






'''simple docstring'''




import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock

import torch

from ..state import AcceleratorState, PartialState
from ..utils import (
    gather,
    is_bnb_available,
    is_comet_ml_available,
    is_datasets_available,
    is_deepspeed_available,
    is_mps_available,
    is_safetensors_available,
    is_tensorboard_available,
    is_torch_version,
    is_tpu_available,
    is_transformers_available,
    is_wandb_available,
    is_xpu_available,
)

def    __lowercase		(     __lowercase  ,    __lowercase=False			)			->		int:

      '''simple docstring'''


      try:
            _A     	=      os.environ[key]
      except KeyError:
            # KEY isn't set, default to `default`.
            _A     	=      default
      else:
            # KEY is set, convert it to True or False.
            try:
                  _A     	=      strtobool(__UpperCAmelCase			)
            except ValueError:
                  # More values are supported, but let's keep the message simple.
                  raise ValueError(F'''If set, {key} must be yes or no.'''			)
      return _value


lowerCamelCase_				   =   parse_flag_from_env('''RUN_SLOW''', default=False)

def    __lowercase		(     __lowercase			)			->		int:

      '''simple docstring'''


      return unittest.skip("Test was skipped"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		Dict:

      '''simple docstring'''


      return unittest.skipUnless(_run_slow_tests  ,    "test is slow"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		int:

      '''simple docstring'''


      return unittest.skipUnless(not torch.cuda.is_available()  ,    "test requires only a CPU"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		List[str]:

      '''simple docstring'''


      return unittest.skipUnless(torch.cuda.is_available()  ,    "test requires a GPU"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		List[Any]:

      '''simple docstring'''


      return unittest.skipUnless(is_xpu_available()  ,    "test requires a XPU"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		str:

      '''simple docstring'''


      return unittest.skipUnless(is_mps_available()  ,    "test requires a `mps` backend support in `torch`"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		int:

      '''simple docstring'''


      return unittest.skipUnless(
          is_transformers_available() and is_datasets_available()  ,    "test requires the Hugging Face suite"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		str:

      '''simple docstring'''


      return unittest.skipUnless(is_bnb_available()  ,    "test requires the bitsandbytes library"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		str:

      '''simple docstring'''


      return unittest.skipUnless(is_tpu_available()  ,    "test requires TPU"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		int:

      '''simple docstring'''


      return unittest.skipUnless(torch.cuda.device_count() == 1  ,    "test requires a GPU"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		List[Any]:

      '''simple docstring'''


      return unittest.skipUnless(torch.xpu.device_count() == 1  ,    "test requires a XPU"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		str:

      '''simple docstring'''


      return unittest.skipUnless(torch.cuda.device_count() > 1  ,    "test requires multiple GPUs"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		Optional[int]:

      '''simple docstring'''


      return unittest.skipUnless(torch.xpu.device_count() > 1  ,    "test requires multiple XPUs"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		Any:

      '''simple docstring'''


      return unittest.skipUnless(is_safetensors_available()  ,    "test requires safetensors"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		Dict:

      '''simple docstring'''


      return unittest.skipUnless(is_deepspeed_available()  ,    "test requires DeepSpeed"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		int:

      '''simple docstring'''


      return unittest.skipUnless(is_torch_version(">="  ,    "1.12.0"			)  ,    "test requires torch version >= 1.12.0"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase=None  ,    __lowercase=None			)			->		Optional[int]:

      '''simple docstring'''


      if test_case is None:
            return partial(__UpperCAmelCase  ,    version=__UpperCAmelCase			)
      return unittest.skipUnless(is_torch_version(">="  ,    __UpperCAmelCase			)  ,    F'''test requires torch version >= {version}'''			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		int:

      '''simple docstring'''


      return unittest.skipUnless(is_tensorboard_available()  ,    "test requires Tensorboard"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		Optional[Any]:

      '''simple docstring'''


      return unittest.skipUnless(is_wandb_available()  ,    "test requires wandb"			)(__UpperCAmelCase			)

def    __lowercase		(     __lowercase			)			->		Tuple:

      '''simple docstring'''


      return unittest.skipUnless(is_comet_ml_available()  ,    "test requires comet_ml"			)(__UpperCAmelCase			)


lowerCamelCase_				   =   (
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)

def    __lowercase		(     __lowercase			)			->		Optional[int]:

      '''simple docstring'''


      return unittest.skipUnless(
          _atleast_one_tracker_available  ,    "test requires at least one tracker to be available and for `comet_ml` to not be installed"  ,    )(__UpperCAmelCase			)

class   _UpperCAmelCase     (	unittest.TestCase		):




