






'''simple docstring'''



import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


lowerCamelCase	 =       logging.getLogger(__name__)





@dataclass
class _UpperCamelCase		(     A		):





				'''simple docstring'''





				lowerCAmelCase__					    =    field(
				    default=0.0      ,       metadata={"""help""": """The label smoothing epsilon to apply (if not zero)."""}		)
				lowerCAmelCase__					    =    field(default=A      ,       metadata={"""help""": """Whether to SortishSamler or not."""}		)
				lowerCAmelCase__					    =    field(
				    default=A      ,       metadata={"""help""": """Whether to use generate to calculate generative metrics (ROUGE, BLEU)."""}		)
				lowerCAmelCase__					    =    field(default=A      ,       metadata={"""help""": """whether to use adafactor"""}		)
				lowerCAmelCase__					    =    field(
				    default=A      ,       metadata={"""help""": """Encoder layer dropout probability. Goes into model.config."""}		)
				lowerCAmelCase__					    =    field(
				    default=A      ,       metadata={"""help""": """Decoder layer dropout probability. Goes into model.config."""}		)
				lowerCAmelCase__					    =    field(default=A      ,       metadata={"""help""": """Dropout probability. Goes into model.config."""}		)
				lowerCAmelCase__					    =    field(
				    default=A      ,       metadata={"""help""": """Attention dropout probability. Goes into model.config."""}		)
				lowerCAmelCase__					    =    field(
				    default="""linear"""      ,       metadata={"""help""": f"""Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()		)}"""}      ,       )








'''simple docstring'''



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



def   _A       (   _lowerCAmelCase					):



							"""simple docstring"""



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

							__lowercase       	=precision
							__lowercase       	=ceil(precision / 14					)
							__lowercase       	=426_880 * Decimal(10_005					).sqrt()
							__lowercase       	=1
							__lowercase       	=13_591_409
							__lowercase       	=Decimal(_lowerCAmelCase					)
							for k in range(1  ,   _lowerCAmelCase					):
														__lowercase       	=factorial(6 * k					) // (factorial(3 * k					) * factorial(_lowerCAmelCase					) ** 3)
														linear_term += 545_140_134
														exponential_term *= -262_537_412_640_768_000
														partial_sum += Decimal(multinomial_term * linear_term					) / exponential_term
							return str(constant_term / partial_sum					)[:-1]


if __name__ == "__main__":
		lowerCamelCase	 =       50
		print(f"The first {n} digits of pi is: {pi(n)}")



