code: 
  """simple docstring"""
  
  
  
  
  
  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	 =							{
      '''nghuyong/ernie-1.0-base-zh''': '''https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json''',
      '''nghuyong/ernie-2.0-base-en''': '''https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json''',
      '''nghuyong/ernie-2.0-large-en''': '''https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json''',
      '''nghuyong/ernie-3.0-base-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json''',
      '''nghuyong/ernie-3.0-medium-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json''',
      '''nghuyong/ernie-3.0-mini-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json''',
      '''nghuyong/ernie-3.0-micro-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json''',
      '''nghuyong/ernie-3.0-nano-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json''',
      '''nghuyong/ernie-gram-zh''': '''https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json''',
      '''nghuyong/ernie-health-zh''': '''https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json''',
  }
  
  
  class A_			(A__   ):
  
  
  
  
    '''simple docstring'''
    SCREAMING_SNAKE_CASE__    :		int						  =	'''ernie'''
  
  
  
  
  
  
  
    def __init__(	self       ,     lowercase_=3_0522       ,     lowercase_=768       ,     lowercase_=12       ,     lowercase_=12       ,     lowercase_=3072       ,     lowercase_="gelu"       ,     lowercase_=0.1       ,     lowercase_=0.1       ,     lowercase_=512       ,     lowercase_=2       ,     lowercase_=3       ,     lowercase_=False       ,     lowercase_=0.02       ,     lowercase_=1E-1_2       ,     lowercase_=0       ,     lowercase_="absolute"       ,     lowercase_=True       ,     lowercase_=None       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       super().__init__(pad_token_id=lowercase_       ,     **lowercase_						)
  
       UpperCAmelCase_      :      Optional[Any]      =					vocab_size
       UpperCAmelCase_      :      Optional[Any]      =					hidden_size
       UpperCAmelCase_      :      List[Any]      =					num_hidden_layers
       UpperCAmelCase_      :      Tuple      =					num_attention_heads
       UpperCAmelCase_      :      List[str]      =					hidden_act
       UpperCAmelCase_      :      Tuple      =					intermediate_size
       UpperCAmelCase_      :      List[str]      =					hidden_dropout_prob
       UpperCAmelCase_      :      Optional[Any]      =					attention_probs_dropout_prob
       UpperCAmelCase_      :      List[str]      =					max_position_embeddings
       UpperCAmelCase_      :      Union[str, Any]      =					type_vocab_size
       UpperCAmelCase_      :      List[Any]      =					task_type_vocab_size
       UpperCAmelCase_      :      Dict      =					use_task_id
       UpperCAmelCase_      :      str      =					initializer_range
       UpperCAmelCase_      :      Tuple      =					layer_norm_eps
       UpperCAmelCase_      :      List[str]      =					position_embedding_type
       UpperCAmelCase_      :      Optional[int]      =					use_cache
       UpperCAmelCase_      :      List[Any]      =					classifier_dropout
  
  
  
  
  class A_			(A__   ):
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    @property
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
  
  
  
  
  
  
       if self.task == "multiple-choice":
          UpperCAmelCase_      :      int      =					{0: "batch", 1: "choice", 2: "sequence"}
       else:
          UpperCAmelCase_      :      Optional[int]      =					{0: "batch", 1: "sequence"}
       return OrderedDict(
           [
               ("input_ids", dynamic_axis),
               ("attention_mask", dynamic_axis),
               ("token_type_ids", dynamic_axis),
               ("task_type_ids", dynamic_axis),
           ]						)
  
  
  
style_context: 
  """simple docstring"""
  
  
  
  
  
  def 			__a  (	__lowerCamelCase = 1000						):
     UpperCAmelCase_      :      List[Any]      =					0
     UpperCAmelCase_      :      List[str]      =					(n - 1) // 3
     total += ((terms) * (6 + (terms - 1) * 3)) // 2  # total of an A.P.
     UpperCAmelCase_      :      Any      =					(n - 1) // 5
     total += ((terms) * (10 + (terms - 1) * 5)) // 2
     UpperCAmelCase_      :      Optional[int]      =					(n - 1) // 15
     total -= ((terms) * (30 + (terms - 1) * 15)) // 2
     return total
  
  
  if __name__ == "__main__":
      print(f"""{solution() = }""")
  
  
  