





from ...configuration_utils import PretrainedConfig

class 		snake_case_   (							UpperCAmelCase_						):







	'''simple docstring'''
	__UpperCamelCase   =		'''bert-generation'''




	def __init__(						self							:     List[str]					,      __lowerCamelCase							:     Optional[int]=50_358					,      __lowerCamelCase							:     Any=1_024					,      __lowerCamelCase							:     int=24					,      __lowerCamelCase							:     Optional[int]=16					,      __lowerCamelCase							:     Union[str, Any]=4_096					,      __lowerCamelCase							:     List[str]="gelu"					,      __lowerCamelCase							:     Optional[int]=0.1					,      __lowerCamelCase							:     List[str]=0.1					,      __lowerCamelCase							:     str=512					,      __lowerCamelCase							:     List[Any]=0.02					,      __lowerCamelCase							:     Optional[int]=1E-1_2					,      __lowerCamelCase							:     int=0					,      __lowerCamelCase							:     List[str]=2					,      __lowerCamelCase							:     Union[str, Any]=1					,      __lowerCamelCase							:     Union[str, Any]="absolute"					,      __lowerCamelCase							:     Optional[int]=True					,      **__lowerCamelCase							:     List[Any]					,      )       -> Union[str, Any]:

			'''simple docstring'''




			super().__init__(pad_token_id=__lowerCamelCase					,      bos_token_id=__lowerCamelCase					,      eos_token_id=__lowerCamelCase					,      **__lowerCamelCase   )

			__lowercase											=     vocab_size
			__lowercase											=     hidden_size
			__lowercase											=     num_hidden_layers
			__lowercase											=     num_attention_heads
			__lowercase											=     hidden_act
			__lowercase											=     intermediate_size
			__lowercase											=     hidden_dropout_prob
			__lowercase											=     attention_probs_dropout_prob
			__lowercase											=     max_position_embeddings
			__lowercase											=     initializer_range
			__lowercase											=     layer_norm_eps
			__lowercase											=     position_embedding_type
			__lowercase											=     use_cache











SCREAMING_SNAKE_CASE_   :      dict[str, float]			=   {
    "joule": 1.0,
    "kilojoule": 1000,
    "megajoule": 100_0000,
    "gigajoule": 10_0000_0000,
    "wattsecond": 1.0,
    "watthour": 3600,
    "kilowatthour": 360_0000,
    "newtonmeter": 1.0,
    "calorie_nutr": 4186.8,
    "kilocalorie_nutr": 418_6800.00,
    "electronvolt": 1.6_0_2_1_7_6_6_3_4e-1_9,
    "britishthermalunit_it": 1055.0_5585,
    "footpound": 1.35_5818,
}



def  SCREAMING_SNAKE_CASE				(      snake_case						,   snake_case						,   snake_case							)		->    float:
		if to_type not in ENERGY_CONVERSION or from_type not in ENERGY_CONVERSION:
				__lowercase											=     (
				    F"Incorrect 'from_type' or 'to_type' value: {from_type!r}, {to_type!r}\n"
				    F"Valid values are: {', '.join(snake_case							)}"
				)
				raise ValueError(snake_case							)
		return value * ENERGY_CONVERSION[from_type] / ENERGY_CONVERSION[to_type]


if __name__ == "__main__":
		import doctest

		doctest.testmod()




