code: 
  from collections import OrderedDict
  from typing import Mapping
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  snake_case				:	Any							   =						logging.get_logger(__name__)
  
  snake_case				:	Tuple							   =						{
      "google/rembert": "https://huggingface.co/google/rembert/resolve/main/config.json",
      # See all RemBERT models at https://huggingface.co/models?filter=rembert
  }
  
  
  
  
  
  class    _snake_case      (  snake_case       ):
  			UpperCamelCase__					   =					'rembert'
  
  
  
  
  
  
  
  			def __init__(       self		,     _a=250_300		,     _a=1_152		,     _a=32		,     _a=18		,     _a=256		,     _a=1_664		,     _a=4_608		,     _a="gelu"		,     _a=0.0		,     _a=0.0		,     _a=0.1		,     _a=512		,     _a=2		,     _a=0.02		,     _a=1e-12		,     _a=True		,     _a=0		,     _a=312		,     _a=313		,     **_a		,     ):
  				super().__init__(pad_token_id=_a		,     bos_token_id=_a		,     eos_token_id=_a		,     **_a	)
  
  				__magic_name__	:	Any			     =  vocab_size
  				__magic_name__	:	Tuple			     =  input_embedding_size
  				__magic_name__	:	str			     =  output_embedding_size
  				__magic_name__	:	Any			     =  max_position_embeddings
  				__magic_name__	:	Optional[Any]			     =  hidden_size
  				__magic_name__	:	Dict			     =  num_hidden_layers
  				__magic_name__	:	List[str]			     =  num_attention_heads
  				__magic_name__	:	Union[str, Any]			     =  intermediate_size
  				__magic_name__	:	List[Any]			     =  hidden_act
  				__magic_name__	:	Tuple			     =  hidden_dropout_prob
  				__magic_name__	:	Dict			     =  attention_probs_dropout_prob
  				__magic_name__	:	str			     =  classifier_dropout_prob
  				__magic_name__	:	Optional[Any]			     =  initializer_range
  				__magic_name__	:	Optional[int]			     =  type_vocab_size
  				__magic_name__	:	int			     =  layer_norm_eps
  				__magic_name__	:	str			     =  use_cache
  				__magic_name__	:	Tuple			     =  False
  
  
  
  
  
  
  
  class    _snake_case      (  snake_case       ):
  
  
  
  
  
  
  
  			@property
  			def     SCREAMING_SNAKE_CASE					(       self	):
  				if self.task == "multiple-choice":
  					__magic_name__	:	Union[str, Any]			     =  {0: "batch", 1: "choice", 2: "sequence"}
  				else:
  					__magic_name__	:	Tuple			     =  {0: "batch", 1: "sequence"}
  				return OrderedDict(
  				    [
  				        ("input_ids", dynamic_axis),
  				        ("attention_mask", dynamic_axis),
  				        ("token_type_ids", dynamic_axis),
  				    ]	)
  
  
  
  
  
  
  
  			@property
  			def     SCREAMING_SNAKE_CASE					(       self	):
  				return 1e-4
  
  
  
  
  
  
style_context: 
  from __future__ import annotations
  
  snake_case				:	List[str]							   =						"Alexander Joslin"
  
  
  
  
  
  
  def 						lowerCAmelCase_		(      _snake_case   :						int     )       ->	int:
  
  
  
  
  
  
  
  	'''simple docstring'''
  
  
  	if number <= 0:
  		__magic_name__	:	int			     =  F'''n must be greater than 0. Got n = {number}'''
  		raise ValueError(_snake_case     )
  
  	__magic_name__	:	List[str]			     =  [number + 1] * (number + 1)
  
  	# starting position
  	__magic_name__	:	Any			     =  0
  	for i in range(1   ,     _snake_case     ):
  		__magic_name__	:	Optional[int]			     =  min(table[i + 1]   ,     table[i] + 1     )
  		# check if out of bounds
  		if i * 2 <= number:
  			__magic_name__	:	str			     =  min(table[i * 2]   ,     table[i] + 1     )
  		# check if out of bounds
  		if i * 3 <= number:
  			__magic_name__	:	Any			     =  min(table[i * 3]   ,     table[i] + 1     )
  	return table[number]
  
  
  if __name__ == "__main__":
  				import doctest
  
  				doctest.testmod()
  