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


_snake_case				:   List[str]     =				parse_flag_from_env("""RUN_SLOW""", default=False)



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[Any]  ):
						return unittest.skip("Test was skipped"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str  ):
						return unittest.skipUnless(_run_slow_tests	,			"test is slow"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[str]  ):
						return unittest.skipUnless(not torch.cuda.is_available()	,			"test requires only a CPU"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Dict  ):
						return unittest.skipUnless(torch.cuda.is_available()	,			"test requires a GPU"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[str]  ):
						return unittest.skipUnless(is_xpu_available()	,			"test requires a XPU"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[str]  ):
						return unittest.skipUnless(is_mps_available()	,			"test requires a `mps` backend support in `torch`"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Optional[Any]  ):
						return unittest.skipUnless(
						    is_transformers_available() and is_datasets_available()	,			"test requires the Hugging Face suite"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Optional[Any]  ):
						return unittest.skipUnless(is_bnb_available()	,			"test requires the bitsandbytes library"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str  ):
						return unittest.skipUnless(is_tpu_available()	,			"test requires TPU"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Union[str, Any]  ):
						return unittest.skipUnless(torch.cuda.device_count() == 1	,			"test requires a GPU"  )(_SCREAMING_SNAKE_CASE  )



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



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



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[str]  ):
						return unittest.skipUnless(torch.xpu.device_count() > 1	,			"test requires multiple XPUs"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[Any]  ):
						return unittest.skipUnless(is_safetensors_available()	,			"test requires safetensors"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Tuple  ):
						return unittest.skipUnless(is_deepspeed_available()	,			"test requires DeepSpeed"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Optional[Any]  ):
						return unittest.skipUnless(is_torch_version(">="	,			"1.12.0"  )	,			"test requires torch version >= 1.12.0"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[str]=None	,			_SCREAMING_SNAKE_CASE		:   Any=None  ):
						if test_case is None:
												return partial(_SCREAMING_SNAKE_CASE	,			version=_SCREAMING_SNAKE_CASE  )
						return unittest.skipUnless(is_torch_version(">="	,			_SCREAMING_SNAKE_CASE  )	,			F'test requires torch version >= {version}'  )(_SCREAMING_SNAKE_CASE  )



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



def 			_a		(	_SCREAMING_SNAKE_CASE		:   List[Any]  ):
						return unittest.skipUnless(is_wandb_available()	,			"test requires wandb"  )(_SCREAMING_SNAKE_CASE  )



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Dict  ):
						return unittest.skipUnless(is_comet_ml_available()	,			"test requires comet_ml"  )(_SCREAMING_SNAKE_CASE  )


_snake_case				:   Optional[int]     =				(
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)



def 			_a		(	_SCREAMING_SNAKE_CASE		:   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"	,			)(_SCREAMING_SNAKE_CASE  )


class 			lowerCAmelCase (				unittest.TestCase			):
		a							:					List[Any]       =					True




		@classmethod
		def     lowercase       (				cls      ):
								_SCREAMING_SNAKE_CASE				= tempfile.mkdtemp()




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




		def     lowercase       (				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(UpperCamelCase      )


class 			lowerCAmelCase (				unittest.TestCase			):




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


class 			lowerCAmelCase (				unittest.TestCase			):




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= mocks if isinstance(UpperCamelCase					,						(tuple, list)      ) else [mocks]
								for m in self.mocks:
														m.start()
														self.addCleanup(m.stop      )



