



'''simple docstring'''
from collections import OrderedDict
from typing import Mapping

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


_UpperCamelCase											=			logging.get_logger(__name__)

_UpperCamelCase											=			{
    '''google/mobilebert-uncased''': '''https://huggingface.co/google/mobilebert-uncased/resolve/main/config.json'''
}



class _A  (    __SCREAMING_SNAKE_CASE    ):
		_SCREAMING_SNAKE_CASE					:    Union[str, Any]						      =			MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
		_SCREAMING_SNAKE_CASE					:    Optional[int]						      =			"mobilebert"





		def __init__(     self ,       __UpperCAmelCase=30_522 ,       __UpperCAmelCase=512 ,       __UpperCAmelCase=24 ,       __UpperCAmelCase=4 ,       __UpperCAmelCase=512 ,       __UpperCAmelCase="relu" ,       __UpperCAmelCase=0.0 ,       __UpperCAmelCase=0.1 ,       __UpperCAmelCase=512 ,       __UpperCAmelCase=2 ,       __UpperCAmelCase=0.02 ,       __UpperCAmelCase=1E-12 ,       __UpperCAmelCase=0 ,       __UpperCAmelCase=128 ,       __UpperCAmelCase=True ,       __UpperCAmelCase=True ,       __UpperCAmelCase=128 ,       __UpperCAmelCase=False ,       __UpperCAmelCase=True ,       __UpperCAmelCase=4 ,       __UpperCAmelCase="no_norm" ,       __UpperCAmelCase=True ,       __UpperCAmelCase=None ,       **__UpperCAmelCase ,       )       ->     str:

					'''simple docstring'''
					super().__init__(pad_token_id=__UpperCAmelCase ,       **__UpperCAmelCase				)

					__UpperCAmelCase   :      Tuple										=     vocab_size
					__UpperCAmelCase   :      Tuple										=     hidden_size
					__UpperCAmelCase   :      Union[str, Any]										=     num_hidden_layers
					__UpperCAmelCase   :      Union[str, Any]										=     num_attention_heads
					__UpperCAmelCase   :      List[Any]										=     hidden_act
					__UpperCAmelCase   :      Union[str, Any]										=     intermediate_size
					__UpperCAmelCase   :      List[str]										=     hidden_dropout_prob
					__UpperCAmelCase   :      List[Any]										=     attention_probs_dropout_prob
					__UpperCAmelCase   :      List[Any]										=     max_position_embeddings
					__UpperCAmelCase   :      Optional[Any]										=     type_vocab_size
					__UpperCAmelCase   :      Any										=     initializer_range
					__UpperCAmelCase   :      Tuple										=     layer_norm_eps
					__UpperCAmelCase   :      Union[str, Any]										=     embedding_size
					__UpperCAmelCase   :      Tuple										=     trigram_input
					__UpperCAmelCase   :      List[Any]										=     use_bottleneck
					__UpperCAmelCase   :      List[Any]										=     intra_bottleneck_size
					__UpperCAmelCase   :      Union[str, Any]										=     use_bottleneck_attention
					__UpperCAmelCase   :      Dict										=     key_query_shared_bottleneck
					__UpperCAmelCase   :      Tuple										=     num_feedforward_networks
					__UpperCAmelCase   :      Optional[Any]										=     normalization_type
					__UpperCAmelCase   :      str										=     classifier_activation

					if self.use_bottleneck:
								__UpperCAmelCase   :      List[Any]										=     intra_bottleneck_size
					else:
								__UpperCAmelCase   :      Optional[Any]										=     hidden_size

					__UpperCAmelCase   :      Optional[int]										=     classifier_dropout



class _A  (    __SCREAMING_SNAKE_CASE    ):





		@property
		def 							__A       (     self				)       ->     Mapping[str, Mapping[int, str]]:

					'''simple docstring'''
					if self.task == "multiple-choice":
								__UpperCAmelCase   :      Dict										=     {0: """batch""", 1: """choice""", 2: """sequence"""}
					else:
								__UpperCAmelCase   :      Union[str, Any]										=     {0: """batch""", 1: """sequence"""}
					return OrderedDict(
					    [
					        ("""input_ids""", dynamic_axis),
					        ("""attention_mask""", dynamic_axis),
					        ("""token_type_ids""", dynamic_axis),
					    ]				)









'''simple docstring'''
from math import pi


def   lowercase_	(   lowerCAmelCase__	:  float ):

			"""simple docstring"""





			return degree / (180 / pi)


if __name__ == "__main__":
					from doctest import testmod

					testmod()




