"""simple docstring"""



from math import gcd

def    _A(		lowerCAmelCase = 1_2000       ):
							A__					:    List[str]														= 0
							for d in range(max_d + 1       ):
														for n in range(d // 3 + 1 ,     (d + 1) // 2       ):
																					if gcd(UpperCamelCase__ ,     UpperCamelCase__       ) == 1:
																												fractions_number += 1
							return fractions_number


if __name__ == "__main__":
	print(F'{solution() = }')






"""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 	__UpperCAmelCase						(unittest.TestCase    ):







			'''simple docstring'''





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    Optional[int]														= inspect.getfile(accelerate.test_utils       )
										A__					:    Tuple														= os.path.sep.join(mod_file.split(os.path.sep       )[:-1] + ["""scripts""", """test_sync.py"""]       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main      ,			num_processes=1       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main       )





			@require_single_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										test_sync.main()





			@require_multi_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


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





