




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

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


__SCREAMING_SNAKE_CASE 						=logging.getLogger(__name__)






@dataclass
class  __magic_name__						(  __UpperCAmelCase):
				'''simple docstring'''







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








from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
__SCREAMING_SNAKE_CASE 						=1.0_5_4_5_7_1_8_1_7e-3_4  # unit of ℏ : J * s

__SCREAMING_SNAKE_CASE 						=3e8  # unit of c : m * s^-1

def 			a   (_lowerCAmelCase  ,    _lowerCAmelCase  ,    _lowerCAmelCase     ):

							if (force, area, distance).count(0     ) != 1:
														raise ValueError('''One and only one argument must be 0'''     )
							if force < 0:
														raise ValueError('''Magnitude of force can not be negative'''     )
							if distance < 0:
														raise ValueError('''Distance can not be negative'''     )
							if area < 0:
														raise ValueError('''Area can not be negative'''     )
							if force == 0:
														SCREAMING_SNAKE_CASE_   	=    (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
														    2_4_0 * (distance) ** 4
														)
														return {"force": force}
							elif area == 0:
														SCREAMING_SNAKE_CASE_   	=    (2_4_0 * force * (distance) ** 4) / (
														    REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
														)
														return {"area": area}
							elif distance == 0:
														SCREAMING_SNAKE_CASE_   	=    (
														    (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (2_4_0 * force)
														) ** (1 / 4)
														return {"distance": distance}
							raise ValueError('''One and only one argument must be 0'''     )


# Run doctest
if __name__ == "__main__":
			import doctest

			doctest.testmod()


