


'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


lowercase__				     =		logging.get_logger(__name__)

lowercase__				     =		{
    "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 						__SCREAMING_SNAKE_CASE					(      lowerCamelCase__ ):
     UpperCAmelCase 					=				'''convbert'''






     def __init__(			self     ,							__UpperCamelCase=30_522     ,							__UpperCamelCase=768     ,							__UpperCamelCase=12     ,							__UpperCamelCase=12     ,							__UpperCamelCase=3_072     ,							__UpperCamelCase="gelu"     ,							__UpperCamelCase=0.1     ,							__UpperCamelCase=0.1     ,							__UpperCamelCase=512     ,							__UpperCamelCase=2     ,							__UpperCamelCase=0.02     ,							__UpperCamelCase=1e-12     ,							__UpperCamelCase=1     ,							__UpperCamelCase=0     ,							__UpperCamelCase=2     ,							__UpperCamelCase=768     ,							__UpperCamelCase=2     ,							__UpperCamelCase=9     ,							__UpperCamelCase=1     ,							__UpperCamelCase=None     ,							**__UpperCamelCase     ,							)       ->    Optional[int]:
          super().__init__(
              pad_token_id=__UpperCamelCase     ,							bos_token_id=__UpperCamelCase     ,							eos_token_id=__UpperCamelCase     ,							**__UpperCamelCase     ,							)

          _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 						__SCREAMING_SNAKE_CASE					(      lowerCamelCase__ ):






     @property
     def  a_					(			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'''

from math import factorial, pi






def __UpperCamelCase   (			__lowerCamelCase		: float      ,  __lowerCamelCase		: int = 30				)      ->     float:







     '''simple docstring'''






     if not isinstance(__lowerCamelCase      ,  (int, float)				):
          raise ValueError("maclaurin_sin() requires either an int or float for theta"				)

     if not isinstance(__lowerCamelCase      ,  __lowerCamelCase				) or accuracy <= 0:
          raise ValueError("maclaurin_sin() requires a positive int for accuracy"				)

     _a						=		float(__lowerCamelCase				)
     _a						=		theta // (2 * pi)
     theta -= 2 * div * pi
     return sum(
         (-1) ** r * theta ** (2 * r + 1) / factorial(2 * r + 1				) for r in range(__lowerCamelCase				)				)






def __UpperCamelCase   (			__lowerCamelCase		: float      ,  __lowerCamelCase		: int = 30				)      ->     float:







     '''simple docstring'''






     if not isinstance(__lowerCamelCase      ,  (int, float)				):
          raise ValueError("maclaurin_cos() requires either an int or float for theta"				)

     if not isinstance(__lowerCamelCase      ,  __lowerCamelCase				) or accuracy <= 0:
          raise ValueError("maclaurin_cos() requires a positive int for accuracy"				)

     _a						=		float(__lowerCamelCase				)
     _a						=		theta // (2 * pi)
     theta -= 2 * div * pi
     return sum((-1) ** r * theta ** (2 * r) / factorial(2 * r				) for r in range(__lowerCamelCase				)				)


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   print(maclaurin_sin(10))
   print(maclaurin_sin(-10))
   print(maclaurin_sin(10, 15))
   print(maclaurin_sin(-10, 15))

   print(maclaurin_cos(5))
   print(maclaurin_cos(-5))
   print(maclaurin_cos(10, 15))
   print(maclaurin_cos(-10, 15))

