
'''simple docstring'''





import math


class 			UpperCamelCase__	:






 def __init__(      self	:Any						,					_A	:Dict						,					_A	:int						,					_A	:List[str]      )					->      List[Any]:







       '''simple docstring'''



       __A													=      x
       __A													=      y
       __A													=      z






 def __repr__(      self	:Dict      )					->      str:







       '''simple docstring'''



       return F'Point({self.x}, {self.y}, {self.z})'





def 							snake_case				(		UpperCAmelCase   ,	UpperCAmelCase						)->      float:







      """simple docstring"""
      return math.sqrt(abs((b.x - a.x) ** 2 + (b.y - a.y) ** 2 + (b.z - a.z) ** 2						)						)


if __name__ == "__main__":
 import doctest

 doctest.testmod()














'''simple docstring'''







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    ):
     '''simple docstring'''







     def      _UpperCamelCase (self     :						int       )	->							Optional[int]:
           __A		 =   inspect.getfile(accelerate.test_utils       )
           __A		 =   os.path.sep.join(mod_file.split(os.path.sep       )[:-1] + ["scripts", "test_sync.py"]       )






     @require_cpu
     def      _UpperCamelCase (self     :						str       )	->							Optional[Any]:
           debug_launcher(test_sync.main					,					num_processes=1       )






     @require_cpu
     def      _UpperCamelCase (self     :						Union[str, Any]       )	->							Optional[Any]:
           debug_launcher(test_sync.main       )






     @require_single_gpu
     def      _UpperCamelCase (self     :						Union[str, Any]       )	->							List[str]:
           test_sync.main()






     @require_multi_gpu
     def      _UpperCamelCase (self     :						Optional[int]       )	->							List[str]:
           print(f"Found {torch.cuda.device_count()} devices."       )
           __A		 =   ["torchrun", f"--nproc_per_node={torch.cuda.device_count()}", self.test_file_path]
           with patch_environment(omp_num_threads=1       ):
                 execute_subprocess_async(lowercase__					,					env=os.environ.copy()       )


