				,					__A=-1				,					**__A				,					)      ->  Dict:
       super().__init__(tie_word_embeddings=__A				,					**__A		)
  
       a					=vocab_size
       a					=type_vocab_size
       a					=modality_type_vocab_size
       a					=max_position_embeddings
  
       a					=hidden_size
       a					=num_hidden_layers
       a					=num_attention_heads
       a					=intermediate_size
       a					=hidden_act
       a					=hidden_dropout_prob
       a					=attention_probs_dropout_prob
       a					=initializer_range
       a					=layer_norm_eps
  
       a					=image_size
       a					=patch_size
       a					=num_channels
       a					=qkv_bias
       a					=max_image_length
       a					=num_images