



"""simple docstring"""




from math import asin, atan, cos, radians, sin, sqrt, tan

_lowerCAmelCase							:   Dict				=				6_3_7_8_1_3_7.0
_lowerCAmelCase							:   Union[str, Any]				=				6_3_5_6_7_5_2.3_1_4_2_4_5
_lowerCAmelCase							:   List[str]				=				6_37_81_37

def 		__snake_case		( SCREAMING_SNAKE_CASE__      :		float		,    SCREAMING_SNAKE_CASE__      :		float		,    SCREAMING_SNAKE_CASE__      :		float		,    SCREAMING_SNAKE_CASE__      :		float							)    ->  float:





     '''simple docstring'''

     _UpperCAmelCase     :      int														=       (AXIS_A - AXIS_B) / AXIS_A
     _UpperCAmelCase     :      List[str]														=       atan((1 - flattening) * tan(radians(SCREAMING_SNAKE_CASE__							)							)							)
     _UpperCAmelCase     :      Dict														=       atan((1 - flattening) * tan(radians(SCREAMING_SNAKE_CASE__							)							)							)
     _UpperCAmelCase     :      Any														=       radians(SCREAMING_SNAKE_CASE__							)
     _UpperCAmelCase     :      List[Any]														=       radians(SCREAMING_SNAKE_CASE__							)
     # Equation
     _UpperCAmelCase     :      Any														=       sin((phi_a - phi_a) / 2							)
     _UpperCAmelCase     :      Union[str, Any]														=       sin((lambda_a - lambda_a) / 2							)
     # Square both values
     sin_sq_phi *= sin_sq_phi
     sin_sq_lambda *= sin_sq_lambda
     _UpperCAmelCase     :      Optional[Any]														=       sqrt(sin_sq_phi + (cos(SCREAMING_SNAKE_CASE__							) * cos(SCREAMING_SNAKE_CASE__							) * sin_sq_lambda)							)
     return 2 * RADIUS * asin(SCREAMING_SNAKE_CASE__							)


if __name__ == "__main__":
 import doctest

 doctest.testmod()





"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


_lowerCAmelCase							:   Optional[int]				=				logging.get_logger(__name__)

_lowerCAmelCase							:   Any				=				{
    "roberta-base": "https://huggingface.co/roberta-base/resolve/main/config.json",
    "roberta-large": "https://huggingface.co/roberta-large/resolve/main/config.json",
    "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/config.json",
    "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/config.json",
    "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json",
    "roberta-large-openai-detector": "https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json",
}






class       UpperCAmelCase_    (							_UpperCamelCase		):
      __SCREAMING_SNAKE_CASE		:  Optional[int]						=					'roberta'



      def __init__(	self	:      str	,      A	:      Optional[int]=5_0_2_6_5	,      A	:      Optional[int]=7_6_8	,      A	:      Tuple=1_2	,      A	:      Optional[Any]=1_2	,      A	:      Optional[int]=3_0_7_2	,      A	:      str="gelu"	,      A	:      List[Any]=0.1	,      A	:      Optional[Any]=0.1	,      A	:      Any=5_1_2	,      A	:      Dict=2	,      A	:      Union[str, Any]=0.02	,      A	:      str=1e-12	,      A	:      Optional[int]=1	,      A	:      List[str]=0	,      A	:      int=2	,      A	:      Any="absolute"	,      A	:      Optional[int]=True	,      A	:      int=None	,      **A	:      str	,      ):
           super().__init__(pad_token_id=A	,      bos_token_id=A	,      eos_token_id=A	,      **A		)

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







class       UpperCAmelCase_    (							_UpperCamelCase		):



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