   """simple docstring"""

   snake_case       							=		True

   @classmethod
   def 		lowerCAmelCase					(						cls					:      Optional[int]						):





         '''simple docstring'''





         _A     	=      tempfile.mkdtemp()

   @classmethod
   def 		lowerCAmelCase					(						cls					:      Optional[int]						):





         '''simple docstring'''





         if os.path.exists(cls.tmpdir						):
               shutil.rmtree(cls.tmpdir						)

   def 		lowerCAmelCase					(						self					:      Optional[Any]						):





         '''simple docstring'''





         if self.clear_on_setup:
               for path in Path(self.tmpdir						).glob("**/*"						):
                     if path.is_file():
                           path.unlink()
                     elif path.is_dir():
                           shutil.rmtree(a_						)





class   _UpperCAmelCase     (	unittest.TestCase		):




   """simple docstring"""

   def 		lowerCAmelCase					(						self					:      Optional[int]						):





         '''simple docstring'''





         super().tearDown()
         # Reset the state of the AcceleratorState singleton.
         AcceleratorState._reset_state()
         PartialState._reset_state()





class   _UpperCAmelCase     (	unittest.TestCase		):




   """simple docstring"""

   def 		lowerCAmelCase					(						self					:      str , __UpperCAmelCase					:      Union[mock.Mock, List[mock.Mock]]						):





         '''simple docstring'''





         _A     	=      mocks if isinstance(a_ , (tuple, list)						) else [mocks]
         for m in self.mocks:
               m.start()
               self.addCleanup(m.stop						)





def    __lowercase		(     __lowercase			)			->		Any:

      '''simple docstring'''


      _A     	=      AcceleratorState()
      _A     	=      tensor[None].clone().to(state.device			)
      _A     	=      gather(__UpperCAmelCase			).cpu()
      _A     	=      tensor[0].cpu()
      for i in range(tensors.shape[0]			):
            if not torch.equal(tensors[i]  ,    __UpperCAmelCase			):
                  return False
      return True

class   _UpperCAmelCase     :




   """simple docstring"""

   def __init__(						self					:      List[Any] , __UpperCAmelCase					:      List[Any] , __UpperCAmelCase					:      List[str] , __UpperCAmelCase					:      List[str]						):





         '''simple docstring'''





         _A     	=      returncode
         _A     	=      stdout
         _A     	=      stderr





async def    __lowercase		(     __lowercase  ,    __lowercase			)			->		str:

      '''simple docstring'''


      while True:
            _A     	=      await stream.readline()
            if line:
                  callback(__UpperCAmelCase			)
            else:
                  break

async def    __lowercase		(     __lowercase  ,    __lowercase=None  ,    __lowercase=None  ,    __lowercase=None  ,    __lowercase=False  ,    __lowercase=False			)			->		_RunOutput:

      '''simple docstring'''


      if echo:
            print("\nRunning: "  ,    " ".join(__UpperCAmelCase			)			)

      _A     	=      await asyncio.create_subprocess_exec(
          cmd[0]  ,    *cmd[1:]  ,    stdin=__UpperCAmelCase  ,    stdout=asyncio.subprocess.PIPE  ,    stderr=asyncio.subprocess.PIPE  ,    env=__UpperCAmelCase  ,    )

      # note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe
      # https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait
      #
      # If it starts hanging, will need to switch to the following code. The problem is that no data
      # will be seen until it's done and if it hangs for example there will be no debug info.
      # out, err = await p.communicate()
      # return _RunOutput(p.returncode, out, err)

      _A     	=      []
      _A     	=      []

      def tee(__lowercase  ,    __lowercase  ,    __lowercase  ,    __lowercase=""			):
            _A     	=      line.decode("utf-8"			).rstrip()
            sink.append(__UpperCAmelCase			)
            if not quiet:
                  print(__UpperCAmelCase  ,    __UpperCAmelCase  ,    file=__UpperCAmelCase			)

