"""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   __snake_case			(	__lowerCAmelCase							):
      a__								=						MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
      a__								=						"""mobilebert"""



      def __init__(		self       ,     lowercase=3_05_22       ,     lowercase=5_12       ,     lowercase=24       ,     lowercase=4       ,     lowercase=5_12       ,     lowercase="relu"       ,     lowercase=0.0       ,     lowercase=0.1       ,     lowercase=5_12       ,     lowercase=2       ,     lowercase=0.02       ,     lowercase=1e-12       ,     lowercase=0       ,     lowercase=1_28       ,     lowercase=True       ,     lowercase=True       ,     lowercase=1_28       ,     lowercase=False       ,     lowercase=True       ,     lowercase=4       ,     lowercase="no_norm"       ,     lowercase=True       ,     lowercase=None       ,     **lowercase       ,     )      ->     Any:





        '''simple docstring'''





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

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

        if self.use_bottleneck:
          a__:	Any     				=      intra_bottleneck_size
        else:
          a__:	List[str]     				=      hidden_size

        a__:	Any     				=      classifier_dropout







class   __snake_case			(	__lowerCAmelCase							):



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





        '''simple docstring'''





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



"""simple docstring"""
def 		__a  (      _SCREAMING_SNAKE_CASE = 100						,	_SCREAMING_SNAKE_CASE = 100  )      ->int:
  return max(
      sum(int(_SCREAMING_SNAKE_CASE  ) for x in str(base**power  )  )
      for base in range(_SCREAMING_SNAKE_CASE  )
      for power in range(_SCREAMING_SNAKE_CASE  )  )


# Tests
if __name__ == "__main__":
 import doctest

 doctest.testmod()


