






'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE_				      =		logging.get_logger(__name__)

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




class 							lowerCAmelCase					(							A__   ):







   """simple docstring"""







   _A						=   MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
   _A						=   'mobilebert'



   def __init__( self   ,   _A=30522   ,   _A=512   ,   _A=24   ,   _A=4   ,   _A=512   ,   _A="relu"   ,   _A=0.0   ,   _A=0.1   ,   _A=512   ,   _A=2   ,   _A=0.02   ,   _A=1E-1_2   ,   _A=0   ,   _A=128   ,   _A=True   ,   _A=True   ,   _A=128   ,   _A=False   ,   _A=True   ,   _A=4   ,   _A="no_norm"   ,   _A=True   ,   _A=None   ,   **_A   ,   )    ->   Dict:
    super().__init__(pad_token_id=_lowerCAmelCase   ,   **_lowerCAmelCase			)

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

    if self.use_bottleneck:
     __a    :	List[str]									=						intra_bottleneck_size
    else:
     __a    :	Tuple									=						hidden_size

    __a    :	List[str]									=						classifier_dropout




class 							lowerCAmelCase					(							A__   ):







   """simple docstring"""







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












'''simple docstring'''


def   lowerCAmelCase__			(					SCREAMING_SNAKE_CASE__ = 30		):
 __a    :	Tuple									=						exponent + 2
 __a    :	str									=						(1 + 5**0.5) / 2
 __a    :	Any									=						(phi**fibonacci_index - (phi - 1) ** fibonacci_index) / 5**0.5

 return int(SCREAMING_SNAKE_CASE__		)


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




