

"""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_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment
@require_huggingface_suite
class      _UpperCAmelCase   (							unittest.TestCase       ):



	def        a  (  self     :       str						):
		__UpperCAmelCase      		= inspect.getfile(accelerate.test_utils						)
		__UpperCAmelCase      		= 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      		= test_metrics



	@require_cpu
	def        a  (  self     :       Union[str, Any]						):
		debug_launcher(self.test_metrics.main			,    num_processes=1						)



	@require_cpu
	def        a  (  self     :       Dict						):
		debug_launcher(self.test_metrics.main						)



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



	@require_multi_gpu
	def        a  (  self     :       Tuple						):
		print(F'''Found {torch.cuda.device_count()} devices.'''						)
		__UpperCAmelCase      		= ['''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()						)







'''simple docstring'''






from __future__ import annotations

import numpy as np
def   UpperCamelCase__ (						lowerCAmelCase    ):





      """simple docstring"""


      _lowerCAmelCase	,				_lowerCAmelCase					=				np.shape(lowerCAmelCase    )
      if rows != columns:
            _lowerCAmelCase					=				(
                """'table' has to be of square shaped array but got a """
                f"{rows}x{columns} array:\n{table}"
            )
            raise ValueError(lowerCAmelCase    )

      _lowerCAmelCase					=				np.zeros((rows, columns)    )
      _lowerCAmelCase					=				np.zeros((rows, columns)    )
      for i in range(lowerCAmelCase    ):
            for j in range(lowerCAmelCase    ):
                  _lowerCAmelCase					=				sum(lower[i][k] * upper[k][j] for k in range(lowerCAmelCase    )    )
                  if upper[j][j] == 0:
                        raise ArithmeticError("""No LU decomposition exists"""    )
                  _lowerCAmelCase					=				(table[i][j] - total) / upper[j][j]
            _lowerCAmelCase					=				1
            for j in range(lowerCAmelCase				,      lowerCAmelCase    ):
                  _lowerCAmelCase					=				sum(lower[i][k] * upper[k][j] for k in range(lowerCAmelCase    )    )
                  _lowerCAmelCase					=				table[i][j] - total
      return lower, upper


if __name__ == "__main__":
      import doctest

      doctest.testmod()






