





"""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  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Any       ,			_lowercase		:       Optional[int]=False   )					->List[str]:






	'''simple docstring'''






	try:
		a :						Tuple      =							os.environ[key]
	except KeyError:
		# KEY isn't set, default to `default`.
		a :						Optional[Any]      =							default
	else:
		# KEY is set, convert it to True or False.
		try:
			a :						Dict      =							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


a		:					Any	      =     parse_flag_from_env('''RUN_SLOW''', default=False)






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Union[str, Any]   )					->str:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       List[Any]   )					->List[str]:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       str   )					->Optional[int]:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       List[str]   )					->Dict:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       int   )					->str:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Union[str, Any]   )					->Dict:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Optional[Any]   )					->str:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Dict   )					->Union[str, Any]:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Optional[int]   )					->Dict:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Dict   )					->Optional[Any]:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Optional[int]   )					->int:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Dict   )					->Optional[int]:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       List[Any]   )					->str:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Tuple   )					->Dict:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       List[Any]   )					->List[str]:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Optional[int]   )					->int:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       List[Any]=None       ,			_lowercase		:       int=None   )					->str:






	'''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  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Dict   )					->Any:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Tuple   )					->List[str]:






	'''simple docstring'''






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






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Tuple   )					->List[str]:






	'''simple docstring'''






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


a		:					List[Any]	      =     (
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       int   )					->Optional[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 			__UpperCamelCase							(		unittest.TestCase		):
							lowerCamelCase  :   Optional[Any]    =True






							@classmethod
							def        __a  (  cls )      ->					Tuple:
								a :						int      =							tempfile.mkdtemp()






							@classmethod
							def        __a  (  cls )      ->					Union[str, Any]:
								if os.path.exists(cls.tmpdir ):
									shutil.rmtree(cls.tmpdir )






							def        __a  (  self )      ->					Tuple:
								if self.clear_on_setup:
									for path in Path(self.tmpdir ).glob("**/*" ):
										if path.is_file():
											path.unlink()
										elif path.is_dir():
											shutil.rmtree(lowerCAmelCase__ )


class 			__UpperCamelCase							(		unittest.TestCase		):






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


class 			__UpperCamelCase							(		unittest.TestCase		):






							def        __a  (  self ,   lowerCAmelCase__ )      ->					List[str]:
								a :						Any      =							mocks if isinstance(lowerCAmelCase__ ,   (tuple, list) ) else [mocks]
								for m in self.mocks:
									m.start()
									self.addCleanup(m.stop )






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       int   )					->Dict:






	'''simple docstring'''






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


class 			__UpperCamelCase							:






							def __init__(  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ ,   lowerCAmelCase__ )      ->					List[str]:
								a :						List[str]      =							returncode
								a :						List[Any]      =							stdout
								a :						List[str]      =							stderr






async def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       List[Any]       ,			_lowercase		:       Any   )					->int:






	'''simple docstring'''






	while True:
		a :						Optional[Any]      =							await stream.readline()
		if line:
			callback(_lowercase   )
		else:
			break






async def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Optional[Any]       ,			_lowercase		:       List[Any]=None       ,			_lowercase		:       Optional[Any]=None       ,			_lowercase		:       Dict=None       ,			_lowercase		:       List[Any]=False       ,			_lowercase		:       List[str]=False   )					->_RunOutput:






	'''simple docstring'''






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

	a :						Optional[Any]      =							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)

	a :						str      =							[]
	a :						Optional[Any]      =							[]

	def tee(_lowercase		:       Dict       ,			_lowercase		:       str       ,			_lowercase		:       Union[str, Any]       ,			_lowercase		:       Optional[Any]=""   ):
		a :						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  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Union[str, Any]       ,			_lowercase		:       Optional[int]=None       ,			_lowercase		:       List[Any]=None       ,			_lowercase		:       Optional[int]=180       ,			_lowercase		:       Dict=False       ,			_lowercase		:       List[str]=True   )					->_RunOutput:






