



from collections import OrderedDict
from typing import Mapping

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


a__						=		logging.get_logger(__name__)

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







class 						snake_case  (		SCREAMING_SNAKE_CASE_					):



   '''simple docstring'''






   snake_case_   :	Union[str, Any]       =						MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
   snake_case_   :	Optional[Any]       =						"""mobilebert"""

   def __init__(   self							:     Optional[int]			,						lowerCAmelCase							:     List[Any]=3_0522			,						lowerCAmelCase							:     Optional[Any]=512			,						lowerCAmelCase							:     Tuple=24			,						lowerCAmelCase							:     Union[str, Any]=4			,						lowerCAmelCase							:     Union[str, Any]=512			,						lowerCAmelCase							:     Tuple="relu"			,						lowerCAmelCase							:     str=0.0			,						lowerCAmelCase							:     Any=0.1			,						lowerCAmelCase							:     Tuple=512			,						lowerCAmelCase							:     List[Any]=2			,						lowerCAmelCase							:     List[Any]=0.02			,						lowerCAmelCase							:     Dict=1E-12			,						lowerCAmelCase							:     str=0			,						lowerCAmelCase							:     Tuple=128			,						lowerCAmelCase							:     int=True			,						lowerCAmelCase							:     List[Any]=True			,						lowerCAmelCase							:     int=128			,						lowerCAmelCase							:     Any=False			,						lowerCAmelCase							:     Any=True			,						lowerCAmelCase							:     Optional[Any]=4			,						lowerCAmelCase							:     int="no_norm"			,						lowerCAmelCase							:     Any=True			,						lowerCAmelCase							:     Union[str, Any]=None			,						**lowerCAmelCase							:     Optional[Any]			,						)			->			Tuple:

    """simple docstring"""







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

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

    if self.use_bottleneck:
     _snake_case      :					Optional[int]					=   intra_bottleneck_size
    else:
     _snake_case      :					Any					=   hidden_size

    _snake_case      :					Optional[int]					=   classifier_dropout







class 						snake_case  (		SCREAMING_SNAKE_CASE_					):



   '''simple docstring'''






   @property
   def        UpperCamelCase_					(   self							:     Optional[Any])			->			Mapping[str, Mapping[int, str]]:

    """simple docstring"""







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





def  lowercase    (				SCREAMING_SNAKE_CASE__    :		float			,    SCREAMING_SNAKE_CASE__    :		float			)					->       float:
 _snake_case      :					str					=   float()
 try:
  _snake_case      :					str					=   mass * acceleration
 except Exception:
  return -0.0
 return force


if __name__ == "__main__":
  import doctest

  # run doctest
  doctest.testmod()

  # demo
  a__      =		12.5
  a__      =		10
  a__      =		newtons_second_law_of_motion(mass, acceleration)
  print("""The force is """, force, """N""")
