from __future__ import annotations

def 							UpperCamelCase				(    lowerCAmelCase_       ,					lowerCAmelCase_   )		->						Union[str, Any]:




       '''simple docstring'''






       if nth_term == "":
              return [""]
       _A=	int(SCREAMING_SNAKE_CASE__   )
       _A=	int(SCREAMING_SNAKE_CASE__   )
       _A=	[]
       for temp in range(int(SCREAMING_SNAKE_CASE__   )   ):
              series.append(F"1 / {pow(temp + 1       ,					int(SCREAMING_SNAKE_CASE__   )   )}" if series else '1'   )
       return series


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      UpperCAmelCase_								=       int(input('''Enter the last number (nth term) of the P-Series'''))
      UpperCAmelCase_								=       int(input('''Enter the power for  P-Series'''))
      print('''Formula of P-Series => 1+1/2^p+1/3^p ..... 1/n^p''')
      print(p_series(nth_term, power))
from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase_								=							logging.get_logger(__name__)

UpperCAmelCase_								=							{
    '''YituTech/conv-bert-base''': '''https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json''',
    '''YituTech/conv-bert-medium-small''': (
        '''https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json'''
    ),
    '''YituTech/conv-bert-small''': '''https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json''',
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}





class      lowerCAmelCase						(					_a			):
     _SCREAMING_SNAKE_CASE     :     List[str]		="""convbert"""



     def __init__(					self				,      lowerCAmelCase__=30522				,      lowerCAmelCase__=768				,      lowerCAmelCase__=12				,      lowerCAmelCase__=12				,      lowerCAmelCase__=3072				,      lowerCAmelCase__="gelu"				,      lowerCAmelCase__=0.1				,      lowerCAmelCase__=0.1				,      lowerCAmelCase__=512				,      lowerCAmelCase__=2				,      lowerCAmelCase__=0.02				,      lowerCAmelCase__=1E-12				,      lowerCAmelCase__=1				,      lowerCAmelCase__=0				,      lowerCAmelCase__=2				,      lowerCAmelCase__=768				,      lowerCAmelCase__=2				,      lowerCAmelCase__=9				,      lowerCAmelCase__=1				,      lowerCAmelCase__=None				,      **lowerCAmelCase__				,      ):
            super().__init__(
                pad_token_id=lowerCAmelCase__				,      bos_token_id=lowerCAmelCase__				,      eos_token_id=lowerCAmelCase__				,      **lowerCAmelCase__				,      )

            _A=	vocab_size
            _A=	hidden_size
            _A=	num_hidden_layers
            _A=	num_attention_heads
            _A=	intermediate_size
            _A=	hidden_act
            _A=	hidden_dropout_prob
            _A=	attention_probs_dropout_prob
            _A=	max_position_embeddings
            _A=	type_vocab_size
            _A=	initializer_range
            _A=	layer_norm_eps
            _A=	embedding_size
            _A=	head_ratio
            _A=	conv_kernel_size
            _A=	num_groups
            _A=	classifier_dropout





class      lowerCAmelCase						(					_a			):



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