

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_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment





@require_huggingface_suite
class  __UpperCAmelCase					(	unittest.TestCase						):



   def 	__magic_name__   (							self							:					List[str]						):
     UpperCAmelCase	:							List[Any]						=			inspect.getfile(accelerate.test_utils						)
     UpperCAmelCase	:							Any						=			os.path.sep.join(
         mod_file.split(os.path.sep						)[:-1] + ['''scripts''', '''external_deps''', '''test_metrics.py''']						)

     from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

     UpperCAmelCase	:							int						=			test_metrics



   @require_cpu
   def 	__magic_name__   (							self							:					Optional[int]						):
     debug_launcher(self.test_metrics.main,		num_processes=1						)



   @require_cpu
   def 	__magic_name__   (							self							:					Any						):
     debug_launcher(self.test_metrics.main						)



   @require_single_gpu
   def 	__magic_name__   (							self							:					int						):
     self.test_metrics.main()





   @require_multi_gpu
   def 	__magic_name__   (							self							:					int						):
     print(F'''Found {torch.cuda.device_count()} devices.'''						)
     UpperCAmelCase	:							List[Any]						=			['''torchrun''', F'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
     with patch_environment(omp_num_threads=1						):
       execute_subprocess_async(__A,		env=os.environ.copy()						)








from math import log

from scipy.constants import Boltzmann, physical_constants

_lowerCamelCase    :       Tuple        =							3_0_0  # TEMPERATURE (unit = K)

def       a__					(		UpperCAmelCase							:      float    ,			UpperCAmelCase							:      float    ,			UpperCAmelCase							:      float    ,			)  ->						float:

  if donor_conc <= 0:
    raise ValueError('''Donor concentration should be positive'''      )
  elif acceptor_conc <= 0:
    raise ValueError('''Acceptor concentration should be positive'''      )
  elif intrinsic_conc <= 0:
    raise ValueError('''Intrinsic concentration should be positive'''      )
  elif donor_conc <= intrinsic_conc:
    raise ValueError(
        '''Donor concentration should be greater than intrinsic concentration'''      )
  elif acceptor_conc <= intrinsic_conc:
    raise ValueError(
        '''Acceptor concentration should be greater than intrinsic concentration'''      )
  else:
    return (
        Boltzmann
        * T
        * log((donor_conc * acceptor_conc) / intrinsic_conc**2      )
        / physical_constants["electron volt"][0]
    )


if __name__ == "__main__":
     import doctest

     doctest.testmod()





