code: 
  
  
  import warnings
  from contextlib import contextmanager
  
  from ...processing_utils import ProcessorMixin
  
  class 						snake_case			(       lowerCAmelCase__	):
  			'''simple docstring'''
  
  			UpperCAmelCase       :       Union[str, Any]       = ["""image_processor""", """tokenizer"""]
  			UpperCAmelCase       :       Any       = """AutoImageProcessor"""
  			UpperCAmelCase       :       str       = """AutoTokenizer"""
  
  			def __init__(	self     :     Tuple							,							lowerCAmelCase_     :     Dict=None							,							lowerCAmelCase_     :     Any=None							,							**lowerCAmelCase_     :     Tuple					)					->					Optional[Any]:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								SCREAMING_SNAKE_CASE_	      =       None
  								if "feature_extractor" in kwargs:
  													warnings.warn(
  													    '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
  													    ''' instead.'''							,							lowerCAmelCase_							,							)
  													SCREAMING_SNAKE_CASE_	      =       kwargs.pop('''feature_extractor'''					)
  
  								SCREAMING_SNAKE_CASE_	      =       image_processor if image_processor is not None else feature_extractor
  								if image_processor is None:
  													raise ValueError('''You need to specify an `image_processor`.'''					)
  								if tokenizer is None:
  													raise ValueError('''You need to specify a `tokenizer`.'''					)
  
  								super().__init__(lowerCAmelCase_							,							lowerCAmelCase_					)
  								SCREAMING_SNAKE_CASE_	      =       self.image_processor
  								SCREAMING_SNAKE_CASE_	      =       False
  
  			def __call__(	self     :     Union[str, Any]							,							*lowerCAmelCase_     :     int							,							**lowerCAmelCase_     :     Union[str, Any]					)					->					str:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								if self._in_target_context_manager:
  													return self.current_processor(*lowerCAmelCase_							,							**lowerCAmelCase_					)
  
  								SCREAMING_SNAKE_CASE_	      =       kwargs.pop('''images'''							,							lowerCAmelCase_					)
  								SCREAMING_SNAKE_CASE_	      =       kwargs.pop('''text'''							,							lowerCAmelCase_					)
  								if len(lowerCAmelCase_					) > 0:
  													SCREAMING_SNAKE_CASE_	      =       args[0]
  													SCREAMING_SNAKE_CASE_	      =       args[1:]
  
  								if images is None and text is None:
  													raise ValueError('''You need to specify either an `images` or `text` input to process.'''					)
  
  								if images is not None:
  													SCREAMING_SNAKE_CASE_	      =       self.image_processor(lowerCAmelCase_							,							*lowerCAmelCase_							,							**lowerCAmelCase_					)
  								if text is not None:
  													SCREAMING_SNAKE_CASE_	      =       self.tokenizer(lowerCAmelCase_							,							**lowerCAmelCase_					)
  
  								if text is None:
  													return inputs
  								elif images is None:
  													return encodings
  								else:
  													SCREAMING_SNAKE_CASE_	      =       encodings['''input_ids''']
  													return inputs
  
  			def _lowercase (	self     :     Any							,							*lowerCAmelCase_     :     Any							,							**lowerCAmelCase_     :     Dict					)					->					Dict:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								return self.tokenizer.batch_decode(*lowerCAmelCase_							,							**lowerCAmelCase_					)
  
  			def _lowercase (	self     :     Union[str, Any]							,							*lowerCAmelCase_     :     Any							,							**lowerCAmelCase_     :     int					)					->					int:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								return self.tokenizer.decode(*lowerCAmelCase_							,							**lowerCAmelCase_					)
  
  			@contextmanager
  			def _lowercase (	self     :     Any					)					->					List[Any]:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								warnings.warn(
  								    '''`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '''
  								    '''labels by using the argument `text` of the regular `__call__` method (either in the same call as '''
  								    '''your images inputs, or in a separate call.'''					)
  								SCREAMING_SNAKE_CASE_	      =       True
  								SCREAMING_SNAKE_CASE_	      =       self.tokenizer
  								yield
  								SCREAMING_SNAKE_CASE_	      =       self.image_processor
  								SCREAMING_SNAKE_CASE_	      =       False
  
  			@property
  			def _lowercase (	self     :     Dict					)					->					Optional[int]:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								warnings.warn(
  								    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''							,							lowerCAmelCase_							,							)
  								return self.image_processor_class
  
  
  
  
  			@property
  			def _lowercase (	self     :     Any					)					->					Tuple:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								warnings.warn(
  								    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''							,							lowerCAmelCase_							,							)
  								return self.image_processor
  
