


'''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 			_a			(		_lowercase      :			Tuple    ,      _lowercase      :			Optional[Any]=False						):





     '''simple docstring'''






     try:
          __UpperCAmelCase			:				Optional[Any]													=    os.environ[key]
     except KeyError:
          # KEY isn't set, default to `default`.
          __UpperCAmelCase			:				Optional[int]													=    default
     else:
          # KEY is set, convert it to True or False.
          try:
               __UpperCAmelCase			:				Union[str, Any]													=    strtobool(_lowercase						)
          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


__UpperCAmelCase    :Dict				       =     parse_flag_from_env("RUN_SLOW", default=False)




def 			_a			(		_lowercase      :			Optional[Any]						):





     '''simple docstring'''






     return unittest.skip('''Test was skipped'''						)(_lowercase						)




def 			_a			(		_lowercase      :			Optional[Any]						):





     '''simple docstring'''






     return unittest.skipUnless(_run_slow_tests    ,      '''test is slow'''						)(_lowercase						)




def 			_a			(		_lowercase      :			Dict						):





     '''simple docstring'''






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




def 			_a			(		_lowercase      :			List[str]						):





     '''simple docstring'''






     return unittest.skipUnless(torch.cuda.is_available()    ,      '''test requires a GPU'''						)(_lowercase						)




def 			_a			(		_lowercase      :			List[Any]						):





     '''simple docstring'''






     return unittest.skipUnless(is_xpu_available()    ,      '''test requires a XPU'''						)(_lowercase						)




def 			_a			(		_lowercase      :			Union[str, Any]						):





     '''simple docstring'''






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




def 			_a			(		_lowercase      :			Union[str, Any]						):





     '''simple docstring'''






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




def 			_a			(		_lowercase      :			Union[str, Any]						):





     '''simple docstring'''






     return unittest.skipUnless(is_bnb_available()    ,      '''test requires the bitsandbytes library'''						)(_lowercase						)




def 			_a			(		_lowercase      :			List[str]						):





     '''simple docstring'''






     return unittest.skipUnless(is_tpu_available()    ,      '''test requires TPU'''						)(_lowercase						)




def 			_a			(		_lowercase      :			Union[str, Any]						):





     '''simple docstring'''






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




def 			_a			(		_lowercase      :			Optional[Any]						):





     '''simple docstring'''






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




def 			_a			(		_lowercase      :			List[Any]						):





     '''simple docstring'''






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




def 			_a			(		_lowercase      :			List[Any]						):





     '''simple docstring'''






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




def 			_a			(		_lowercase      :			Dict						):





     '''simple docstring'''






     return unittest.skipUnless(is_safetensors_available()    ,      '''test requires safetensors'''						)(_lowercase						)




def 			_a			(		_lowercase      :			Tuple						):





     '''simple docstring'''






     return unittest.skipUnless(is_deepspeed_available()    ,      '''test requires DeepSpeed'''						)(_lowercase						)




def 			_a			(		_lowercase      :			Dict						):





     '''simple docstring'''






     return unittest.skipUnless(is_torch_version('''>='''    ,      '''1.12.0'''						)    ,      '''test requires torch version >= 1.12.0'''						)(_lowercase						)




def 			_a			(		_lowercase      :			Any=None    ,      _lowercase      :			Tuple=None						):





     '''simple docstring'''






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




def 			_a			(		_lowercase      :			Tuple						):





     '''simple docstring'''






     return unittest.skipUnless(is_tensorboard_available()    ,      '''test requires Tensorboard'''						)(_lowercase						)




def 			_a			(		_lowercase      :			Optional[Any]						):





     '''simple docstring'''






     return unittest.skipUnless(is_wandb_available()    ,      '''test requires wandb'''						)(_lowercase						)




def 			_a			(		_lowercase      :			int						):





     '''simple docstring'''






     return unittest.skipUnless(is_comet_ml_available()    ,      '''test requires comet_ml'''						)(_lowercase						)


__UpperCAmelCase    :str				       =     (
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)




def 			_a			(		_lowercase      :			List[Any]						):





     '''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'''    ,      )(_lowercase						)



class 			a       (	unittest.TestCase ):


     """simple docstring"""






     SCREAMING_SNAKE_CASE :				Any							     =     True

     @classmethod
     def 				lowerCamelCase__				(       cls  :	Optional[Any]    )		->							List[str]:
          __UpperCAmelCase			:				List[str]													=    tempfile.mkdtemp()

     @classmethod
     def 				lowerCamelCase__				(       cls  :	List[str]    )		->							Tuple:
          if os.path.exists(cls.tmpdir    ):
               shutil.rmtree(cls.tmpdir    )






     def 				lowerCamelCase__				(       self  :	List[Any]    )		->							Optional[Any]:
          if self.clear_on_setup:
               for path in Path(self.tmpdir    ).glob('''**/*'''    ):
                    if path.is_file():
                         path.unlink()
                    elif path.is_dir():
                         shutil.rmtree(snake_case    )



class 			a       (	unittest.TestCase ):


