


'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

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


a_   :      int				    =      logging.get_logger(__name__)

a_   :      Optional[Any]				    =      {
    "YituTech/conv-bert-base": "https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json",
    "YituTech/conv-bert-medium-small": (
        "https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"
    ),
    "YituTech/conv-bert-small": "https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}




class 	a       (       _SCREAMING_SNAKE_CASE    ):
 _lowerCAmelCase	   =		"""convbert"""
 def __init__(	self ,			__magic_name__=3_05_22 ,			__magic_name__=7_68 ,			__magic_name__=12 ,			__magic_name__=12 ,			__magic_name__=30_72 ,			__magic_name__="gelu" ,			__magic_name__=0.1 ,			__magic_name__=0.1 ,			__magic_name__=5_12 ,			__magic_name__=2 ,			__magic_name__=0.0_2 ,			__magic_name__=1e-12 ,			__magic_name__=1 ,			__magic_name__=0 ,			__magic_name__=2 ,			__magic_name__=7_68 ,			__magic_name__=2 ,			__magic_name__=9 ,			__magic_name__=1 ,			__magic_name__=None ,			**__magic_name__ ,			)   ->							Optional[Any]:
      super().__init__(
          pad_token_id=__magic_name__ ,			bos_token_id=__magic_name__ ,			eos_token_id=__magic_name__ ,			**__magic_name__ ,			)

      _a      =							vocab_size
      _a      =							hidden_size
      _a      =							num_hidden_layers
      _a      =							num_attention_heads
      _a      =							intermediate_size
      _a      =							hidden_act
      _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      =							head_ratio
      _a      =							conv_kernel_size
      _a      =							num_groups
      _a      =							classifier_dropout





class 	a       (       _SCREAMING_SNAKE_CASE    ):
 @property
 def 							__UpperCAmelCase						(	self  )   ->							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),
          ]  )





'''simple docstring'''






def 		_A			(lowerCAmelCase__					:int						)				->					int:




     '''simple docstring'''



     assert (
         isinstance(lowerCAmelCase__			,  lowerCAmelCase__						) and number_of_steps > 0
     ), f'number_of_steps needs to be positive integer, your input {number_of_steps}'
     if number_of_steps == 1:
          return 1
     _a ,				_a      =							1, 1
     for _ in range(number_of_steps - 1						):
          _a ,				_a      =							current + previous, current
     return current


if __name__ == "__main__":
 import doctest

 doctest.testmod()