    # XXX: the timeout doesn't seem to make any difference here
      await asyncio.wait(
          [
              asyncio.create_task(_read_stream(p.stdout  ,    lambda __lowercase			: tee(__UpperCAmelCase  ,    __UpperCAmelCase  ,    sys.stdout  ,    label="stdout:"			)			)			),
              asyncio.create_task(_read_stream(p.stderr  ,    lambda __lowercase			: tee(__UpperCAmelCase  ,    __UpperCAmelCase  ,    sys.stderr  ,    label="stderr:"			)			)			),
          ]  ,    timeout=__UpperCAmelCase  ,    )
      return _RunOutput(await p.wait()  ,    __UpperCAmelCase  ,    __UpperCAmelCase			)

def    __lowercase		(     __lowercase  ,    __lowercase=None  ,    __lowercase=None  ,    __lowercase=180  ,    __lowercase=False  ,    __lowercase=True			)			->		_RunOutput:

      '''simple docstring'''


      _A     	=      asyncio.get_event_loop()
      _A     	=      loop.run_until_complete(
          _stream_subprocess(__UpperCAmelCase  ,    env=__UpperCAmelCase  ,    stdin=__UpperCAmelCase  ,    timeout=__UpperCAmelCase  ,    quiet=__UpperCAmelCase  ,    echo=__UpperCAmelCase			)			)

      _A     	=      ' '.join(__UpperCAmelCase			)
      if result.returncode > 0:
            _A     	=      '\n'.join(result.stderr			)
            raise RuntimeError(
                F'''\'{cmd_str}\' failed with returncode {result.returncode}\n\n'''
                F'''The combined stderr from workers follows:\n{stderr}'''			)

      return result

class   _UpperCAmelCase     (	snake_case_		):




   """simple docstring"""

   pass





def    __lowercase		(     __lowercase  ,    __lowercase=False			)			->		Union[str, Any]:

      '''simple docstring'''


      try:
            _A     	=      subprocess.check_output(__UpperCAmelCase  ,    stderr=subprocess.STDOUT			)
            if return_stdout:
                  if hasattr(__UpperCAmelCase  ,    "decode"			):
                        _A     	=      output.decode("utf-8"			)
                  return output
      except subprocess.CalledProcessError as e:
            raise SubprocessCallException(
                F'''Command `{' '.join(__UpperCAmelCase			)}` failed with the following error:\n\n{e.output.decode()}'''			) from e










'''simple docstring'''

from random import randint
from tempfile import TemporaryFile

import numpy as np







def a_     (    __UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase					)				->					int:





			"""simple docstring"""







			snake_case:    int      							=0
			if start < end:
						snake_case:    Tuple      							=randint(__UpperCAmelCase				,							__UpperCAmelCase					)
						snake_case:    Optional[Any]      							=a[end]
						snake_case:    List[Any]      							=a[pivot]
						snake_case:    int      							=temp

						snake_case							,  snake_case:    Optional[int]      							=_in_place_partition(__UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase					)
						count += _in_place_quick_sort(__UpperCAmelCase				,							__UpperCAmelCase				,							p - 1					)
						count += _in_place_quick_sort(__UpperCAmelCase				,							p + 1				,							__UpperCAmelCase					)
			return count







def a_     (    __UpperCAmelCase				,							__UpperCAmelCase				,							__UpperCAmelCase					)				->					Optional[int]:





			"""simple docstring"""







			snake_case:    Tuple      							=0
			snake_case:    Tuple      							=randint(__UpperCAmelCase				,							__UpperCAmelCase					)
			snake_case:    List[Any]      							=a[end]
			snake_case:    List[str]      							=a[pivot]
			snake_case:    Dict      							=temp
			snake_case:    Union[str, Any]      							=start - 1
			for index in range(__UpperCAmelCase				,							__UpperCAmelCase					):
						count += 1
						if a[index] < a[end]:  # check if current val is less than pivot value
									snake_case:    Optional[Any]      							=new_pivot_index + 1
									snake_case:    Dict      							=a[new_pivot_index]
									snake_case:    Union[str, Any]      							=a[index]
									snake_case:    List[Any]      							=temp

			snake_case:    Union[str, Any]      							=a[new_pivot_index + 1]
			snake_case:    Tuple      							=a[end]
			snake_case:    Union[str, Any]      							=temp
			return new_pivot_index + 1, count


a							   =				TemporaryFile()
a							   =				100  # 1000 elements are to be sorted


a   ,      a							   =				0, 1  # mean and standard deviation
a							   =				np.random.normal(mu, sigma, p)
np.save(outfile, X)
print('The array is')
print(X)


outfile.seek(0)  # using the same array
a							   =				np.load(outfile)
a							   =				len(M) - 1
a							   =				_in_place_quick_sort(M, 0, r)

print(
    'No of Comparisons for 100 elements selected from a standard normal distribution'
    'is :'
)







print(z)




