




from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


_lowerCamelCase      :  Dict      						=						{
    "susnato/ernie-m-base_pytorch": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json",
    "susnato/ernie-m-large_pytorch": "https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json",
}
class        __snake_case  (_a		):
				lowerCAmelCase__				=     "ernie_m"
				lowerCAmelCase__				=     {"dropout": "classifier_dropout", "num_classes": "num_labels"}



				def __init__(      self      :		Any		,	_UpperCAmelCase      :		int = 25_0002		,	_UpperCAmelCase      :		int = 768		,	_UpperCAmelCase      :		int = 12		,	_UpperCAmelCase      :		int = 12		,	_UpperCAmelCase      :		int = 3072		,	_UpperCAmelCase      :		str = "gelu"		,	_UpperCAmelCase      :		float = 0.1		,	_UpperCAmelCase      :		float = 0.1		,	_UpperCAmelCase      :		int = 514		,	_UpperCAmelCase      :		float = 0.02		,	_UpperCAmelCase      :		int = 1		,	_UpperCAmelCase      :		float = 1E-05		,	_UpperCAmelCase      :		Any=None		,	_UpperCAmelCase      :		Union[str, Any]=False		,	_UpperCAmelCase      :		Optional[int]=0.0		,	**_UpperCAmelCase      :		List[Any]		,	)  ->    Optional[Any]:





								'''simple docstring'''




								super().__init__(pad_token_id=_UpperCAmelCase		,	**_UpperCAmelCase      )
								_lowerCAmelCase										=      vocab_size
								_lowerCAmelCase										=      hidden_size
								_lowerCAmelCase										=      num_hidden_layers
								_lowerCAmelCase										=      num_attention_heads
								_lowerCAmelCase										=      intermediate_size
								_lowerCAmelCase										=      hidden_act
								_lowerCAmelCase										=      hidden_dropout_prob
								_lowerCAmelCase										=      attention_probs_dropout_prob
								_lowerCAmelCase										=      max_position_embeddings
								_lowerCAmelCase										=      initializer_range
								_lowerCAmelCase										=      layer_norm_eps
								_lowerCAmelCase										=      classifier_dropout
								_lowerCAmelCase										=      is_decoder
								_lowerCAmelCase										=      act_dropout







import numpy as np




def 							_UpperCAmelCase  (UpperCamelCase_ : np.array       ):
				'''simple docstring'''
				return (2 / (1 + np.exp(-2 * vector       ))) - 1


if __name__ == "__main__":
	import doctest

	doctest.testmod()

