
from collections import OrderedDict
from typing import Mapping

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


_SCREAMING_SNAKE_CASE    :      Dict          =			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE    :      Dict          =			{
    'kssteven/ibert-roberta-base': 'https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json',
    'kssteven/ibert-roberta-large': 'https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json',
    'kssteven/ibert-roberta-large-mnli': (
        'https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json'
    ),
}







class  UpperCamelCase__		(    SCREAMING_SNAKE_CASE_   ):







	'''simple docstring'''
	_lowerCAmelCase							       =				"ibert"





	def __init__(			self				,       UpperCamelCase__=3_0522				,       UpperCamelCase__=768				,       UpperCamelCase__=12				,       UpperCamelCase__=12				,       UpperCamelCase__=3072				,       UpperCamelCase__="gelu"				,       UpperCamelCase__=0.1				,       UpperCamelCase__=0.1				,       UpperCamelCase__=512				,       UpperCamelCase__=2				,       UpperCamelCase__=0.0_2				,       UpperCamelCase__=1e-12				,       UpperCamelCase__=1				,       UpperCamelCase__=0				,       UpperCamelCase__=2				,       UpperCamelCase__="absolute"				,       UpperCamelCase__=False				,       UpperCamelCase__="none"				,       **UpperCamelCase__				,       ):
					super().__init__(pad_token_id=UpperCamelCase__				,       bos_token_id=UpperCamelCase__				,       eos_token_id=UpperCamelCase__				,       **UpperCamelCase__		)

					A__  :	Optional[Any]         =							vocab_size
					A__  :	Optional[int]         =							hidden_size
					A__  :	Optional[Any]         =							num_hidden_layers
					A__  :	Any         =							num_attention_heads
					A__  :	str         =							hidden_act
					A__  :	Tuple         =							intermediate_size
					A__  :	int         =							hidden_dropout_prob
					A__  :	int         =							attention_probs_dropout_prob
					A__  :	List[str]         =							max_position_embeddings
					A__  :	Union[str, Any]         =							type_vocab_size
					A__  :	Union[str, Any]         =							initializer_range
					A__  :	Any         =							layer_norm_eps
					A__  :	List[Any]         =							position_embedding_type
					A__  :	List[str]         =							quant_mode
					A__  :	Tuple         =							force_dequant







class  UpperCamelCase__		(    SCREAMING_SNAKE_CASE_   ):







	'''simple docstring'''





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

from numpy import exp, pi, sqrt

def 				SCREAMING_SNAKE_CASE     (      __UpperCamelCase :						Dict							,						__UpperCamelCase :						float = 0.0							,						__UpperCamelCase :						float = 1.0       ) ->       int:

				"""simple docstring"""







				return 1 / sqrt(2 * pi * sigma**2       ) * exp(-((x - mu) ** 2) / (2 * sigma**2)       )


if __name__ == "__main__":
					import doctest

					doctest.testmod()