





"""simple docstring"""




from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
a						: Tuple     	=			1.0_5_4_5_7_1_8_1_7E-3_4  # unit of ℏ : J * s

a						: Dict     	=			3E8  # unit of c : m * s^-1






def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    float    ,       _lowercase						:    float    ,       _lowercase						:    float					) ->dict[str, float]:






	'''simple docstring'''






	if (force, area, distance).count(0					) != 1:
		raise ValueError("One and only one argument must be 0"					)
	if force < 0:
		raise ValueError("Magnitude of force can not be negative"					)
	if distance < 0:
		raise ValueError("Distance can not be negative"					)
	if area < 0:
		raise ValueError("Area can not be negative"					)
	if force == 0:
		a      :		Optional[Any]	=				(REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
		    240 * (distance) ** 4
		)
		return {"force": force}
	elif area == 0:
		a      :		Any	=				(240 * force * (distance) ** 4) / (
		    REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
		)
		return {"area": area}
	elif distance == 0:
		a      :		str	=				(
		    (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (240 * force)
		) ** (1 / 4)
		return {"distance": distance}
	raise ValueError("One and only one argument must be 0"					)


# Run doctest
if __name__ == "__main__":
		import doctest

		doctest.testmod()








from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


__lowerCAmelCase		:				int       			=		{
    'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
    'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/config.json',
    'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/config.json',
    'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json',
    'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/config.json',
    'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/config.json',
    'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/config.json',
    'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json',
}




class     snake_case__							(_UpperCamelCase   ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_       :							Optional[int]							 =					"""albert"""





				def __init__(      self				:     List[str]					,      __lowerCamelCase				:     Union[str, Any]=3_00_00					,      __lowerCamelCase				:     Union[str, Any]=1_28					,      __lowerCamelCase				:     Any=40_96					,      __lowerCamelCase				:     str=12					,      __lowerCamelCase				:     Union[str, Any]=1					,      __lowerCamelCase				:     Union[str, Any]=64					,      __lowerCamelCase				:     Dict=1_63_84					,      __lowerCamelCase				:     List[Any]=1					,      __lowerCamelCase				:     Optional[Any]="gelu_new"					,      __lowerCamelCase				:     List[str]=0					,      __lowerCamelCase				:     List[str]=0					,      __lowerCamelCase				:     Tuple=5_12					,      __lowerCamelCase				:     Optional[Any]=2					,      __lowerCamelCase				:     Optional[Any]=0.02					,      __lowerCamelCase				:     Optional[Any]=1e-12					,      __lowerCamelCase				:     Union[str, Any]=0.1					,      __lowerCamelCase				:     Any="absolute"					,      __lowerCamelCase				:     List[str]=0					,      __lowerCamelCase				:     List[str]=2					,      __lowerCamelCase				:     Any=3					,      **__lowerCamelCase				:     int					,      )					->     int:
							super().__init__(pad_token_id=__lowerCamelCase					,      bos_token_id=__lowerCamelCase					,      eos_token_id=__lowerCamelCase					,      **__lowerCamelCase							)

							a    =			vocab_size
							a    =			embedding_size
							a    =			hidden_size
							a    =			num_hidden_layers
							a    =			num_hidden_groups
							a    =			num_attention_heads
							a    =			inner_group_num
							a    =			hidden_act
							a    =			intermediate_size
							a    =			hidden_dropout_prob
							a    =			attention_probs_dropout_prob
							a    =			max_position_embeddings
							a    =			type_vocab_size
							a    =			initializer_range
							a    =			layer_norm_eps
							a    =			classifier_dropout_prob
							a    =			position_embedding_type




class     snake_case__							(_UpperCamelCase   ):
				"""simple docstring"""



				@property
				def 							__UpperCAmelCase							(      self				:     List[Any]							)					->     Mapping[str, Mapping[int, str]]:
							if self.task == "multiple-choice":
										a    =			{0: "batch", 1: "choice", 2: "sequence"}
							else:
										a    =			{0: "batch", 1: "sequence"}
							return OrderedDict(
							    [
							        ("input_ids", dynamic_axis),
							        ("attention_mask", dynamic_axis),
							        ("token_type_ids", dynamic_axis),
							    ]							)






