


from collections import OrderedDict
from typing import Mapping

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


_snake_case             =     logging.get_logger(__name__)

_snake_case             =     {
    '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json''',
    '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json''',
    '''junnyu/roformer_chinese_char_small''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json'''
    ),
    '''junnyu/roformer_chinese_char_base''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_discriminator''': (
        '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_generator''': (
        '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json'''
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}
class 	UpperCAmelCase_					(					a__    ):

   '''simple docstring'''




   __A :      Optional[int]     		=		"""roformer"""






   def __init__(		self						,				__A=5_0000						,				__A=None						,				__A=768						,				__A=12						,				__A=12						,				__A=3072						,				__A="gelu"						,				__A=0.1						,				__A=0.1						,				__A=1536						,				__A=2						,				__A=0.02						,				__A=1e-12						,				__A=0						,				__A=False						,				__A=True						,				**__A						,				):






     """simple docstring"""





     super().__init__(pad_token_id=lowerCAmelCase__						,				**lowerCAmelCase__ )

     lowerCamelCase :					Any    =				vocab_size
     lowerCamelCase :					Any    =				hidden_size if embedding_size is None else embedding_size
     lowerCamelCase :					Optional[Any]    =				hidden_size
     lowerCamelCase :					List[str]    =				num_hidden_layers
     lowerCamelCase :					List[str]    =				num_attention_heads
     lowerCamelCase :					Optional[int]    =				hidden_act
     lowerCamelCase :					Any    =				intermediate_size
     lowerCamelCase :					str    =				hidden_dropout_prob
     lowerCamelCase :					Tuple    =				attention_probs_dropout_prob
     lowerCamelCase :					str    =				max_position_embeddings
     lowerCamelCase :					List[Any]    =				type_vocab_size
     lowerCamelCase :					Optional[Any]    =				initializer_range
     lowerCamelCase :					Dict    =				layer_norm_eps
     lowerCamelCase :					str    =				rotary_value
     lowerCamelCase :					str    =				use_cache



class 	UpperCAmelCase_					(					a__    ):

   '''simple docstring'''




   @property
   def _snake_case    (		self ):






     """simple docstring"""





     if self.task == "multiple-choice":
       lowerCamelCase :					Tuple    =				{0: "batch", 1: "choice", 2: "sequence"}
     else:
       lowerCamelCase :					Any    =				{0: "batch", 1: "sequence"}
     lowerCamelCase :					Union[str, Any]    =				{0: "batch", 1: "sequence"}
     return OrderedDict(
         [
             ("input_ids", dynamic_axis),
             ("attention_mask", dynamic_axis),
             ("token_type_ids", dynamic_axis),
         ] )










"""simple docstring"""




from decimal import Decimal, getcontext
from math import ceil, factorial






def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    int					) ->str:






	'''simple docstring'''






	if not isinstance(_lowercase    ,       _lowercase					):
		raise TypeError("Undefined for non-integers"					)
	elif precision < 1:
		raise ValueError("Undefined for non-natural numbers"					)

	a      :		Tuple	=				precision
	a      :		str	=				ceil(precision / 14					)
	a      :		List[Any]	=				42_6880 * Decimal(1_0005					).sqrt()
	a      :		Union[str, Any]	=				1
	a      :		Dict	=				1359_1409
	a      :		Optional[int]	=				Decimal(_lowercase					)
	for k in range(1    ,       _lowercase					):
		a      :		int	=				factorial(6 * k					) // (factorial(3 * k					) * factorial(_lowercase					) ** 3)
		linear_term += 5_4514_0134
		exponential_term *= -26_2537_4126_4076_8000
		partial_sum += Decimal(multinomial_term * linear_term					) / exponential_term
	return str(constant_term / partial_sum					)[:-1]


if __name__ == "__main__":
		a						: Optional[Any]     	=			50
		print(F'''The first {n} digits of pi is: {pi(n)}''')