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


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= returncode
								_SCREAMING_SNAKE_CASE				= stdout
								_SCREAMING_SNAKE_CASE				= stderr



async def 			_a		(	_SCREAMING_SNAKE_CASE		:   Optional[int]	,			_SCREAMING_SNAKE_CASE		:   int  ):
						while True:
												_SCREAMING_SNAKE_CASE				= await stream.readline()
												if line:
																		callback(_SCREAMING_SNAKE_CASE  )
												else:
																		break



async def 			_a		(	_SCREAMING_SNAKE_CASE		:   Union[str, Any]	,			_SCREAMING_SNAKE_CASE		:   Dict=None	,			_SCREAMING_SNAKE_CASE		:   List[str]=None	,			_SCREAMING_SNAKE_CASE		:   Any=None	,			_SCREAMING_SNAKE_CASE		:   List[str]=False	,			_SCREAMING_SNAKE_CASE		:   Tuple=False  ):
						if echo:
												print("\nRunning: "	,			" ".join(_SCREAMING_SNAKE_CASE  )  )

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

						# 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)

						_SCREAMING_SNAKE_CASE				= []
						_SCREAMING_SNAKE_CASE				= []

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

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



def 			_a		(	_SCREAMING_SNAKE_CASE		:   Optional[Any]	,			_SCREAMING_SNAKE_CASE		:   Dict=None	,			_SCREAMING_SNAKE_CASE		:   Dict=None	,			_SCREAMING_SNAKE_CASE		:   List[Any]=180	,			_SCREAMING_SNAKE_CASE		:   Union[str, Any]=False	,			_SCREAMING_SNAKE_CASE		:   Dict=True  ):
						_SCREAMING_SNAKE_CASE				= asyncio.get_event_loop()
						_SCREAMING_SNAKE_CASE				= loop.run_until_complete(
						    _stream_subprocess(_SCREAMING_SNAKE_CASE	,			env=_SCREAMING_SNAKE_CASE	,			stdin=_SCREAMING_SNAKE_CASE	,			timeout=_SCREAMING_SNAKE_CASE	,			quiet=_SCREAMING_SNAKE_CASE	,			echo=_SCREAMING_SNAKE_CASE  )  )

						_SCREAMING_SNAKE_CASE				= " ".join(_SCREAMING_SNAKE_CASE  )
						if result.returncode > 0:
												_SCREAMING_SNAKE_CASE				= "\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 (				__UpperCAmelCase			):
		pass



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

'''simple docstring'''







import baseaa
import io
import json
import os
from copy import deepcopy

from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase      ):
								if isinstance(UpperCamelCase					,						UpperCamelCase      ):
														# Don't modify user's data should they want to reuse it (e.g. in tests), because once we
														# modified it, it will not be accepted here again, since `auto` values would have been overridden
														_SCREAMING_SNAKE_CASE				= deepcopy(UpperCamelCase      )
								elif os.path.exists(UpperCamelCase      ):
														with io.open(UpperCamelCase					,						"r"					,						encoding="utf-8"      ) as f:
																				_SCREAMING_SNAKE_CASE				= json.load(UpperCamelCase      )
								else:
														try:
																				_SCREAMING_SNAKE_CASE				= baseaa.urlsafe_baadecode(UpperCamelCase      ).decode("utf-8"      )
																				_SCREAMING_SNAKE_CASE				= json.loads(UpperCamelCase      )
														except (UnicodeDecodeError, AttributeError, ValueError):
																				raise ValueError(
																				    F'Expected a string path to an existing deepspeed config, or a dictionary, or a base64 encoded string. Received: {config_file_or_dict}'      )

								_SCREAMING_SNAKE_CASE				= config

								self.set_stage_and_offload()




		def     lowercase       (				self      ):
								# zero stage - this is done as early as possible, before model is created, to allow
								# ``is_deepspeed_zero3_enabled`` query and getting to the early deepspeed config object
								# during ``zero.Init()`` which needs to know the dtype, and some other hparams.
								_SCREAMING_SNAKE_CASE				= self.get_value("zero_optimization.stage"					,						-1      )

								# offload
								_SCREAMING_SNAKE_CASE				= False
								if self.is_zeroa() or self.is_zeroa():
														_SCREAMING_SNAKE_CASE				= set(["cpu", "nvme"]      )
														_SCREAMING_SNAKE_CASE				= set(
														    [
														        self.get_value("zero_optimization.offload_optimizer.device"      ),
														        self.get_value("zero_optimization.offload_param.device"      ),
														    ]      )
														if len(offload_devices & offload_devices_valid      ) > 0:
																				_SCREAMING_SNAKE_CASE				= True




