



"""simple docstring"""






from __future__ import annotations






def 	snake_case__  (						__lowerCamelCase							:       Any				,						__lowerCamelCase							:       Tuple      ):
			"""simple docstring"""
			lowerCamelCase__						:						Union[str, Any]						      =0
			lowerCamelCase__						:						int						      =len(snake_case_      ) - 1
			while left <= right:
						lowerCamelCase__						:						Any						      =(left + right) // 2
						if left == right:
									if sorted_list[middle] < item:
												lowerCamelCase__						:						Optional[int]						      =middle + 1
									break
						elif sorted_list[middle] < item:
									lowerCamelCase__						:						List[Any]						      =middle + 1
						else:
									lowerCamelCase__						:						Any						      =middle - 1
			sorted_list.insert(snake_case_				,						snake_case_      )
			return sorted_list






def 	snake_case__  (						__lowerCamelCase							:       Dict				,						__lowerCamelCase							:       Dict      ):
			"""simple docstring"""
			lowerCamelCase__						:						List[Any]						      =[]
			while left and right:
						if left[0][0] < right[0][0]:
									result.append(left.pop(0      )      )
						else:
									result.append(right.pop(0      )      )
			return result + left + right






def 	snake_case__  (						__lowerCamelCase							:       Any      ):
			"""simple docstring"""
			lowerCamelCase__						:						int						      =len(snake_case_      )
			if length <= 1:
						return list_ad
			lowerCamelCase__						:						Optional[Any]						      =length // 2
			return merge(sortlist_ad(list_ad[:middle]      )				,						sortlist_ad(list_ad[middle:]      )      )






def 	snake_case__  (						__lowerCamelCase							:       list[int]      ):
			"""simple docstring"""



			if len(snake_case_      ) <= 1:
						return collection
			lowerCamelCase__						:						Union[str, Any]						      =[]
			lowerCamelCase__						:						Union[str, Any]						      =False
			for i in range(0				,						len(snake_case_      )				,						2      ):
						if i == len(snake_case_      ) - 1:
									lowerCamelCase__						:						Tuple						      =True
						else:
									if collection[i] < collection[i + 1]:
												two_paired_list.append([collection[i], collection[i + 1]]      )
									else:
												two_paired_list.append([collection[i + 1], collection[i]]      )
			lowerCamelCase__						:						str						      =sortlist_ad(snake_case_      )
			lowerCamelCase__						:						Dict						      =[i[0] for i in sorted_list_ad]
			result.append(sorted_list_ad[-1][1]      )
			if has_last_odd_item:
						lowerCamelCase__						:						Dict						      =collection[-1]
						lowerCamelCase__						:						List[Any]						      =binary_search_insertion(snake_case_				,						snake_case_      )
			lowerCamelCase__						:						Dict						      =False
			for i in range(len(snake_case_      ) - 1      ):
						if result[i] == collection[-1] and has_last_odd_item:
									lowerCamelCase__						:						List[Any]						      =True
						lowerCamelCase__						:						Tuple						      =sorted_list_ad[i][1]
						# If last_odd_item is inserted before the item's index,
						# you should forward index one more.
						if is_last_odd_item_inserted_before_this_index:
									lowerCamelCase__						:						int						      =result[: i + 2] + binary_search_insertion(result[i + 2 :]				,						snake_case_      )
						else:
									lowerCamelCase__						:						List[Any]						      =result[: i + 1] + binary_search_insertion(result[i + 1 :]				,						snake_case_      )

			return result


if __name__ == "__main__":
		_lowercase					:					str 		=		input("Enter numbers separated by a comma:\n").strip()
		_lowercase					:					Any 		=		[int(item) for item in user_input.split(",")]
		print(merge_insertion_sort(unsorted))






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





class 		__lowerCamelCase     (   lowercase		):
							lowerCamelCase__:				Any      =							['''image_processor''', '''tokenizer''']
							lowerCamelCase__:				List[Any]      =							'''EfficientNetImageProcessor'''
							lowerCamelCase__:				str      =							('''BertTokenizer''', '''BertTokenizerFast''')



							def __init__(     self	,				__snake_case	,				__snake_case							)						->     Optional[Any]:






								"""simple docstring"""



								super().__init__(__snake_case	,				__snake_case							)



							def __call__(     self	,				__snake_case=None	,				__snake_case=None	,				__snake_case="max_length"	,				__snake_case=6_4	,				__snake_case=None	,				**__snake_case							)						->     Any:






								"""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:
									UpperCAmelCase:					Dict 						=     self.tokenizer(
									    __snake_case	,				padding=__snake_case	,				max_length=__snake_case	,				return_tensors=__snake_case	,				**__snake_case							)

								if images is not None:
									UpperCAmelCase:					List[str] 						=     self.image_processor(__snake_case	,				return_tensors=__snake_case	,				**__snake_case							)

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



							def     A__ (     self	,				*__snake_case	,				**__snake_case							)						->     Any:






								"""simple docstring"""



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



							def     A__ (     self	,				*__snake_case	,				**__snake_case							)						->     List[str]:






								"""simple docstring"""



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




							@property
							def     A__ (     self							)						->     Optional[int]:






								"""simple docstring"""



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