from __future__ import annotations

import bisect






def _lowerCamelCase  (		snake_case     , snake_case     , snake_case = 0     , snake_case = -1  ):
							if hi < 0:
														_lowerCAmelCase							=							len(snake_case  )

							while lo < hi:
														_lowerCAmelCase							=							lo + (hi - lo) // 2
														if sorted_collection[mid] < item:
																					_lowerCAmelCase							=							mid + 1
														else:
																					_lowerCAmelCase							=							mid

							return lo






def _lowerCamelCase  (		snake_case     , snake_case     , snake_case = 0     , snake_case = -1  ):
							if hi < 0:
														_lowerCAmelCase							=							len(snake_case  )

							while lo < hi:
														_lowerCAmelCase							=							lo + (hi - lo) // 2
														if sorted_collection[mid] <= item:
																					_lowerCAmelCase							=							mid + 1
														else:
																					_lowerCAmelCase							=							mid

							return lo






def _lowerCamelCase  (		snake_case     , snake_case     , snake_case = 0     , snake_case = -1  ):
							sorted_collection.insert(bisect_left(snake_case     , snake_case     , snake_case     , snake_case  )     , snake_case  )






def _lowerCamelCase  (		snake_case     , snake_case     , snake_case = 0     , snake_case = -1  ):
							sorted_collection.insert(bisect_right(snake_case     , snake_case     , snake_case     , snake_case  )     , snake_case  )






def _lowerCamelCase  (		snake_case     , snake_case  ):
							_lowerCAmelCase							=							0
							_lowerCAmelCase							=							len(snake_case  ) - 1

							while left <= right:
														_lowerCAmelCase							=							left + (right - left) // 2
														_lowerCAmelCase							=							sorted_collection[midpoint]
														if current_item == item:
																					return midpoint
														elif item < current_item:
																					_lowerCAmelCase							=							midpoint - 1
														else:
																					_lowerCAmelCase							=							midpoint + 1
							return None






def _lowerCamelCase  (		snake_case     , snake_case  ):
							_lowerCAmelCase							=							bisect.bisect_left(snake_case     , snake_case  )
							if index != len(snake_case  ) and sorted_collection[index] == item:
														return index
							return None






def _lowerCamelCase  (		snake_case     , snake_case     , snake_case     , snake_case  ):
							if right < left:
														return None

							_lowerCAmelCase							=							left + (right - left) // 2

							if sorted_collection[midpoint] == item:
														return midpoint
							elif sorted_collection[midpoint] > item:
														return binary_search_by_recursion(snake_case     , snake_case     , snake_case     , midpoint - 1  )
							else:
														return binary_search_by_recursion(snake_case     , snake_case     , midpoint + 1     , snake_case  )


if __name__ == "__main__":
				_lowercase:	List[Any]       			=		input('''Enter numbers separated by comma:\n''').strip()
				_lowercase:	List[str]       			=		sorted(int(item) for item in user_input.split(''','''))
				_lowercase:	int       			=		int(input('''Enter a single number to be found in the list:\n'''))
				_lowercase:	Dict       			=		binary_search(collection, target)
				if result is None:
								print(f"""{target} was not found in {collection}.""")
				else:
								print(f"""{target} was found at position {result} in {collection}.""")







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowercase:	Optional[Any]       			=		logging.get_logger(__name__)

_lowercase:	Tuple       			=		{
    '''andreasmadsen/efficient_mlm_m0.40''': (
        '''https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'''
    ),
}



class        lowerCamelCase__				(   UpperCAmelCase				):
			UpperCamelCase__    							="roberta-prelayernorm"





			def __init__(       self	:	int  ,  lowercase__	:	int=5_02_65  ,  lowercase__	:	str=7_68  ,  lowercase__	:	List[Any]=12  ,  lowercase__	:	Any=12  ,  lowercase__	:	Optional[Any]=30_72  ,  lowercase__	:	List[Any]="gelu"  ,  lowercase__	:	str=0.1  ,  lowercase__	:	List[Any]=0.1  ,  lowercase__	:	Tuple=5_12  ,  lowercase__	:	Optional[int]=2  ,  lowercase__	:	Dict=0.0_2  ,  lowercase__	:	Tuple=1e-12  ,  lowercase__	:	Optional[int]=1  ,  lowercase__	:	Optional[int]=0  ,  lowercase__	:	Union[str, Any]=2  ,  lowercase__	:	Any="absolute"  ,  lowercase__	:	Any=True  ,  lowercase__	:	Any=None  ,  **lowercase__	:	Optional[int]  ,  ):
										super().__init__(pad_token_id=lowercase__  ,  bos_token_id=lowercase__  ,  eos_token_id=lowercase__  ,  **lowercase__						)

										_lowerCAmelCase							=							vocab_size
										_lowerCAmelCase							=							hidden_size
										_lowerCAmelCase							=							num_hidden_layers
										_lowerCAmelCase							=							num_attention_heads
										_lowerCAmelCase							=							hidden_act
										_lowerCAmelCase							=							intermediate_size
										_lowerCAmelCase							=							hidden_dropout_prob
										_lowerCAmelCase							=							attention_probs_dropout_prob
										_lowerCAmelCase							=							max_position_embeddings
										_lowerCAmelCase							=							type_vocab_size
										_lowerCAmelCase							=							initializer_range
										_lowerCAmelCase							=							layer_norm_eps
										_lowerCAmelCase							=							position_embedding_type
										_lowerCAmelCase							=							use_cache
										_lowerCAmelCase							=							classifier_dropout







class        lowerCamelCase__				(   UpperCAmelCase				):





			@property
			def   SCREAMING_SNAKE_CASE__     (       self	:	List[str]						):
										if self.task == "multiple-choice":
																	_lowerCAmelCase							=							{0: 'batch', 1: 'choice', 2: 'sequence'}
										else:
																	_lowerCAmelCase							=							{0: 'batch', 1: 'sequence'}
										return OrderedDict(
										    [
										        ('input_ids', dynamic_axis),
										        ('attention_mask', dynamic_axis),
										    ]						)






