




"""simple docstring"""

from __future__ import annotations

from math import pow, sqrt






def 		_snake_case	(   _snake_case				:   float							,    _snake_case				:   float							,    _snake_case				:   float				)       ->   dict[str, float]:






      '''simple docstring'''


      if (resistance, reactance, impedance).count(0				) != 1:
            raise ValueError('One and only one argument must be 0'				)
      if resistance == 0:
            return {"resistance": sqrt(pow(_snake_case							,    2				) - pow(_snake_case							,    2				)				)}
      elif reactance == 0:
            return {"reactance": sqrt(pow(_snake_case							,    2				) - pow(_snake_case							,    2				)				)}
      elif impedance == 0:
            return {"impedance": sqrt(pow(_snake_case							,    2				) + pow(_snake_case							,    2				)				)}
      else:
            raise ValueError('Exactly one argument must be 0'				)


if __name__ == "__main__":
       import doctest

       doctest.testmod()







"""simple docstring"""

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

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


a							      =     logging.getLogger(__name__)





@dataclass
class 							lowercase_			(	__lowerCAmelCase				):



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

