





"""simple docstring"""


def      UpperCamelCase							(SCREAMING_SNAKE_CASE = 6008_5147_5143     ):

						try:
												UpperCamelCase				:		Optional[Any]				   =			int(SCREAMING_SNAKE_CASE     )
						except (TypeError, ValueError):
												raise TypeError("""Parameter n must be int or castable to int."""     )
						if n <= 0:
												raise ValueError("""Parameter n must be greater than or equal to one."""     )
						UpperCamelCase				:		Dict				   =			2
						UpperCamelCase				:		List[Any]				   =			0
						if n == 2:
												return 2
						while n > 2:
												while n % i != 0:
																		i += 1
												UpperCamelCase				:		Optional[int]				   =			i
												while n % i == 0:
																		UpperCamelCase				:		Optional[Any]				   =			n // i
												i += 1
						return int(SCREAMING_SNAKE_CASE     )


if __name__ == "__main__":
		print(f'''{solution() = }''')










"""simple docstring"""


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

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


__magic_name__       :					Dict						=			logging.getLogger(__name__)






@dataclass
class 							lowercase__			(   __SCREAMING_SNAKE_CASE	):

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



