
'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

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


__lowercase							:   Dict					=     logging.get_logger(__name__)

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

class 	__lowercase				(  _lowercase    ):
			lowerCamelCase			:		Tuple	      =			"roberta-prelayernorm"

			def __init__(self			,   A=5_0_2_6_5			,   A=7_6_8			,   A=1_2			,   A=1_2			,   A=3_0_7_2			,   A="gelu"			,   A=0.1			,   A=0.1			,   A=5_1_2			,   A=2			,   A=0.02			,   A=1E-12			,   A=1			,   A=0			,   A=2			,   A="absolute"			,   A=True			,   A=None			,   **A			,   ):
								super().__init__(pad_token_id=A			,   bos_token_id=A			,   eos_token_id=A			,   **A      )

								lowerCamelCase_					:      int     =		vocab_size
								lowerCamelCase_					:      int     =		hidden_size
								lowerCamelCase_					:      Optional[Any]     =		num_hidden_layers
								lowerCamelCase_					:      str     =		num_attention_heads
								lowerCamelCase_					:      List[Any]     =		hidden_act
								lowerCamelCase_					:      Optional[Any]     =		intermediate_size
								lowerCamelCase_					:      List[Any]     =		hidden_dropout_prob
								lowerCamelCase_					:      Optional[Any]     =		attention_probs_dropout_prob
								lowerCamelCase_					:      Dict     =		max_position_embeddings
								lowerCamelCase_					:      List[str]     =		type_vocab_size
								lowerCamelCase_					:      Any     =		initializer_range
								lowerCamelCase_					:      str     =		layer_norm_eps
								lowerCamelCase_					:      List[str]     =		position_embedding_type
								lowerCamelCase_					:      List[str]     =		use_cache
								lowerCamelCase_					:      Optional[Any]     =		classifier_dropout

class 	__lowercase				(  _lowercase    ):

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




'''simple docstring'''


def lowercase_	(   _lowercase = 1_000				)     ->							int:
					'''simple docstring'''

					lowerCamelCase_					:      Dict     =		2**power
					lowerCamelCase_					:      Union[str, Any]     =		str(_lowercase				)
					lowerCamelCase_					:      Union[str, Any]     =		list(_lowercase				)
					lowerCamelCase_					:      Dict     =		0

					for i in list_num:
										sum_of_num += int(_lowercase				)

					return sum_of_num


if __name__ == "__main__":
					__lowercase							:   Optional[Any]					=     int(input('''Enter the power of 2: ''').strip())
					print('''2 ^ ''', power, ''' = ''', 2**power)
					__lowercase							:   Tuple					=     solution(power)
					print('''Sum of the digits is: ''', result)


