


"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE					:       Any							   =							logging.get_logger(__name__)

SCREAMING_SNAKE_CASE					:       Optional[Any]							   =							{
    """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/config.json""",
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}



class      _UpperCAmelCase					(				__snake_case							):






		'''simple docstring'''

		lowerCamelCase__           ='rembert'



		def __init__(self							,			a_=25_03_00							,			a_=11_52							,			a_=32							,			a_=18							,			a_=2_56							,			a_=16_64							,			a_=46_08							,			a_="gelu"							,			a_=0.0							,			a_=0.0							,			a_=0.1							,			a_=5_12							,			a_=2							,			a_=0.02							,			a_=1E-12							,			a_=True							,			a_=0							,			a_=3_12							,			a_=3_13							,			**a_							,			):





			'''simple docstring'''

			super().__init__(pad_token_id=a_							,			bos_token_id=a_							,			eos_token_id=a_							,			**a_   )

			__snake_case      :		List[str]         =							vocab_size
			__snake_case      :		int         =							input_embedding_size
			__snake_case      :		List[Any]         =							output_embedding_size
			__snake_case      :		str         =							max_position_embeddings
			__snake_case      :		Tuple         =							hidden_size
			__snake_case      :		int         =							num_hidden_layers
			__snake_case      :		int         =							num_attention_heads
			__snake_case      :		List[str]         =							intermediate_size
			__snake_case      :		Optional[Any]         =							hidden_act
			__snake_case      :		Optional[Any]         =							hidden_dropout_prob
			__snake_case      :		Union[str, Any]         =							attention_probs_dropout_prob
			__snake_case      :		Any         =							classifier_dropout_prob
			__snake_case      :		List[str]         =							initializer_range
			__snake_case      :		Tuple         =							type_vocab_size
			__snake_case      :		Dict         =							layer_norm_eps
			__snake_case      :		Union[str, Any]         =							use_cache
			__snake_case      :		Any         =							False



class      _UpperCAmelCase					(				__snake_case							):






		'''simple docstring'''

		@property
		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			if self.task == "multiple-choice":
				__snake_case      :		List[str]         =							{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
			else:
				__snake_case      :		Any         =							{0: '''batch''', 1: '''sequence'''}
			return OrderedDict(
			    [
			        ('''input_ids''', dynamic_axis),
			        ('''attention_mask''', dynamic_axis),
			        ('''token_type_ids''', dynamic_axis),
			    ]   )



		@property
		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			return 1E-4












from __future__ import annotations

def      a    (   _lowercase :  float | int			,    _lowercase :  float | int			,    _lowercase :  float | int			,    )  ->list[float | int]:
		if not all((nth_term, start_term_a, common_ratio_r)							):
				return []
		UpperCamelCase__								=						[]
		UpperCamelCase__								=						1
		UpperCamelCase__								=						common_ratio_r
		for _ in range(int(_lowercase							)							):
				if not series:
						series.append(_lowercase							)
				else:
						power += 1
						series.append(float(start_term_a * multiple							)							)
						UpperCamelCase__								=						pow(float(_lowercase							)			,    _lowercase							)
		return series


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				__lowerCAmelCase 	=      float(input("Enter the last number (n term) of the Geometric Series"))
				__lowerCAmelCase 	=      float(input("Enter the starting term (a) of the Geometric Series"))
				__lowerCAmelCase 	=      float(
				    input("Enter the common ratio between two terms (r) of the Geometric Series")
				)
				print("Formula of Geometric Series => a + ar + ar^2 ... +ar^n")
				print(geometric_series(nth_term, start_term_a, common_ratio_r))





