from typing import Callable, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCamelCase					:	Any       =  logging.get_logger(__name__)

__lowerCamelCase					:	Tuple       =  {
    '''microsoft/xprophetnet-large-wiki100-cased''': (
        '''https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'''
    ),
}






class 		a__						(					A__					):
					A	       =							'xlm-prophetnet'
					A	       =							['past_key_values']
					A	       =							{
					    'num_attention_heads': 'num_encoder_attention_heads',
					}

					def __init__(    self      :       Optional[Any],_A      :       Optional[float] = 0.1,_A      :       Optional[Union[str, Callable]] = "gelu",_A      :       Optional[int] = 3_0522,_A      :       Optional[int] = 1024,_A      :       Optional[int] = 4096,_A      :       Optional[int] = 12,_A      :       Optional[int] = 16,_A      :       Optional[int] = 4096,_A      :       Optional[int] = 12,_A      :       Optional[int] = 16,_A      :       Optional[float] = 0.1,_A      :       Optional[float] = 0.1,_A      :       Optional[int] = 512,_A      :       Optional[float] = 0.02,_A      :       Optional[bool] = True,_A      :       Optional[bool] = True,_A      :       Optional[int] = 0,_A      :       Optional[int] = 2,_A      :       Optional[int] = 32,_A      :       Optional[int] = 128,_A      :       Optional[bool] = False,_A      :       Optional[float] = 0.0,_A      :       Optional[bool] = True,_A      :       Optional[int] = 0,_A      :       Optional[int] = 1,_A      :       Optional[int] = 2,**_A      :       str,):







							"""simple docstring"""






							SCREAMING_SNAKE_CASE_  :		List[str]				      =    vocab_size
							SCREAMING_SNAKE_CASE_  :		Tuple				      =    hidden_size
							SCREAMING_SNAKE_CASE_  :		str				      =    encoder_ffn_dim
							SCREAMING_SNAKE_CASE_  :		Any				      =    num_encoder_layers
							SCREAMING_SNAKE_CASE_  :		Any				      =    num_encoder_attention_heads
							SCREAMING_SNAKE_CASE_  :		int				      =    decoder_ffn_dim
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    num_decoder_layers
							SCREAMING_SNAKE_CASE_  :		str				      =    num_decoder_attention_heads
							SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    max_position_embeddings
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    init_std  # Normal(0, this parameter)
							SCREAMING_SNAKE_CASE_  :		Dict				      =    activation_function

							# parameters for xlmprophetnet
							SCREAMING_SNAKE_CASE_  :		int				      =    ngram
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    num_buckets
							SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    relative_max_distance
							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    disable_ngram_loss
							SCREAMING_SNAKE_CASE_  :		List[str]				      =    eps

							# 3 Types of Dropout
							SCREAMING_SNAKE_CASE_  :		str				      =    attention_dropout
							SCREAMING_SNAKE_CASE_  :		Tuple				      =    activation_dropout
							SCREAMING_SNAKE_CASE_  :		List[Any]				      =    dropout

							SCREAMING_SNAKE_CASE_  :		Any				      =    use_cache

							super().__init__(
							    pad_token_id=_A,bos_token_id=_A,eos_token_id=_A,is_encoder_decoder=_A,add_cross_attention=_A,decoder_start_token_id=_A,**_A,)

					@property
					def 				__UpperCamelCase   (    self      :       Tuple    ):







							"""simple docstring"""






							return self.num_encoder_layers + self.num_decoder_layers






					@num_hidden_layers.setter
					def 				__UpperCamelCase   (    self      :       Optional[int],_A      :       str    ):







							"""simple docstring"""






							raise NotImplementedError(
							    "This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"
							    " `num_decoder_layers`."    )

from __future__ import annotations

from math import pi, sqrt




def       _snake_case	(   lowerCAmelCase							:   float   , lowerCAmelCase							:   float	):
		"""simple docstring"""







		if inductance <= 0:
				raise ValueError("Inductance cannot be 0 or negative"	)

		elif capacitance <= 0:
				raise ValueError("Capacitance cannot be 0 or negative"	)

		else:
				return (
				    "Resonant frequency",
				    float(1 / (2 * pi * (sqrt(inductance * capacitance	)))	),
				)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
