code: 
  
  
  '''simple docstring'''
  
  
  
  
  
  from typing import Any
  class 	a__				:
  
  
  
  
  
  			'''simple docstring'''
  
  			def __init__(     self       : Any  )			->		int:
  						__A=  []
  						__A=  0
  			def __str__(     self       : Tuple  )			->		Dict:
  						__A=  '<' + str(self.stack  )[1:-1] + '>'
  						return printed
  			def 				lowerCAmelCase    (     self       : Tuple ,						lowerCAmelCase_       : Any  )			->		None:
  						self.stack.append(lowerCAmelCase_  )
  						__A=  self.length + 1
  			def 				lowerCAmelCase    (     self       : int  )			->		Any:
  						self.rotate(1  )
  						__A=  self.stack[self.length - 1]
  						__A=  self.stack[:-1]
  						self.rotate(self.length - 1  )
  						__A=  self.length - 1
  						return dequeued
  			def 				lowerCAmelCase    (     self       : Optional[int] ,						lowerCAmelCase_       : int  )			->		None:
  						for _ in range(lowerCAmelCase_  ):
  									__A=  self.stack[0]
  									__A=  self.stack[1:]
  									self.put(lowerCAmelCase_  )
  									__A=  self.length - 1
  			def 				lowerCAmelCase    (     self       : Tuple  )			->		Any:
  						__A=  self.get()
  						self.put(lowerCAmelCase_  )
  						self.rotate(self.length - 1  )
  						return front
  			def 				lowerCAmelCase    (     self       : Dict  )			->		int:
  						return self.length
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  
  
  
  
  from collections import OrderedDict
  from typing import Mapping
  
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import logging
  
  
  UpperCAmelCase__      =							logging.get_logger(__name__)
  
  UpperCAmelCase__      =							{
      '''google/mobilebert-uncased''': '''https://huggingface.co/google/mobilebert-uncased/resolve/main/config.json'''
  }
  class 	a__				(				a_      ):
  
  
  
  
  
  			'''simple docstring'''
  
  			A	:							int							= MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
  			A	:							Optional[int]							= '''mobilebert'''
  			def __init__(     self       : Optional[int] ,						lowerCAmelCase_       : str=30_522 ,						lowerCAmelCase_       : List[Any]=512 ,						lowerCAmelCase_       : Optional[int]=24 ,						lowerCAmelCase_       : str=4 ,						lowerCAmelCase_       : List[str]=512 ,						lowerCAmelCase_       : List[str]="relu" ,						lowerCAmelCase_       : Dict=0.0 ,						lowerCAmelCase_       : List[Any]=0.1 ,						lowerCAmelCase_       : Optional[Any]=512 ,						lowerCAmelCase_       : str=2 ,						lowerCAmelCase_       : Dict=0.02 ,						lowerCAmelCase_       : Any=1E-12 ,						lowerCAmelCase_       : List[Any]=0 ,						lowerCAmelCase_       : Union[str, Any]=128 ,						lowerCAmelCase_       : Any=True ,						lowerCAmelCase_       : Optional[Any]=True ,						lowerCAmelCase_       : List[Any]=128 ,						lowerCAmelCase_       : Dict=False ,						lowerCAmelCase_       : Tuple=True ,						lowerCAmelCase_       : Any=4 ,						lowerCAmelCase_       : Optional[Any]="no_norm" ,						lowerCAmelCase_       : Optional[Any]=True ,						lowerCAmelCase_       : Union[str, Any]=None ,						**lowerCAmelCase_       : Union[str, Any] ,						)			->		List[Any]:
  						super().__init__(pad_token_id=lowerCAmelCase_ ,						**lowerCAmelCase_  )
  
  						__A=  vocab_size
  						__A=  hidden_size
  						__A=  num_hidden_layers
  						__A=  num_attention_heads
  						__A=  hidden_act
  						__A=  intermediate_size
  						__A=  hidden_dropout_prob
  						__A=  attention_probs_dropout_prob
  						__A=  max_position_embeddings
  						__A=  type_vocab_size
  						__A=  initializer_range
  						__A=  layer_norm_eps
  						__A=  embedding_size
  						__A=  trigram_input
  						__A=  use_bottleneck
  						__A=  intra_bottleneck_size
  						__A=  use_bottleneck_attention
  						__A=  key_query_shared_bottleneck
  						__A=  num_feedforward_networks
  						__A=  normalization_type
  						__A=  classifier_activation
  
  						if self.use_bottleneck:
  									__A=  intra_bottleneck_size
  						else:
  									__A=  hidden_size
  
  						__A=  classifier_dropout
  
  
  class 	a__				(				a_      ):
  
  
  
  
  
  			'''simple docstring'''
  
  			@property
  			def 				lowerCAmelCase    (     self       : List[str]  )			->		Mapping[str, Mapping[int, str]]:
  						if self.task == "multiple-choice":
  									__A=  {0: 'batch', 1: 'choice', 2: 'sequence'}
  						else:
  									__A=  {0: 'batch', 1: 'sequence'}
  						return OrderedDict(
  						    [
  						        ('input_ids', dynamic_axis),
  						        ('attention_mask', dynamic_axis),
  						        ('token_type_ids', dynamic_axis),
  						    ]  )
  
  
  
  