




from statistics import mean, stdev




def 			__magic_name__				( A		:					list,  A		:					int = 3   ):






			'''simple docstring'''







			a    =			min(A   )
			a    =			max(A   )
			# normalize data
			return [round((x - x_min) / (x_max - x_min),  A   ) for x in data]






def 			__magic_name__				( A		:					list,  A		:					int = 3   ):






			'''simple docstring'''







			a    =			mean(A   )
			a    =			stdev(A   )
			# standardize data
			return [round((x - mu) / (sigma),  A   ) for x in data]












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),
							    ]							)






