





'''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						(							a_						:  str      ,a_						:  Optional[Any]=False	):
		try:
				lowerCAmelCase     :    Tuple						=   os.environ[key]
		except KeyError:
				# KEY isn't set, default to `default`.
				lowerCAmelCase     :    Dict						=   default
		else:
				# KEY is set, convert it to True or False.
				try:
						lowerCAmelCase     :    Optional[int]						=   strtobool(a_	)
				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      __A						(							a_						:  int	):
		return unittest.skip("Test was skipped"	)(a_	)






def      __A						(							a_						:  List[str]	):
		return unittest.skipUnless(_run_slow_tests      ,"test is slow"	)(a_	)






def      __A						(							a_						:  Tuple	):
		return unittest.skipUnless(not torch.cuda.is_available()      ,"test requires only a CPU"	)(a_	)






def      __A						(							a_						:  List[str]	):
		return unittest.skipUnless(torch.cuda.is_available()      ,"test requires a GPU"	)(a_	)






def      __A						(							a_						:  Union[str, Any]	):
		return unittest.skipUnless(is_xpu_available()      ,"test requires a XPU"	)(a_	)






def      __A						(							a_						:  Dict	):
		return unittest.skipUnless(is_mps_available()      ,"test requires a `mps` backend support in `torch`"	)(a_	)






def      __A						(							a_						:  Any	):
		return unittest.skipUnless(
		    is_transformers_available() and is_datasets_available()      ,"test requires the Hugging Face suite"	)(a_	)






def      __A						(							a_						:  List[Any]	):
		return unittest.skipUnless(is_bnb_available()      ,"test requires the bitsandbytes library"	)(a_	)






def      __A						(							a_						:  Tuple	):
		return unittest.skipUnless(is_tpu_available()      ,"test requires TPU"	)(a_	)






def      __A						(							a_						:  Dict	):
		return unittest.skipUnless(torch.cuda.device_count() == 1      ,"test requires a GPU"	)(a_	)






def      __A						(							a_						:  Tuple	):
		return unittest.skipUnless(torch.xpu.device_count() == 1      ,"test requires a XPU"	)(a_	)






def      __A						(							a_						:  Optional[int]	):
		return unittest.skipUnless(torch.cuda.device_count() > 1      ,"test requires multiple GPUs"	)(a_	)






def      __A						(							a_						:  str	):
		return unittest.skipUnless(torch.xpu.device_count() > 1      ,"test requires multiple XPUs"	)(a_	)






def      __A						(							a_						:  Any	):
		return unittest.skipUnless(is_safetensors_available()      ,"test requires safetensors"	)(a_	)






def      __A						(							a_						:  List[str]	):
		return unittest.skipUnless(is_deepspeed_available()      ,"test requires DeepSpeed"	)(a_	)






def      __A						(							a_						:  Optional[int]	):
		return unittest.skipUnless(is_torch_version(">="      ,"1.12.0"	)      ,"test requires torch version >= 1.12.0"	)(a_	)






def      __A						(							a_						:  int=None      ,a_						:  Dict=None	):
		if test_case is None:
				return partial(a_      ,version=a_	)
		return unittest.skipUnless(is_torch_version(">="      ,a_	)      ,f'''test requires torch version >= {version}'''	)(a_	)






def      __A						(							a_						:  Optional[int]	):
		return unittest.skipUnless(is_tensorboard_available()      ,"test requires Tensorboard"	)(a_	)






def      __A						(							a_						:  Optional[int]	):
		return unittest.skipUnless(is_wandb_available()      ,"test requires wandb"	)(a_	)






def      __A						(							a_						:  Optional[int]	):
		return unittest.skipUnless(is_comet_ml_available()      ,"test requires comet_ml"	)(a_	)


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






def      __A						(							a_						:  Optional[Any]	):
		return unittest.skipUnless(
		    _atleast_one_tracker_available      ,"test requires at least one tracker to be available and for `comet_ml` to not be installed"      ,)(a_	)
class 		lowerCamelCase  (      unittest.TestCase       ):
	snake_case_      =   True



	@classmethod
	def   _lowerCamelCase    (   cls	):
			lowerCAmelCase     :    Tuple						=   tempfile.mkdtemp()