	'''simple docstring'''






	a :						List[Any]      =							asyncio.get_event_loop()
	a :						List[str]      =							loop.run_until_complete(
	    _stream_subprocess(_lowercase       ,			env=_lowercase       ,			stdin=_lowercase       ,			timeout=_lowercase       ,			quiet=_lowercase       ,			echo=_lowercase   )   )

	a :						Any      =							" ".join(_lowercase   )
	if result.returncode > 0:
		a :						Union[str, 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 			__UpperCamelCase							(		a__		):
							pass






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       List[str]       ,			_lowercase		:       Union[str, Any]=False   )					->List[Any]:






	'''simple docstring'''






	try:
		a :						Optional[Any]      =							subprocess.check_output(_lowercase       ,			stderr=subprocess.STDOUT   )
		if return_stdout:
			if hasattr(_lowercase       ,			"decode"   ):
				a :						Dict      =							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"""




import gc
import threading
import time

import psutil
import torch


class 			__UpperCamelCase							:






							def __init__(  self )      ->					Any:
								a :						str      =							psutil.Process()
								a :						str      =							False






							def        __a  (  self )      ->					str:
								a :						List[Any]      =							-1

								while True:
									a :						str      =							max(self.process.memory_info().rss ,   self.cpu_memory_peak )

									# can't sleep or will not catch the peak right (this comment is here on purpose)
									if not self.peak_monitoring:
										break






							def        __a  (  self )      ->					List[str]:
								a :						Dict      =							True
								a :						Optional[Any]      =							threading.Thread(target=self.peak_monitor )
								a :						List[Any]      =							True
								self.thread.start()






							def        __a  (  self )      ->					List[str]:
								a :						Optional[int]      =							False
								self.thread.join()
								return self.cpu_memory_peak
a		:					Tuple	      =     PeakCPUMemory()






def  _SCREAMING_SNAKE_CASE						(      )					->List[Any]:






	'''simple docstring'''






	a :						List[str]      =							{"time": time.time()}

	gc.collect()
	torch.cuda.empty_cache()

	# CPU mem
	a :						Tuple      =							psutil.Process().memory_info().rss
	cpu_peak_tracker.start()

	# GPU mem
	for i in range(torch.cuda.device_count()   ):
		a :						Any      =							torch.cuda.memory_allocated(_lowercase   )
	torch.cuda.reset_peak_memory_stats()

	return measures






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       List[str]   )					->Union[str, Any]:






	'''simple docstring'''






	a :						int      =							{"time": time.time() - start_measures["time"]}

	gc.collect()
	torch.cuda.empty_cache()

	# CPU mem
	a :						List[Any]      =							(psutil.Process().memory_info().rss - start_measures["cpu"]) / 2**20
	a :						Union[str, Any]      =							(cpu_peak_tracker.stop() - start_measures["cpu"]) / 2**20

	# GPU mem
	for i in range(torch.cuda.device_count()   ):
		a :						Optional[Any]      =							(torch.cuda.memory_allocated(_lowercase   ) - start_measures[str(_lowercase   )]) / 2**20
		a :						Optional[Any]      =							(torch.cuda.max_memory_allocated(_lowercase   ) - start_measures[str(_lowercase   )]) / 2**20

	return measures







def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       str       ,			_lowercase		:       Union[str, Any]   )					->Optional[int]:






	'''simple docstring'''






	print(F"""{description}:"""   )
	print(F"""- Time: {measures['time']:.2f}s"""   )
	for i in range(torch.cuda.device_count()   ):
		print(F"""- GPU {i} allocated: {measures[str(_lowercase   )]:.2f}MiB"""   )
		a :						str      =							measures[F"""{i}-peak"""]
		print(F"""- GPU {i} peak: {peak:.2f}MiB"""   )
	print(F"""- CPU RAM allocated: {measures['cpu']:.2f}MiB"""   )
	print(F"""- CPU RAM peak: {measures['cpu-peak']:.2f}MiB"""   )


