






'''simple docstring'''







def     _UpperCamelCase				(  snake_case__				,      snake_case__				):
      __A		 =   sorted(snake_case__				,      key=lambda snake_case__				: value[2]				,      reverse=snake_case__				)

      # Create a list of size equal to the maximum deadline
      # and initialize it with -1
      __A		 =   max(snake_case__				,      key=lambda snake_case__				: value[1]				)[1]
      __A		 =   [-1] * max_deadline

      # Finding the maximum profit and the count of jobs
      __A		 =   0
      __A		 =   0
      for job in jobs:
            # Find a free time slot for this job
            # (Note that we start from the last possible slot)
            for i in range(job[1] - 1				,      -1				,      -1				):
                  if time_slots[i] == -1:
                        __A		 =   job[0]
                        count += 1
                        max_profit += job[2]
                        break
      return [count, max_profit]


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()       )


