



"""simple docstring"""
import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class 					a	(  UpperCAmelCase__       ):
		UpperCamelCase	:				Tuple     						=					['image_processor', 'tokenizer']
		UpperCamelCase	:				Union[str, Any]     						=					'CLIPImageProcessor'
		UpperCamelCase	:				str     						=					('XLMRobertaTokenizer', 'XLMRobertaTokenizerFast')



		def __init__(						self :					Union[str, Any]       ,		lowerCAmelCase :					Union[str, Any]=None       ,		lowerCAmelCase :					Optional[int]=None       ,		**lowerCAmelCase :					List[str]		)     ->					Dict:


					'''simple docstring'''




					SCREAMING_SNAKE_CASE_: List[str]     			=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_: Tuple     			=kwargs.pop("""feature_extractor"""		)

					SCREAMING_SNAKE_CASE_: Any     			=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		)



		def __call__(						self :					List[Any]       ,		lowerCAmelCase :					Optional[Any]=None       ,		lowerCAmelCase :					List[Any]=None       ,		lowerCAmelCase :					Union[str, Any]=None       ,		**lowerCAmelCase :					Optional[Any]		)     ->					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:
								SCREAMING_SNAKE_CASE_: Optional[int]     			=self.tokenizer(lowerCAmelCase       ,		return_tensors=lowerCAmelCase       ,		**lowerCAmelCase		)

					if images is not None:
								SCREAMING_SNAKE_CASE_: str     			=self.image_processor(lowerCAmelCase       ,		return_tensors=lowerCAmelCase       ,		**lowerCAmelCase		)

					if text is not None and images is not None:
								SCREAMING_SNAKE_CASE_: Optional[Any]     			=image_features.pixel_values
								return encoding
					elif text is not None:
								return encoding
					else:
								return BatchEncoding(data=dict(**lowerCAmelCase		)       ,		tensor_type=lowerCAmelCase		)



		def 	lowerCamelCase__       (						self :					List[Any]       ,		*lowerCAmelCase :					Tuple       ,		**lowerCAmelCase :					Tuple		)     ->					List[Any]:


					'''simple docstring'''




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



		def 	lowerCamelCase__       (						self :					Dict       ,		*lowerCAmelCase :					Dict       ,		**lowerCAmelCase :					List[Any]		)     ->					int:


					'''simple docstring'''




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





		@property
		def 	lowerCamelCase__       (						self :					Union[str, Any]		)     ->					str:


					'''simple docstring'''




					SCREAMING_SNAKE_CASE_: Optional[Any]     			=self.tokenizer.model_input_names
					SCREAMING_SNAKE_CASE_: int     			=self.image_processor.model_input_names
					return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names		)		)








"""simple docstring"""
def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: int     			=False
   while is_sorted is False:  # Until all the indices are traversed keep looping
      SCREAMING_SNAKE_CASE_: Tuple     			=True
      for i in range(0							,			len(lowercase ) - 1							,			2 ):  # iterating over all even indices
         if input_list[i] > input_list[i + 1]:
            SCREAMING_SNAKE_CASE_			,		SCREAMING_SNAKE_CASE_: Optional[int]     			=input_list[i + 1], input_list[i]
            # swapping if elements not in order
            SCREAMING_SNAKE_CASE_: Tuple     			=False

      for i in range(1							,			len(lowercase ) - 1							,			2 ):  # iterating over all odd indices
         if input_list[i] > input_list[i + 1]:
            SCREAMING_SNAKE_CASE_			,		SCREAMING_SNAKE_CASE_: str     			=input_list[i + 1], input_list[i]
            # swapping if elements not in order
            SCREAMING_SNAKE_CASE_: str     			=False
   return input_list


if __name__ == "__main__":
   print("""Enter list to be sorted""")
   _UpperCAmelCase     =			[int(x) for x in input().split()]
   # inputing elements of the list in one line
   _UpperCAmelCase     =			odd_even_sort(input_list)
   print("""The sorted list is""")
   print(sorted_list)



