

import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding


class SCREAMING_SNAKE_CASE	(		__snake_case				):






			"""simple docstring"""




			__A    	=	["""image_processor""", """tokenizer"""]
			__A    	=	"""CLIPImageProcessor"""
			__A    	=	("""CLIPTokenizer""", """CLIPTokenizerFast""")


			def __init__(     self			,					__UpperCamelCase=None			,					__UpperCamelCase=None			,					**__UpperCamelCase				):

				"""simple docstring"""


				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.'			,					__UpperCamelCase			,					)
					snake_case_   		=			kwargs.pop('feature_extractor'				)

				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__(__UpperCamelCase			,					__UpperCamelCase				)


			def __call__(     self			,					__UpperCamelCase=None			,					__UpperCamelCase=None			,					__UpperCamelCase=None			,					**__UpperCamelCase				):

				"""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:
					snake_case_   		=			self.tokenizer(__UpperCamelCase			,					return_tensors=__UpperCamelCase			,					**__UpperCamelCase				)

				if images is not None:
					snake_case_   		=			self.image_processor(__UpperCamelCase			,					return_tensors=__UpperCamelCase			,					**__UpperCamelCase				)

				if text is not None and images is not None:
					snake_case_   		=			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				):

				"""simple docstring"""


				return self.tokenizer.batch_decode(*__UpperCamelCase			,					**__UpperCamelCase				)


			def       __lowerCAmelCase			(     self			,					*__UpperCamelCase			,					**__UpperCamelCase				):

				"""simple docstring"""


				return self.tokenizer.decode(*__UpperCamelCase			,					**__UpperCamelCase				)


			@property
			def       __lowerCAmelCase			(     self				):

				"""simple docstring"""


				snake_case_   		=			self.tokenizer.model_input_names
				snake_case_   		=			self.image_processor.model_input_names
				return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names				)				)


			@property
			def       __lowerCAmelCase			(     self				):

				"""simple docstring"""


				warnings.warn(
				    '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'			,					__UpperCamelCase			,					)
				return self.image_processor_class







			@property
			def       __lowerCAmelCase			(     self				):

				"""simple docstring"""


				warnings.warn(
				    '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'			,					__UpperCamelCase			,					)
				return self.image_processor



from __future__ import annotations





def a(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						):





	'''simple docstring'''
	if (direction == 1 and array[indexa] > array[indexa]) or (
	    direction == 0 and array[indexa] < array[indexa]
	):
		snake_case_		,							snake_case_   		=			array[indexa], array[indexa]





def a(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						):





	'''simple docstring'''
	if length > 1:
		snake_case_   		=			int(length / 2						)
		for i in range(lowercase__      ,			low + middle						):
			comp_and_swap(lowercase__      ,			lowercase__      ,			i + middle      ,			lowercase__						)
		bitonic_merge(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						)
		bitonic_merge(lowercase__      ,			low + middle      ,			lowercase__      ,			lowercase__						)





def a(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						):





	'''simple docstring'''
	if length > 1:
		snake_case_   		=			int(length / 2						)
		bitonic_sort(lowercase__      ,			lowercase__      ,			lowercase__      ,			1						)
		bitonic_sort(lowercase__      ,			low + middle      ,			lowercase__      ,			0						)
		bitonic_merge(lowercase__      ,			lowercase__      ,			lowercase__      ,			lowercase__						)


if __name__ == "__main__":
		A									=  input('Enter numbers separated by a comma:\n').strip()
		A									=  [int(item.strip()) for item in user_input.split(',')]

		bitonic_sort(unsorted, 0, len(unsorted), 1)
		print('\nSorted array in ascending order is: ', end='')
		print(*unsorted, sep=', ')

		bitonic_merge(unsorted, 0, len(unsorted), 0)
		print('Sorted array in descending order is: ', end='')
		print(*unsorted, sep=', ')