  
  
style_context: 
  
  
  import unittest
  
  from transformers import load_tool
  from transformers.tools.agent_types import AGENT_TYPE_MAPPING
  
  from .test_tools_common import ToolTesterMixin, output_types
  
  class 						snake_case			(       unittest.TestCase	, lowerCAmelCase__	):
  			'''simple docstring'''
  
  			def _lowercase (	self     :     List[Any]					)					->					Optional[Any]:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								SCREAMING_SNAKE_CASE_	      =       load_tool('''translation'''					)
  								self.tool.setup()
  								SCREAMING_SNAKE_CASE_	      =       load_tool('''translation'''							,							remote=lowerCAmelCase_					)
  
  			def _lowercase (	self     :     Tuple					)					->					str:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								SCREAMING_SNAKE_CASE_	      =       self.tool('''Hey, what\'s up?'''							,							src_lang='''English'''							,							tgt_lang='''French'''					)
  								self.assertEqual(lowerCAmelCase_							,							'''- Hé, comment ça va?'''					)
  
  			def _lowercase (	self     :     Optional[Any]					)					->					int:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								SCREAMING_SNAKE_CASE_	      =       self.remote_tool('''Hey, what\'s up?'''							,							src_lang='''English'''							,							tgt_lang='''French'''					)
  								self.assertEqual(lowerCAmelCase_							,							'''- Hé, comment ça va?'''					)
  
  			def _lowercase (	self     :     Optional[int]					)					->					str:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								SCREAMING_SNAKE_CASE_	      =       self.tool(text='''Hey, what\'s up?'''							,							src_lang='''English'''							,							tgt_lang='''French'''					)
  								self.assertEqual(lowerCAmelCase_							,							'''- Hé, comment ça va?'''					)
  
  			def _lowercase (	self     :     str					)					->					List[str]:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								SCREAMING_SNAKE_CASE_	      =       self.remote_tool(text='''Hey, what\'s up?'''							,							src_lang='''English'''							,							tgt_lang='''French'''					)
  								self.assertEqual(lowerCAmelCase_							,							'''- Hé, comment ça va?'''					)
  
  			def _lowercase (	self     :     Optional[int]					)					->					Dict:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								SCREAMING_SNAKE_CASE_	      =       ['''Hey, what\'s up?''', '''English''', '''Spanish''']
  								SCREAMING_SNAKE_CASE_	      =       self.tool(*lowerCAmelCase_					)
  
  								# There is a single output
  								if len(self.tool.outputs					) == 1:
  													SCREAMING_SNAKE_CASE_	      =       [outputs]
  
  								self.assertListEqual(output_types(lowerCAmelCase_					)							,							self.tool.outputs					)
  
  			def _lowercase (	self     :     Optional[int]					)					->					List[str]:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								SCREAMING_SNAKE_CASE_	      =       ['''Hey, what\'s up?''', '''English''', '''Spanish''']
  								SCREAMING_SNAKE_CASE_	      =       self.tool(*lowerCAmelCase_					)
  
  								if not isinstance(lowerCAmelCase_							,							lowerCAmelCase_					):
  													SCREAMING_SNAKE_CASE_	      =       [outputs]
  
  								self.assertEqual(len(lowerCAmelCase_					)							,							len(self.tool.outputs					)					)
  
  								for output, output_type in zip(lowerCAmelCase_							,							self.tool.outputs					):
  													SCREAMING_SNAKE_CASE_	      =       AGENT_TYPE_MAPPING[output_type]
  													self.assertTrue(isinstance(lowerCAmelCase_							,							lowerCAmelCase_					)					)
  
  
  
  
  			def _lowercase (	self     :     Tuple					)					->					int:
  
  
  
  
  								"""simple docstring"""
  
  
  
  
  
  
  								SCREAMING_SNAKE_CASE_	      =       ['''Hey, what\'s up?''', '''English''', '''Spanish''']
  
  								SCREAMING_SNAKE_CASE_	      =       []
  
  								for _input, input_type in zip(lowerCAmelCase_							,							self.tool.inputs					):
  													if isinstance(lowerCAmelCase_							,							lowerCAmelCase_					):
  																		_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input					) for _input_type in input_type]					)
  													else:
  																		_inputs.append(AGENT_TYPE_MAPPING[input_type](_input					)					)
  
          # Should not raise an error
  								SCREAMING_SNAKE_CASE_	      =       self.tool(*lowerCAmelCase_					)
  
  								if not isinstance(lowerCAmelCase_							,							lowerCAmelCase_					):
  													SCREAMING_SNAKE_CASE_	      =       [outputs]
  
  								self.assertEqual(len(lowerCAmelCase_					)							,							len(self.tool.outputs					)					)
  
  
  