
import json
import logging
import os
import socket

import git
import numpy as np
import torch


logging.basicConfig(
    format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d -  %(message)s",
    datefmt="%m/%d/%Y %H:%M:%S",
    level=logging.INFO,
)
lowercase__	:Dict										=					logging.getLogger(__name__)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		git.Repo(search_parent_directories=lowerCAmelCase__	)
					lowercase					=		{
					    '''repo_id''': str(lowerCAmelCase__	),
					    '''repo_sha''': str(repo.head.object.hexsha	),
					    '''repo_branch''': str(repo.active_branch	),
					}

					with open(os.path.join(lowerCAmelCase__				,    '''git_log.json'''	)				,    '''w'''	) as f:
										json.dump(lowerCAmelCase__				,    lowerCAmelCase__				,    indent=4	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					if params.n_gpu <= 0:
										lowercase					=		0
										lowercase					=		-1
										lowercase					=		True
										lowercase					=		False
										return

					assert torch.cuda.is_available()

					logger.info('''Initializing GPUs'''	)
					if params.n_gpu > 1:
										assert params.local_rank != -1

										lowercase					=		int(os.environ['''WORLD_SIZE''']	)
										lowercase					=		int(os.environ['''N_GPU_NODE''']	)
										lowercase					=		int(os.environ['''RANK''']	)

										# number of nodes / node ID
										lowercase					=		params.world_size // params.n_gpu_per_node
										lowercase					=		params.global_rank // params.n_gpu_per_node
										lowercase					=		True

										assert params.n_nodes == int(os.environ['''N_NODES''']	)
										assert params.node_id == int(os.environ['''NODE_RANK''']	)

					# local job (single GPU)
					else:
										assert params.local_rank == -1

										lowercase					=		1
										lowercase					=		0
										lowercase					=		0
										lowercase					=		0
										lowercase					=		1
										lowercase					=		1
										lowercase					=		False

					# sanity checks
					assert params.n_nodes >= 1
					assert 0 <= params.node_id < params.n_nodes
					assert 0 <= params.local_rank <= params.global_rank < params.world_size
					assert params.world_size == params.n_nodes * params.n_gpu_per_node

					# define whether this is the master process / if we are in multi-node distributed mode
					lowercase					=		params.node_id == 0 and params.local_rank == 0
					lowercase					=		params.n_nodes > 1

					# summary
					lowercase					=		f'--- Global rank: {params.global_rank} - '
					logger.info(PREFIX + '''Number of nodes: %i''' % params.n_nodes	)
					logger.info(PREFIX + '''Node ID        : %i''' % params.node_id	)
					logger.info(PREFIX + '''Local rank     : %i''' % params.local_rank	)
					logger.info(PREFIX + '''World size     : %i''' % params.world_size	)
					logger.info(PREFIX + '''GPUs per node  : %i''' % params.n_gpu_per_node	)
					logger.info(PREFIX + '''Master         : %s''' % str(params.is_master	)	)
					logger.info(PREFIX + '''Multi-node     : %s''' % str(params.multi_node	)	)
					logger.info(PREFIX + '''Multi-GPU      : %s''' % str(params.multi_gpu	)	)
					logger.info(PREFIX + '''Hostname       : %s''' % socket.gethostname()	)

					# set GPU device
					torch.cuda.set_device(params.local_rank	)

					# initialize multi-GPU
					if params.multi_gpu:
										logger.info('''Initializing PyTorch distributed'''	)
										torch.distributed.init_process_group(
										    init_method='''env://'''				,    backend='''nccl'''				,    )



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					np.random.seed(args.seed	)
					torch.manual_seed(args.seed	)
					if args.n_gpu > 0:
										torch.cuda.manual_seed_all(args.seed	)






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  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=False	):
					'''simple docstring'''
					try:
										lowercase					=		os.environ[key]
					except KeyError:
										# KEY isn't set, default to `default`.
										lowercase					=		default
					else:
										# KEY is set, convert it to True or False.
										try:
															lowercase					=		strtobool(lowerCAmelCase__	)
										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


