
"""simple docstring"""

import random
def 		UpperCAmelCase (		a_,						a_,						a_      ):





		'''simple docstring'''


		lowerCamelCase					:      Union[str, Any]          =   a[left_index]
		lowerCamelCase					:      Tuple          =   left_index + 1
		for j in range(left_index + 1,						a_      ):
				if a[j] < pivot:
						lowerCamelCase     ,   lowerCamelCase					:      Union[str, Any]          =   a[i], a[j]
						i += 1
		lowerCamelCase     ,   lowerCamelCase					:      Optional[Any]          =   a[i - 1], a[left_index]
		return i - 1
def 		UpperCAmelCase (		a_,						a_,						a_      ):





		'''simple docstring'''


		if left < right:
				lowerCamelCase					:      int          =   random.randint(a_,						right - 1      )
				lowerCamelCase     ,   lowerCamelCase					:      int          =   (
				    a[left],
				    a[pivot],
				)  # switches the pivot with the left most bound
				lowerCamelCase					:      Tuple          =   partition(a_,						a_,						a_      )
				quick_sort_random(
				    a_,						a_,						a_      )  # recursive quicksort to the left of the pivot point
				quick_sort_random(
				    a_,						pivot_index + 1,						a_      )  # recursive quicksort to the right of the pivot point
def 		UpperCAmelCase (		):





		'''simple docstring'''


		lowerCamelCase					:      str          =   input('Enter numbers separated by a comma:\n'      ).strip()
		lowerCamelCase					:      Optional[int]          =   [int(a_      ) for item in user_input.split(','      )]

		quick_sort_random(a_,						0,						len(a_      )      )

		print(a_      )


if __name__ == "__main__":
					main()








"""simple docstring"""

import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_A						=			logging.get_logger(__name__)






class 	_lowercase       (    __UpperCAmelCase		):
	lowercase_				=     'encoder-decoder'
	lowercase_				=     True




	def __init__(			self		,			**UpperCAmelCase_ )		->							str:
			super().__init__(**UpperCAmelCase_ )
			assert (
			    "encoder" in kwargs and "decoder" in kwargs
			), "Config has to be initialized with encoder and decoder config"
			lowerCamelCase					:      List[Any]          =   kwargs.pop('encoder' )
			lowerCamelCase					:      Optional[int]          =   encoder_config.pop('model_type' )
			lowerCamelCase					:      str          =   kwargs.pop('decoder' )
			lowerCamelCase					:      Dict          =   decoder_config.pop('model_type' )

			from ..auto.configuration_auto import AutoConfig

			lowerCamelCase					:      int          =   AutoConfig.for_model(UpperCAmelCase_		,			**UpperCAmelCase_ )
			lowerCamelCase					:      List[str]          =   AutoConfig.for_model(UpperCAmelCase_		,			**UpperCAmelCase_ )
			lowerCamelCase					:      List[str]          =   True




	@classmethod
	def       _UpperCamelCase   (			cls		,			UpperCAmelCase_		,			UpperCAmelCase_		,			**UpperCAmelCase_ )		->							PretrainedConfig:
			logger.info('Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config' )
			lowerCamelCase					:      str          =   True
			lowerCamelCase					:      Optional[Any]          =   True

			return cls(encoder=encoder_config.to_dict()		,			decoder=decoder_config.to_dict()		,			**UpperCAmelCase_ )




	def       _UpperCamelCase   (			self )		->							Union[str, Any]:
			lowerCamelCase					:      Union[str, Any]          =   copy.deepcopy(self.__dict__ )
			lowerCamelCase					:      Union[str, Any]          =   self.encoder.to_dict()
			lowerCamelCase					:      List[Any]          =   self.decoder.to_dict()
			lowerCamelCase					:      Tuple          =   self.__class__.model_type
			return output