	@classmethod
	def   _lowerCamelCase    (   cls	):
			if os.path.exists(cls.tmpdir	):
					shutil.rmtree(cls.tmpdir	)





	def   _lowerCamelCase    (   self	):
			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 		lowerCamelCase  (      unittest.TestCase       ):



	def   _lowerCamelCase    (   self	):
			super().tearDown()
			# Reset the state of the AcceleratorState singleton.
			AcceleratorState._reset_state()
			PartialState._reset_state()






class 		lowerCamelCase  (      unittest.TestCase       ):



	def   _lowerCamelCase    (   self		,      a_	):
			lowerCAmelCase     :    List[str]						=   mocks if isinstance(a_		,      (tuple, list)	) else [mocks]
			for m in self.mocks:
					m.start()
					self.addCleanup(m.stop	)






def      __A						(							a_						:  int	):
		lowerCAmelCase     :    Optional[Any]						=   AcceleratorState()
		lowerCAmelCase     :    List[str]						=   tensor[None].clone().to(state.device	)
		lowerCAmelCase     :    Optional[Any]						=   gather(a_	).cpu()
		lowerCAmelCase     :    List[Any]						=   tensor[0].cpu()
		for i in range(tensors.shape[0]	):
				if not torch.equal(tensors[i]      ,a_	):
						return False
		return True
class 		lowerCamelCase  :



	def __init__(   self		,      a_		,      a_		,      a_	):
			lowerCAmelCase     :    List[Any]						=   returncode
			lowerCAmelCase     :    int						=   stdout
			lowerCAmelCase     :    Any						=   stderr






async def      __A						(							a_						:  Union[str, Any]      ,a_						:  Union[str, Any]	):
		while True:
				lowerCAmelCase     :    Tuple						=   await stream.readline()
				if line:
						callback(a_	)
				else:
						break






async def      __A						(							a_						:  List[Any]      ,a_						:  Dict=None      ,a_						:  Optional[int]=None      ,a_						:  Optional[Any]=None      ,a_						:  str=False      ,a_						:  List[Any]=False	):
		if echo:
				print("\nRunning: "      ," ".join(a_	)	)

		lowerCAmelCase     :    Union[str, Any]						=   await asyncio.create_subprocess_exec(
		    cmd[0]      ,*cmd[1:]      ,stdin=a_      ,stdout=asyncio.subprocess.PIPE      ,stderr=asyncio.subprocess.PIPE      ,env=a_      ,)

		# 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)

		lowerCAmelCase     :    Tuple						=   []
		lowerCAmelCase     :    Union[str, Any]						=   []

		def tee(a_						:  Any      ,a_						:  List[str]      ,a_						:  Tuple      ,a_						:  Tuple=""	):
				lowerCAmelCase     :    Any						=   line.decode("utf-8"	).rstrip()
				sink.append(a_	)
				if not quiet:
						print(a_      ,a_      ,file=a_	)

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






def      __A						(							a_						:  List[str]      ,a_						:  Dict=None      ,a_						:  Tuple=None      ,a_						:  Union[str, Any]=1_8_0      ,a_						:  Optional[int]=False      ,a_						:  Union[str, Any]=True	):
		lowerCAmelCase     :    Optional[int]						=   asyncio.get_event_loop()
		lowerCAmelCase     :    int						=   loop.run_until_complete(
		    _stream_subprocess(a_      ,env=a_      ,stdin=a_      ,timeout=a_      ,quiet=a_      ,echo=a_	)	)

		lowerCAmelCase     :    int						=   " ".join(a_	)
		if result.returncode > 0:
				lowerCAmelCase     :    List[Any]						=   "\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 		lowerCamelCase  (      _A       ):
	pass






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










'''simple docstring'''






from collections import namedtuple

lowerCAmelCase       		=      namedtuple("""from_to""", """from_ to""")

lowerCAmelCase       		=      {
    """cubicmeter""": from_to(1, 1),
    """litre""": from_to(0.001, 10_00),
    """kilolitre""": from_to(1, 1),
    """gallon""": from_to(0.00454, 264.172),
    """cubicyard""": from_to(0.76455, 1.30795),
    """cubicfoot""": from_to(0.028, 35.3147),
    """cup""": from_to(0.000236588, 4226.75),
}






def      __A						(							a_						:  float      ,a_						:  str      ,a_						:  str	):
		if from_type not in METRIC_CONVERSION:
				raise ValueError(
				    f'''Invalid \'from_type\' value: {from_type!r}  Supported values are:\n'''
				    + ", ".join(a_	)	)
		if to_type not in METRIC_CONVERSION:
				raise ValueError(
				    f'''Invalid \'to_type\' value: {to_type!r}.  Supported values are:\n'''
				    + ", ".join(a_	)	)
		return value * METRIC_CONVERSION[from_type].from_ * METRIC_CONVERSION[to_type].to


if __name__ == "__main__":
					import doctest

					doctest.testmod()



