
import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment
class      A__       (						unittest.TestCase    ):





							def       a__			(			self  :       Tuple    )						->		str:



											"""simple docstring"""


											__lowercase								= inspect.getfile(accelerate.test_utils    )
											__lowercase								= os.path.sep.join(mod_file.split(os.path.sep    )[:-1] + ['scripts', 'test_sync.py']    )





							@require_cpu
							def       a__			(			self  :       str    )						->		Any:



											"""simple docstring"""


											debug_launcher(test_sync.main					,			num_processes=1    )





							@require_cpu
							def       a__			(			self  :       Dict    )						->		str:



											"""simple docstring"""


											debug_launcher(test_sync.main    )





							@require_single_gpu
							def       a__			(			self  :       List[str]    )						->		Tuple:



											"""simple docstring"""


											test_sync.main()





							@require_multi_gpu
							def       a__			(			self  :       str    )						->		Union[str, Any]:



											"""simple docstring"""


											print(f"""Found {torch.cuda.device_count()} devices."""    )
											__lowercase								= ['torchrun', f"""--nproc_per_node={torch.cuda.device_count()}""", self.test_file_path]
											with patch_environment(omp_num_threads=1    ):
															execute_subprocess_async(_UpperCAmelCase					,			env=os.environ.copy()    )








from math import pi




def 							__SCREAMING_SNAKE_CASE       (		SCREAMING_SNAKE_CASE	:				float      )					->						float:
				return degree / (180 / pi)


if __name__ == "__main__":
							from doctest import testmod

							testmod()





