






from __future__ import annotations

from enum import Enum





class        a__      (	lowerCAmelCase__		):
		UpperCAmelCase_							:       List[str] 					= 24
		UpperCAmelCase_							:       str 					= 21
		UpperCAmelCase_							:       List[str] 					= 18
		UpperCAmelCase_							:       Dict 					= 15
		UpperCAmelCase_							:       Tuple 					= 12
		UpperCAmelCase_							:       Optional[int] 					= 9
		UpperCAmelCase_							:       List[Any] 					= 6
		UpperCAmelCase_							:       Any 					= 3
		UpperCAmelCase_							:       List[Any] 					= 2
		UpperCAmelCase_							:       Dict 					= 1
		UpperCAmelCase_							:       List[str] 					= -1
		UpperCAmelCase_							:       List[str] 					= -2
		UpperCAmelCase_							:       Any 					= -3
		UpperCAmelCase_							:       Any 					= -6
		UpperCAmelCase_							:       Dict 					= -9
		UpperCAmelCase_							:       int 					= -12
		UpperCAmelCase_							:       List[Any] 					= -15
		UpperCAmelCase_							:       List[Any] 					= -18
		UpperCAmelCase_							:       Dict 					= -21
		UpperCAmelCase_							:       Optional[Any] 					= -24





class        a__      (	lowerCAmelCase__		):
		UpperCAmelCase_							:       Optional[int] 					= 8
		UpperCAmelCase_							:       List[Any] 					= 7
		UpperCAmelCase_							:       List[str] 					= 6
		UpperCAmelCase_							:       Any 					= 5
		UpperCAmelCase_							:       Tuple 					= 4
		UpperCAmelCase_							:       int 					= 3
		UpperCAmelCase_							:       Union[str, Any] 					= 2
		UpperCAmelCase_							:       str 					= 1



def      UpperCAmelCase						( lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     ):


		'''simple docstring'''

		if isinstance(lowerCAmelCase__					,     lowerCAmelCase__	):
				__A    =							SIUnit[known_prefix.lower()]
		if isinstance(lowerCAmelCase__					,     lowerCAmelCase__	):
				__A    =							SIUnit[unknown_prefix.lower()]
		__A    =							known_amount * (
		    10 ** (known_prefix.value - unknown_prefix.value)
		)
		return unknown_amount



def      UpperCAmelCase						( lowerCAmelCase__					,     lowerCAmelCase__					,     lowerCAmelCase__					,     ):


		'''simple docstring'''

		if isinstance(lowerCAmelCase__					,     lowerCAmelCase__	):
				__A    =							BinaryUnit[known_prefix.lower()]
		if isinstance(lowerCAmelCase__					,     lowerCAmelCase__	):
				__A    =							BinaryUnit[unknown_prefix.lower()]
		__A    =							known_amount * (
		    2 ** ((known_prefix.value - unknown_prefix.value) * 10)
		)
		return unknown_amount


if __name__ == "__main__":
					import doctest

					doctest.testmod()




from typing import Callable, Optional, Union

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


A__							=				logging.get_logger(__name__)

A__							=				{
    "microsoft/prophetnet-large-uncased": (
        "https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"
    ),
}

class 					__UpperCamelCase					(       SCREAMING_SNAKE_CASE      ):
	_lowercase	: Union[str, Any]												=	"prophetnet"
	_lowercase	: Any												=	["past_key_values"]
	_lowercase	: int												=	{
	    "num_attention_heads": "num_encoder_attention_heads",
	}







	def __init__( self:			Union[str, Any]	,			__UpperCamelCase:			Optional[float] = 0.1	,			__UpperCamelCase:			Optional[Union[str, Callable]] = "gelu"	,			__UpperCamelCase:			Optional[int] = 3_05_22	,			__UpperCamelCase:			Optional[int] = 10_24	,			__UpperCamelCase:			Optional[int] = 40_96	,			__UpperCamelCase:			Optional[int] = 12	,			__UpperCamelCase:			Optional[int] = 16	,			__UpperCamelCase:			Optional[int] = 40_96	,			__UpperCamelCase:			Optional[int] = 12	,			__UpperCamelCase:			Optional[int] = 16	,			__UpperCamelCase:			Optional[float] = 0.1	,			__UpperCamelCase:			Optional[float] = 0.1	,			__UpperCamelCase:			Optional[int] = 5_12	,			__UpperCamelCase:			Optional[float] = 0.02	,			__UpperCamelCase:			Optional[bool] = True	,			__UpperCamelCase:			Optional[bool] = True	,			__UpperCamelCase:			Optional[int] = 0	,			__UpperCamelCase:			Optional[int] = 2	,			__UpperCamelCase:			Optional[int] = 32	,			__UpperCamelCase:			Optional[int] = 1_28	,			__UpperCamelCase:			Optional[bool] = False	,			__UpperCamelCase:			Optional[float] = 0.0	,			__UpperCamelCase:			Optional[bool] = True	,			__UpperCamelCase:			Optional[int] = 0	,			__UpperCamelCase:			Optional[int] = 1	,			__UpperCamelCase:			Optional[int] = 2	,			**__UpperCamelCase:			Optional[int]	,			):

						'''simple docstring'''





						__magic_name__				=     vocab_size
						__magic_name__				=     hidden_size
						__magic_name__				=     encoder_ffn_dim
						__magic_name__				=     num_encoder_layers
						__magic_name__				=     num_encoder_attention_heads
						__magic_name__				=     decoder_ffn_dim
						__magic_name__				=     num_decoder_layers
						__magic_name__				=     num_decoder_attention_heads
						__magic_name__				=     max_position_embeddings
						__magic_name__				=     init_std  # Normal(0, this parameter)
						__magic_name__				=     activation_function

						# parameters for prophetnet
						__magic_name__				=     ngram
						__magic_name__				=     num_buckets
						__magic_name__				=     relative_max_distance
						__magic_name__				=     disable_ngram_loss
						__magic_name__				=     eps

						# 3 Types of Dropout
						__magic_name__				=     attention_dropout
						__magic_name__				=     activation_dropout
						__magic_name__				=     dropout

						__magic_name__				=     use_cache

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







	@property
	def 						_SCREAMING_SNAKE_CASE				( self:			Tuple   ):

						'''simple docstring'''





						return self.num_encoder_layers + self.num_decoder_layers







	@num_hidden_layers.setter
	def 						_SCREAMING_SNAKE_CASE				( self:			Union[str, Any]	,			__UpperCamelCase:			List[Any]   ):

						'''simple docstring'''





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




