code: 
  
  
  from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import BatchEncoding
  
  
  
  class 			a      (      UpperCamelCase_   ):
  		__lowercase													=		["""image_processor""", """tokenizer"""]
  		__lowercase													=		"""EfficientNetImageProcessor"""
  		__lowercase													=		("""BertTokenizer""", """BertTokenizerFast""")
  
  
  
  
  
  
  		def __init__(  self	,     __UpperCamelCase	,     __UpperCamelCase							)->			List[Any]:
  						'''simple docstring'''
  
  
  						super().__init__(__UpperCamelCase	,     __UpperCamelCase							)
  
  
  
  
  
  
  		def __call__(  self	,     __UpperCamelCase=None	,     __UpperCamelCase=None	,     __UpperCamelCase="max_length"	,     __UpperCamelCase=64	,     __UpperCamelCase=None	,     **__UpperCamelCase							)->			Optional[int]:
  						'''simple docstring'''
  
  
  						if text is None and images is None:
  										raise ValueError('''You have to specify either text or images. Both cannot be none.'''							)
  
  						if text is not None:
  										A__     :							Tuple   				=self.tokenizer(
  										    __UpperCamelCase	,     padding=__UpperCamelCase	,     max_length=__UpperCamelCase	,     return_tensors=__UpperCamelCase	,     **__UpperCamelCase							)
  
  						if images is not None:
  										A__     :							List[Any]   				=self.image_processor(__UpperCamelCase	,     return_tensors=__UpperCamelCase	,     **__UpperCamelCase							)
  
  						if text is not None and images is not None:
  										A__     :							Optional[Any]   				=image_features.pixel_values
  										return encoding
  						elif text is not None:
  										return encoding
  						else:
  										return BatchEncoding(data=dict(**__UpperCamelCase							)	,     tensor_type=__UpperCamelCase							)
  
  
  
  
  
  
  		def       lowerCAmelCase_  (  self	,     *__UpperCamelCase	,     **__UpperCamelCase							)->			List[Any]:
  						'''simple docstring'''
  
  
  						return self.tokenizer.batch_decode(*__UpperCamelCase	,     **__UpperCamelCase							)
  
  
  
  
  
  
  		def       lowerCAmelCase_  (  self	,     *__UpperCamelCase	,     **__UpperCamelCase							)->			Union[str, Any]:
  						'''simple docstring'''
  
  
  						return self.tokenizer.decode(*__UpperCamelCase	,     **__UpperCamelCase							)
  
  
  
  
  
  
  		@property
  		def       lowerCAmelCase_  (  self							)->			Dict:
  						'''simple docstring'''
  
  
  						A__     :							int   				=self.tokenizer.model_input_names
  						A__     :							List[Any]   				=self.image_processor.model_input_names
  						return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)
  
  
  
  
style_context: 
  
  
  from __future__ import annotations
  
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_	)			->							list[int]:
  				A__     :							Optional[int]   				=[0] * len(snake_case_	)
  				for i in range(1,	len(snake_case_	)	):
  								A__     :							List[Any]   				=duration_times[i - 1] + waiting_times[i - 1]
  				return waiting_times
  
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_,	snake_case_	)			->							list[int]:
  				return [
  				    duration_time + waiting_times[i]
  				    for i, duration_time in enumerate(snake_case_	)
  				]
  
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_	)			->							float:
  				return sum(snake_case_	) / len(snake_case_	)
  
  
  
  def   SCREAMING_SNAKE_CASE__						(							snake_case_	)			->							float:
  				return sum(snake_case_	) / len(snake_case_	)
  
  
  if __name__ == "__main__":
  						# process id's
  						__lowerCamelCase       :       List[str]				   =			[1, 2, 3]
  
  						# ensure that we actually have processes
  						if len(processes) == 0:
  												print("Zero amount of processes")
  												raise SystemExit(0)
  
  						# duration time of all processes
  						__lowerCamelCase       :       Dict				   =			[19, 8, 9]
  
  						# ensure we can match each id to a duration time
  						if len(duration_times) != len(processes):
  												print("Unable to match all id's with their duration time")
  												raise SystemExit(0)
  
  						# get the waiting times and the turnaround times
  						__lowerCamelCase       :       int				   =			calculate_waiting_times(duration_times)
  						__lowerCamelCase       :       Optional[int]				   =			calculate_turnaround_times(duration_times, waiting_times)
  
  						# get the average times
  						__lowerCamelCase       :       List[str]				   =			calculate_average_waiting_time(waiting_times)
  						__lowerCamelCase       :       Dict				   =			calculate_average_turnaround_time(turnaround_times)
  
  						# print all the results
  						print("Process ID\tDuration Time\tWaiting Time\tTurnaround Time")
  						for i, process in enumerate(processes):
  												print(
  												    F"{process}\t\t{duration_times[i]}\t\t{waiting_times[i]}\t\t"
  												    F"{turnaround_times[i]}"
  												)
  						print(F"Average waiting time = {average_waiting_time}")
  						print(F"Average turn around time = {average_turnaround_time}")
  
  
  
  