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.config

								# find the config node of interest if it exists
								_SCREAMING_SNAKE_CASE				= ds_key_long.split("."      )
								_SCREAMING_SNAKE_CASE				= nodes.pop()
								for node in nodes:
														_SCREAMING_SNAKE_CASE				= config.get(UpperCamelCase      )
														if config is None:
																				return None, ds_key

								return config, ds_key




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase=None      ):
								_SCREAMING_SNAKE_CASE,							_SCREAMING_SNAKE_CASE				= self.find_config_node(UpperCamelCase      )
								if config is None:
														return default
								return config.get(UpperCamelCase					,						UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase=False      ):
								_SCREAMING_SNAKE_CASE				= self.config

								# find the config node of interest if it exists
								_SCREAMING_SNAKE_CASE				= ds_key_long.split("."      )
								for node in nodes:
														_SCREAMING_SNAKE_CASE				= config
														_SCREAMING_SNAKE_CASE				= config.get(UpperCamelCase      )
														if config is None:
																				if must_exist:
																										raise ValueError(F'Can\'t find {ds_key_long} entry in the config: {self.config}'      )
																				else:
																										return

        # if found remove it
								if parent_config is not None:
														parent_config.pop(UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.get_value(UpperCamelCase      )
								return False if value is None else bool(UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= self.get_value(UpperCamelCase      )
								return False if value is None else not bool(UpperCamelCase      )




		def     lowercase       (				self      ):
								return self._stage == 2




		def     lowercase       (				self      ):
								return self._stage == 3




		def     lowercase       (				self      ):
								return self._offload


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= engine




		def     lowercase       (				self					,						UpperCamelCase					,						**UpperCamelCase      ):
								# runs backpropagation and handles mixed precision
								self.engine.backward(UpperCamelCase					,						**UpperCamelCase      )

								# Deepspeed's `engine.step` performs the following operations:
								# - gradient accumulation check
								# - gradient clipping
								# - optimizer step
								# - zero grad
								# - checking overflow
								# - lr_scheduler step (only if engine.lr_scheduler is not None)
								self.engine.step()
								# and this plugin overrides the above calls with no-ops when Accelerate runs under
								# Deepspeed, but allows normal functionality for non-Deepspeed cases thus enabling a simple
								# training loop that works transparently under many training regimes.


class 			lowerCAmelCase (				__UpperCAmelCase			):




		def __init__(				self					,						UpperCamelCase      ):
								super().__init__(UpperCamelCase					,						device_placement=UpperCamelCase					,						scaler=UpperCamelCase      )
								_SCREAMING_SNAKE_CASE				= hasattr(self.optimizer					,						"overflow"      )




		def     lowercase       (				self					,						UpperCamelCase=None      ):
								pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed




		def     lowercase       (				self      ):
								pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed




		@property
		def     lowercase       (				self      ):
								if self.__has_overflow__:
														return self.optimizer.overflow
								return False


class 			lowerCAmelCase (				__UpperCAmelCase			):




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase      ):
								super().__init__(UpperCamelCase					,						UpperCamelCase      )




		def     lowercase       (				self      ):
								pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase=0.0_01					,						UpperCamelCase=0					,						**UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= params
								_SCREAMING_SNAKE_CASE				= lr
								_SCREAMING_SNAKE_CASE				= weight_decay
								_SCREAMING_SNAKE_CASE				= kwargs


class 			lowerCAmelCase :




		def __init__(				self					,						UpperCamelCase					,						UpperCamelCase=None					,						UpperCamelCase=0					,						**UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= optimizer
								_SCREAMING_SNAKE_CASE				= total_num_steps
								_SCREAMING_SNAKE_CASE				= warmup_num_steps
								_SCREAMING_SNAKE_CASE				= kwargs