
"""simple docstring"""


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowercase							      = logging.get_logger(__name__)

_lowercase							      = {
    'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/config.json',
    'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/config.json',
    'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/config.json',
    'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/config.json',
    'bert-base-multilingual-uncased': 'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/config.json',
    'bert-base-multilingual-cased': 'https://huggingface.co/bert-base-multilingual-cased/resolve/main/config.json',
    'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/config.json',
    'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/config.json',
    'bert-large-uncased-whole-word-masking': (
        'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/config.json'
    ),
    'bert-large-cased-whole-word-masking': (
        'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/config.json'
    ),
    'bert-large-uncased-whole-word-masking-finetuned-squad': (
        'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/config.json'
    ),
    'bert-large-cased-whole-word-masking-finetuned-squad': (
        'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/config.json'
    ),
    'bert-base-cased-finetuned-mrpc': 'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/config.json',
    'bert-base-german-dbmdz-cased': 'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/config.json',
    'bert-base-german-dbmdz-uncased': 'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/config.json',
    'cl-tohoku/bert-base-japanese': 'https://huggingface.co/cl-tohoku/bert-base-japanese/resolve/main/config.json',
    'cl-tohoku/bert-base-japanese-whole-word-masking': (
        'https://huggingface.co/cl-tohoku/bert-base-japanese-whole-word-masking/resolve/main/config.json'
    ),
    'cl-tohoku/bert-base-japanese-char': (
        'https://huggingface.co/cl-tohoku/bert-base-japanese-char/resolve/main/config.json'
    ),
    'cl-tohoku/bert-base-japanese-char-whole-word-masking': (
        'https://huggingface.co/cl-tohoku/bert-base-japanese-char-whole-word-masking/resolve/main/config.json'
    ),
    'TurkuNLP/bert-base-finnish-cased-v1': (
        'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/config.json'
    ),
    'TurkuNLP/bert-base-finnish-uncased-v1': (
        'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/config.json'
    ),
    'wietsedv/bert-base-dutch-cased': 'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/config.json',
    # See all BERT models at https://huggingface.co/models?filter=bert
}







class  lowerCAmelCase_ (					__UpperCAmelCase			):



						'''simple docstring'''


						_lowerCamelCase:			Any					=			'''bert'''


						def __init__(       self   :					List[str]     ,A_   :					Any=3_0522     ,A_   :					Any=768     ,A_   :					List[Any]=12     ,A_   :					Optional[Any]=12     ,A_   :					int=3072     ,A_   :					Optional[Any]="gelu"     ,A_   :					Optional[int]=0.1     ,A_   :					Union[str, Any]=0.1     ,A_   :					Any=512     ,A_   :					Tuple=2     ,A_   :					List[str]=0.02     ,A_   :					Optional[Any]=1e-12     ,A_   :					Optional[int]=0     ,A_   :					str="absolute"     ,A_   :					Dict=True     ,A_   :					List[Any]=None     ,**A_   :					Optional[Any]     ,)   ->      Tuple:
							super().__init__(pad_token_id=lowerCamelCase__     ,**lowerCamelCase__					)

							A        =      vocab_size
							A        =      hidden_size
							A        =      num_hidden_layers
							A        =      num_attention_heads
							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        =      position_embedding_type
							A        =      use_cache
							A        =      classifier_dropout







class  lowerCAmelCase_ (					__UpperCAmelCase			):



						'''simple docstring'''


						@property
						def   _SCREAMING_SNAKE_CASE					(       self   :					int					)   ->      List[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),
							    ]					)
"""simple docstring"""






import math



def   a_						(					lowerCamelCase					,			lowerCamelCase       ):
				if (
				    not isinstance(lowerCamelCase					,			(int, float)       )
				    or power_factor < -1
				    or power_factor > 1
				):
								raise ValueError('power_factor must be a valid float value between -1 and 1.'       )
				return apparent_power * power_factor



def   a_						(					lowerCamelCase					,			lowerCamelCase       ):
				if (
				    not isinstance(lowerCamelCase					,			(int, float)       )
				    or power_factor < -1
				    or power_factor > 1
				):
								raise ValueError('power_factor must be a valid float value between -1 and 1.'       )
				return apparent_power * math.sqrt(1 - power_factor**2       )


if __name__ == "__main__":
						import doctest

						doctest.testmod()



