
"""simple docstring"""




from __future__ import annotations

def lowercase_  (   _snake_case   ,_snake_case   ,_snake_case						):
							if days_between_payments <= 0:
														raise ValueError("""days_between_payments must be > 0"""						)
							if daily_interest_rate < 0:
														raise ValueError("""daily_interest_rate must be >= 0"""						)
							if principal <= 0:
														raise ValueError("""principal must be > 0"""						)
							return principal * daily_interest_rate * days_between_payments

def lowercase_  (   _snake_case   ,_snake_case   ,_snake_case   ,):
							if number_of_compounding_periods <= 0:
														raise ValueError("""number_of_compounding_periods must be > 0"""						)
							if nominal_annual_interest_rate_percentage < 0:
														raise ValueError("""nominal_annual_interest_rate_percentage must be >= 0"""						)
							if principal <= 0:
														raise ValueError("""principal must be > 0"""						)

							return principal * (
							    (1 + nominal_annual_interest_rate_percentage) ** number_of_compounding_periods
							    - 1
							)

def lowercase_  (   _snake_case   ,_snake_case   ,_snake_case   ,):
							if number_of_years <= 0:
														raise ValueError("""number_of_years must be > 0"""						)
							if nominal_annual_percentage_rate < 0:
														raise ValueError("""nominal_annual_percentage_rate must be >= 0"""						)
							if principal <= 0:
														raise ValueError("""principal must be > 0"""						)

							return compound_interest(
							    _snake_case   ,nominal_annual_percentage_rate / 365   ,number_of_years * 365						)


if __name__ == "__main__":
					import doctest

					doctest.testmod()






"""simple docstring"""




import pickle
import unittest

import torch

from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu



@require_cpu
class 	lowerCAmelCase_						(unittest.TestCase  ):


				"""simple docstring"""



				def 	__magic_name__    (self    )					->		Union[str, Any]:



											"""simple docstring"""




											SCREAMING_SNAKE_CASE__						:       List[Any]           =   torch.nn.Linear(10   ,       10    )
											SCREAMING_SNAKE_CASE__						:       Optional[int]           =   torch.optim.SGD(model.parameters()   ,       0.1    )
											SCREAMING_SNAKE_CASE__						:       int           =   Accelerator()
											SCREAMING_SNAKE_CASE__						:       List[Any]           =   accelerator.prepare(SCREAMING_SNAKE_CASE__    )
											try:
																		pickle.loads(pickle.dumps(SCREAMING_SNAKE_CASE__    )    )
											except Exception as e:
																		self.fail(F'''Accelerated optimizer pickling failed with {e}'''    )
											AcceleratorState._reset_state()




