





import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union

from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings


_a						=   logging.getLogger(__name__)






@dataclass
@add_start_docstrings(TrainingArguments.__doc__				)
class       __A					(					lowerCAmelCase				):

			'''simple docstring'''







			lowerCAmelCase_							  =		field(default=lowerCAmelCase    ,       metadata={"""help""": """Whether to use SortishSampler or not."""}				)
			lowerCAmelCase_							  =		field(
			    default=lowerCAmelCase    ,       metadata={"""help""": """Whether to use generate to calculate generative metrics (ROUGE, BLEU)."""}				)
			lowerCAmelCase_							  =		field(
			    default=lowerCAmelCase    ,       metadata={
			        """help""": (
			            """The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default """
			            """to the `max_length` value of the model configuration."""
			        )
			    }    ,       )
			lowerCAmelCase_							  =		field(
			    default=lowerCAmelCase    ,       metadata={
			        """help""": (
			            """The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default """
			            """to the `num_beams` value of the model configuration."""
			        )
			    }    ,       )
			lowerCAmelCase_							  =		field(
			    default=lowerCAmelCase    ,       metadata={
			        """help""": """Model id, file path or url pointing to a GenerationConfig json file, to use during prediction."""
			    }    ,       )





			def 	__lowerCamelCase       (					self							):



				'''simple docstring'''







				lowerCamelCase__              =	super().to_dict()
				for k, v in d.items():
					if isinstance(__lowerCAmelCase ,						__lowerCAmelCase							):
						lowerCamelCase__              =	v.to_dict()
				return d










from __future__ import annotations





def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case							)       ->   float:







	'''simple docstring'''







	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 lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,)       ->   float:







	'''simple docstring'''







	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 lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,)       ->   float:







	'''simple docstring'''







	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()



