code: 
  
  
  
  
  
  '''simple docstring'''
  
  
  
  
  import shutil
  import tempfile
  import unittest
  
  import numpy as np
  import pytest
  
  from transformers.testing_utils import require_vision
  from transformers.utils import is_vision_available
  
  
  if is_vision_available():
  			from PIL import Image
  
  			from transformers import AutoProcessor, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast
  
  
  @require_vision
  class 							__snake_case    (				unittest.TestCase       ):
  
  
  
  
  
  	def      _snake_case      (		self		)			->		List[str]:
  		snake_case__  					=      tempfile.mkdtemp()
  
  		snake_case__  					=      CLIPImageProcessor()
  		snake_case__  					=      BertTokenizer.from_pretrained(
  		    'hf-internal-testing/tiny-random-BertModel'			,					model_input_names=['input_ids', 'attention_mask']		)
  
  		snake_case__  					=      GitProcessor(_lowerCamelCase			,					_lowerCamelCase		)
  
  		processor.save_pretrained(self.tmpdirname		)
  
  
  
  
  
  	def      _snake_case      (		self			,					**UpperCamelCase_		)			->		Optional[Any]:
  		return AutoProcessor.from_pretrained(self.tmpdirname			,					**_lowerCamelCase		).tokenizer
  
  
  
  
  
  	def      _snake_case      (		self			,					**UpperCamelCase_		)			->		Dict:
  		return AutoProcessor.from_pretrained(self.tmpdirname			,					**_lowerCamelCase		).image_processor
  
  
  
  
  
  	def      _snake_case      (		self		)			->		Any:
  		shutil.rmtree(self.tmpdirname		)
  
  
  
  
  
  	def      _snake_case      (		self		)			->		int:
  		snake_case__  					=      [np.random.randint(255			,					size=(3, 30, 400)			,					dtype=np.uinta		)]
  
  		snake_case__  					=      [Image.fromarray(np.moveaxis(_lowerCamelCase			,					0			,					-1		)		) for x in image_inputs]
  
  		return image_inputs
  
  
  
  
  
  	def      _snake_case      (		self		)			->		List[Any]:
  		snake_case__  					=      GitProcessor(tokenizer=self.get_tokenizer()			,					image_processor=self.get_image_processor()		)
  		processor.save_pretrained(self.tmpdirname		)
  
  		snake_case__  					=      self.get_tokenizer(bos_token='(BOS)'			,					eos_token='(EOS)'		)
  		snake_case__  					=      self.get_image_processor(do_normalize=_lowerCamelCase			,					padding_value=1.0		)
  
  		snake_case__  					=      GitProcessor.from_pretrained(
  		    self.tmpdirname			,					bos_token='(BOS)'			,					eos_token='(EOS)'			,					do_normalize=_lowerCamelCase			,					padding_value=1.0		)
  
  		self.assertEqual(processor.tokenizer.get_vocab()			,					tokenizer_add_kwargs.get_vocab()		)
  		self.assertIsInstance(processor.tokenizer			,					_lowerCamelCase		)
  
  		self.assertEqual(processor.image_processor.to_json_string()			,					image_processor_add_kwargs.to_json_string()		)
  		self.assertIsInstance(processor.image_processor			,					_lowerCamelCase		)
  
  
  
  
  
  	def      _snake_case      (		self		)			->		Dict:
  		snake_case__  					=      self.get_image_processor()
  		snake_case__  					=      self.get_tokenizer()
  
  		snake_case__  					=      GitProcessor(tokenizer=_lowerCamelCase			,					image_processor=_lowerCamelCase		)
  
  		snake_case__  					=      self.prepare_image_inputs()
  
  		snake_case__  					=      image_processor(_lowerCamelCase			,					return_tensors='np'		)
  		snake_case__  					=      processor(images=_lowerCamelCase			,					return_tensors='np'		)
  
  		for key in input_feat_extract.keys():
  			self.assertAlmostEqual(input_feat_extract[key].sum()			,					input_processor[key].sum()			,					delta=1E-2		)
  
  
  
  
  
  	def      _snake_case      (		self		)			->		Optional[int]:
  		snake_case__  					=      self.get_image_processor()
  		snake_case__  					=      self.get_tokenizer()
  
  		snake_case__  					=      GitProcessor(tokenizer=_lowerCamelCase			,					image_processor=_lowerCamelCase		)
  
  		snake_case__  					=      """lower newer"""
  
  		snake_case__  					=      processor(text=_lowerCamelCase		)
  
  		snake_case__  					=      tokenizer(_lowerCamelCase			,					return_token_type_ids=_lowerCamelCase		)
  
  		for key in encoded_tok.keys():
  			self.assertListEqual(encoded_tok[key]			,					encoded_processor[key]		)
  
  
  
  
  
  	def      _snake_case      (		self		)			->		List[Any]:
  		snake_case__  					=      self.get_image_processor()
  		snake_case__  					=      self.get_tokenizer()
  
  		snake_case__  					=      GitProcessor(tokenizer=_lowerCamelCase			,					image_processor=_lowerCamelCase		)
  
  		snake_case__  					=      """lower newer"""
  		snake_case__  					=      self.prepare_image_inputs()
  
  		snake_case__  					=      processor(text=_lowerCamelCase			,					images=_lowerCamelCase		)
  
  		self.assertListEqual(list(inputs.keys()		)			,					['input_ids', 'attention_mask', 'pixel_values']		)
  
  		# test if it raises when no input is passed
  		with pytest.raises(_lowerCamelCase		):
  			processor()
  
  
  
  
  
  	def      _snake_case      (		self		)			->		str:
  		snake_case__  					=      self.get_image_processor()
  		snake_case__  					=      self.get_tokenizer()
  
  		snake_case__  					=      GitProcessor(tokenizer=_lowerCamelCase			,					image_processor=_lowerCamelCase		)
  
  		snake_case__  					=      [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]
  
  		snake_case__  					=      processor.batch_decode(_lowerCamelCase		)
  		snake_case__  					=      tokenizer.batch_decode(_lowerCamelCase		)
  
  		self.assertListEqual(_lowerCamelCase			,					_lowerCamelCase		)
  
  
  
  
  
  	def      _snake_case      (		self		)			->		Tuple:
  		snake_case__  					=      self.get_image_processor()
  		snake_case__  					=      self.get_tokenizer()
  
  		snake_case__  					=      GitProcessor(tokenizer=_lowerCamelCase			,					image_processor=_lowerCamelCase		)
  
  		snake_case__  					=      """lower newer"""
  		snake_case__  					=      self.prepare_image_inputs()
  
  		snake_case__  					=      processor(text=_lowerCamelCase			,					images=_lowerCamelCase		)
  
  		# For now the processor supports only ['input_ids', 'attention_mask', 'pixel_values']
  		self.assertListEqual(list(inputs.keys()		)			,					['input_ids', 'attention_mask', 'pixel_values']		)
  
  
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  
  
  
  def 	__lowerCamelCase (  UpperCAmelCase_       )      ->int:
  	return 1 if input_a == 0 else 0
  
  
  
  
  def 	__lowerCamelCase (  )      ->None:
  	assert not_gate(0       ) == 1
  	assert not_gate(1       ) == 0
  
  
  if __name__ == "__main__":
  			print(not_gate(0))
  			print(not_gate(1))
  
  
  
  