     """simple docstring"""






     def 				lowerCamelCase__				(       self  :	str    )		->							str:
          super().tearDown()
          # Reset the state of the AcceleratorState singleton.
          AcceleratorState._reset_state()
          PartialState._reset_state()



class 			a       (	unittest.TestCase ):


     """simple docstring"""






     def 				lowerCamelCase__				(       self  :	List[Any]							,				snake_case  :	Union[mock.Mock, List[mock.Mock]]    )		->							Union[str, Any]:
          __UpperCAmelCase			:				List[Any]													=    mocks if isinstance(snake_case							,				(tuple, list)    ) else [mocks]
          for m in self.mocks:
               m.start()
               self.addCleanup(m.stop    )




def 			_a			(		_lowercase      :			List[str]						):





     '''simple docstring'''






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



class 			a       :


     """simple docstring"""






     def __init__(       self  :	Dict							,				snake_case  :	Dict							,				snake_case  :	Optional[Any]							,				snake_case  :	str    )		->							Union[str, Any]:
          __UpperCAmelCase			:				Union[str, Any]													=    returncode
          __UpperCAmelCase			:				Optional[Any]													=    stdout
          __UpperCAmelCase			:				List[Any]													=    stderr




async def 			_a			(		_lowercase      :			str    ,      _lowercase      :			Optional[int]						):





     '''simple docstring'''






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




async def 			_a			(		_lowercase      :			Union[str, Any]    ,      _lowercase      :			Union[str, Any]=None    ,      _lowercase      :			Dict=None    ,      _lowercase      :			Optional[int]=None    ,      _lowercase      :			List[str]=False    ,      _lowercase      :			Optional[int]=False						):





     '''simple docstring'''






     if echo:
          print('''\nRunning: '''    ,      ''' '''.join(_lowercase						)						)

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

     # 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)

     __UpperCAmelCase			:				Optional[int]													=    []
     __UpperCAmelCase			:				str													=    []

     def tee(_lowercase      :			Dict    ,      _lowercase      :			Dict    ,      _lowercase      :			List[Any]    ,      _lowercase      :			Union[str, Any]=""						):
          __UpperCAmelCase			:				Optional[int]													=    line.decode('''utf-8'''						).rstrip()
          sink.append(_lowercase						)
          if not quiet:
               print(_lowercase    ,      _lowercase    ,      file=_lowercase						)

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




def 			_a			(		_lowercase      :			Union[str, Any]    ,      _lowercase      :			Optional[int]=None    ,      _lowercase      :			str=None    ,      _lowercase      :			Optional[int]=180    ,      _lowercase      :			Dict=False    ,      _lowercase      :			Optional[Any]=True						):





     '''simple docstring'''






     __UpperCAmelCase			:				Union[str, Any]													=    asyncio.get_event_loop()
     __UpperCAmelCase			:				Optional[int]													=    loop.run_until_complete(
         _stream_subprocess(_lowercase    ,      env=_lowercase    ,      stdin=_lowercase    ,      timeout=_lowercase    ,      quiet=_lowercase    ,      echo=_lowercase						)						)

     __UpperCAmelCase			:				Dict													=    ''' '''.join(_lowercase						)
     if result.returncode > 0:
          __UpperCAmelCase			:				Dict													=    '''\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 			a       (	_a ):


     """simple docstring"""






     pass




def 			_a			(		_lowercase      :			List[str]    ,      _lowercase      :			Tuple=False						):





     '''simple docstring'''






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



'''simple docstring'''



def 			_a			(		_lowercase      :			int = 50000000						):





     '''simple docstring'''






     __UpperCAmelCase			:				List[str]													=    set()
     __UpperCAmelCase			:				Tuple													=    int((limit - 24) ** (1 / 2)						)

     __UpperCAmelCase			:				Tuple													=    set(range(3    ,      prime_square_limit + 1    ,      2						)						)
     primes.add(2						)
     for p in range(3    ,      prime_square_limit + 1    ,      2						):
          if p not in primes:
               continue
          primes.difference_update(set(range(p * p    ,      prime_square_limit + 1    ,      _lowercase						)						)						)

     for primea in primes:
          __UpperCAmelCase			:				Any													=    primea * primea
          for primea in primes:
               __UpperCAmelCase			:				Any													=    primea * primea * primea
               if square + cube >= limit - 16:
                    break
               for primea in primes:
                    __UpperCAmelCase			:				Optional[Any]													=    primea * primea * primea * primea
                    __UpperCAmelCase			:				Union[str, Any]													=    square + cube + tetr
                    if total >= limit:
                         break
                    ret.add(_lowercase						)

     return len(_lowercase						)


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