


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


class 			SCREAMING_SNAKE_CASE_  (   _lowercase):




							'''simple docstring'''





							__magic_name__					:     Dict				  =  MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
							__magic_name__					:     List[Any]				  =  '''mobilebert'''




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







								'''simple docstring'''




								super().__init__(pad_token_id=lowerCamelCase__	,					**lowerCamelCase__)

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

								if self.use_bottleneck:
									snake_case__  :						Tuple		=      intra_bottleneck_size
								else:
									snake_case__  :						Union[str, Any]		=      hidden_size

								snake_case__  :						Dict		=      classifier_dropout


class 			SCREAMING_SNAKE_CASE_  (   _lowercase):




							'''simple docstring'''





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







								'''simple docstring'''




								if self.task == "multiple-choice":
									snake_case__  :						Any		=      {0: "batch", 1: "choice", 2: "sequence"}
								else:
									snake_case__  :						List[str]		=      {0: "batch", 1: "sequence"}
								return OrderedDict(
								    [
								        ("input_ids", dynamic_axis),
								        ("attention_mask", dynamic_axis),
								        ("token_type_ids", dynamic_axis),
								    ])












'''simple docstring'''






def    lowercase_   (		lowercase__ = 400_0000    ) ->int:

						if n <= 1:
												return 0
						_snake_case: Union[str, Any]	       =		0
						_snake_case: List[Any]	       =		2
						_snake_case: Any	       =		0
						while 4 * b + a <= n:
												_snake_case       ,    _snake_case: int	       =		b, 4 * b + a
												count += a
						return count + b


if __name__ == "__main__":
		print(F'{solution() = }')





