"""simple docstring"""

from collections import OrderedDict
from typing import Mapping

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


UpperCAmelCase       =  {
    """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      UpperCAmelCase_       (						__SCREAMING_SNAKE_CASE):
							snake_case__        =      'albert'






							def __init__(		self :      Tuple     ,						__UpperCamelCase :      Any=3_0000     ,						__UpperCamelCase :      Dict=128     ,						__UpperCamelCase :      int=4096     ,						__UpperCamelCase :      Tuple=12     ,						__UpperCamelCase :      int=1     ,						__UpperCamelCase :      Union[str, Any]=64     ,						__UpperCamelCase :      str=1_6384     ,						__UpperCamelCase :      Optional[int]=1     ,						__UpperCamelCase :      str="gelu_new"     ,						__UpperCamelCase :      Union[str, Any]=0     ,						__UpperCamelCase :      List[Any]=0     ,						__UpperCamelCase :      Any=512     ,						__UpperCamelCase :      List[str]=2     ,						__UpperCamelCase :      str=0.0_2     ,						__UpperCamelCase :      Optional[Any]=1E-12     ,						__UpperCamelCase :      Optional[Any]=0.1     ,						__UpperCamelCase :      int="absolute"     ,						__UpperCamelCase :      int=0     ,						__UpperCamelCase :      int=2     ,						__UpperCamelCase :      Dict=3     ,						**__UpperCamelCase :      Union[str, Any]     ,						)       ->       List[Any]:
												super().__init__(pad_token_id=_a     ,						bos_token_id=_a     ,						eos_token_id=_a     ,						**_a  )

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







class      UpperCAmelCase_       (						__SCREAMING_SNAKE_CASE):






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




"""simple docstring"""




import numpy as np

def        lowercase							(		lowerCAmelCase__ :     np.ndarray    ,					lowerCAmelCase__ :     float			) ->      np.ndarray:
		return np.where(vector > 0    ,					lowerCAmelCase__    ,					(alpha * (np.exp(lowerCAmelCase__			) - 1))			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()






