






import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class 							A_    (						__lowercase			):






 '''simple docstring'''




 _SCREAMING_SNAKE_CASE							:			Any =					ComputeEnvironment.AMAZON_SAGEMAKER
 _SCREAMING_SNAKE_CASE							:			Union[str, Any] =					True
 _SCREAMING_SNAKE_CASE							:			Optional[int] =					"ml.p3.2xlarge"
 _SCREAMING_SNAKE_CASE							:			List[str] =					"accelerate_sagemaker_execution_role"
 _SCREAMING_SNAKE_CASE							:			int =					"hf-sm"
 _SCREAMING_SNAKE_CASE							:			Tuple =					"us-east-1"
 _SCREAMING_SNAKE_CASE							:			List[Any] =					1
 _SCREAMING_SNAKE_CASE							:			Optional[Any] =					"accelerate-sagemaker-1"
 _SCREAMING_SNAKE_CASE							:			Any =					"1.6"
 _SCREAMING_SNAKE_CASE							:			Tuple =					"4.4"
 _SCREAMING_SNAKE_CASE							:			Optional[Any] =					"train.py"
 _SCREAMING_SNAKE_CASE							:			Dict =					[
     "--model_name_or_path",
     "bert",
     "--do_train",
     "False",
     "--epochs",
     "3",
     "--learning_rate",
     "5e-5",
     "--max_steps",
     "50.5",
 ]
 _SCREAMING_SNAKE_CASE							:			List[str] =					[
     "--model_name_or_path",
     "bert",
     "--do_train",
     "--do_test",
     "False",
     "--do_predict",
     "--epochs",
     "3",
     "--learning_rate",
     "5e-5",
     "--max_steps",
     "50.5",
 ]



class 							A_    (						unittest.TestCase			):






 '''simple docstring'''




 def  snake_case__				(	self) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      int			  =				_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args)
     assert isinstance(converted_args['''model_name_or_path''']							,  _A)
     assert isinstance(converted_args['''do_train''']							,  _A)
     assert isinstance(converted_args['''epochs''']							,  _A)
     assert isinstance(converted_args['''learning_rate''']							,  _A)
     assert isinstance(converted_args['''max_steps''']							,  _A)

     with pytest.raises(_A):
         _convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args)












from math import pow, sqrt

def      _lowerCamelCase	(						*__A    :							float )      ->					bool:
    _UpperCAmelCase				:      str			  =				len(__A ) > 0 and all(value > 0.0 for value in values )
    return result

def      _lowerCamelCase	(						__A    :							float		,		__A    :							float )      ->					float | ValueError:
    return (
        round(sqrt(molar_mass_a / molar_mass_a )		,		6 )
        if validate(__A		,		__A )
        else ValueError('''Input Error: Molar mass values must greater than 0.''' )
    )

def      _lowerCamelCase	(						__A    :							float		,		__A    :							float		,		__A    :							float )      ->					float | ValueError:
    return (
        round(effusion_rate * sqrt(molar_mass_a / molar_mass_a )		,		6 )
        if validate(__A		,		__A		,		__A )
        else ValueError(
            '''Input Error: Molar mass and effusion rate values must greater than 0.''' )
    )

def      _lowerCamelCase	(						__A    :							float		,		__A    :							float		,		__A    :							float )      ->					float | ValueError:
    return (
        round(effusion_rate / sqrt(molar_mass_a / molar_mass_a )		,		6 )
        if validate(__A		,		__A		,		__A )
        else ValueError(
            '''Input Error: Molar mass and effusion rate values must greater than 0.''' )
    )

def      _lowerCamelCase	(						__A    :							float		,		__A    :							float		,		__A    :							float )      ->					float | ValueError:
    return (
        round(molar_mass / pow(effusion_rate_a / effusion_rate_a		,		2 )		,		6 )
        if validate(__A		,		__A		,		__A )
        else ValueError(
            '''Input Error: Molar mass and effusion rate values must greater than 0.''' )
    )


def      _lowerCamelCase	(						__A    :							float		,		__A    :							float		,		__A    :							float )      ->					float | ValueError:
    return (
        round(pow(effusion_rate_a / effusion_rate_a		,		2 ) / molar_mass		,		6 )
        if validate(__A		,		__A		,		__A )
        else ValueError(
            '''Input Error: Molar mass and effusion rate values must greater than 0.''' )
    )