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



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skip('''Test was skipped'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(_run_slow_tests				,    '''test is slow'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(not torch.cuda.is_available()				,    '''test requires only a CPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.cuda.is_available()				,    '''test requires a GPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_xpu_available()				,    '''test requires a XPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_mps_available()				,    '''test requires a `mps` backend support in `torch`'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(
					    is_transformers_available() and is_datasets_available()				,    '''test requires the Hugging Face suite'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_bnb_available()				,    '''test requires the bitsandbytes library'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_tpu_available()				,    '''test requires TPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.cuda.device_count() == 1				,    '''test requires a GPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.xpu.device_count() == 1				,    '''test requires a XPU'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.cuda.device_count() > 1				,    '''test requires multiple GPUs'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(torch.xpu.device_count() > 1				,    '''test requires multiple XPUs'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_safetensors_available()				,    '''test requires safetensors'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_deepspeed_available()				,    '''test requires DeepSpeed'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_torch_version('''>='''				,    '''1.12.0'''	)				,    '''test requires torch version >= 1.12.0'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__=None				,    lowerCAmelCase__=None	):
					'''simple docstring'''
					if test_case is None:
										return partial(lowerCAmelCase__				,    version=lowerCAmelCase__	)
					return unittest.skipUnless(is_torch_version('''>='''				,    lowerCAmelCase__	)				,    f'test requires torch version >= {version}'	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_tensorboard_available()				,    '''test requires Tensorboard'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_wandb_available()				,    '''test requires wandb'''	)(lowerCAmelCase__	)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					return unittest.skipUnless(is_comet_ml_available()				,    '''test requires comet_ml'''	)(lowerCAmelCase__	)


lowercase__	:Dict										=					(
    any([is_wandb_available(), is_tensorboard_available()]) and not is_comet_ml_available()
)



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''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'''				,    )(lowerCAmelCase__	)







class        lowercase	(      unittest.TestCase	):
							lowercase_ : int       =True




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




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





							def 				A__   (       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        lowercase	(      unittest.TestCase	):




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







class        lowercase	(      unittest.TestCase	):




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



def  UpperCamelCase					(							lowerCAmelCase__	):
					'''simple docstring'''
					lowercase					=		AcceleratorState()
					lowercase					=		tensor[None].clone().to(state.device	)
					lowercase					=		gather(lowerCAmelCase__	).cpu()
					lowercase					=		tensor[0].cpu()
					for i in range(tensors.shape[0]	):
										if not torch.equal(tensors[i]				,    lowerCAmelCase__	):
															return False
					return True







class        lowercase	:




							def __init__(       self     ,A__     ,A__     ,A__):
												lowercase					=		returncode
												lowercase					=		stdout
												lowercase					=		stderr



async def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__	):
					'''simple docstring'''
					while True:
										lowercase					=		await stream.readline()
										if line:
															callback(lowerCAmelCase__	)
										else:
															break



async def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=None				,    lowerCAmelCase__=None				,    lowerCAmelCase__=None				,    lowerCAmelCase__=False				,    lowerCAmelCase__=False	):
					'''simple docstring'''
					if echo:
										print('''\nRunning: '''				,    ''' '''.join(lowerCAmelCase__	)	)

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

					# 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)

					lowercase					=		[]
					lowercase					=		[]

					def tee(lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__				,    lowerCAmelCase__=""	):
										lowercase					=		line.decode('''utf-8'''	).rstrip()
										sink.append(lowerCAmelCase__	)
										if not quiet:
															print(lowerCAmelCase__				,    lowerCAmelCase__				,    file=lowerCAmelCase__	)

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



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=None				,    lowerCAmelCase__=None				,    lowerCAmelCase__=180				,    lowerCAmelCase__=False				,    lowerCAmelCase__=True	):
					'''simple docstring'''
					lowercase					=		asyncio.get_event_loop()
					lowercase					=		loop.run_until_complete(
					    _stream_subprocess(lowerCAmelCase__				,    env=lowerCAmelCase__				,    stdin=lowerCAmelCase__				,    timeout=lowerCAmelCase__				,    quiet=lowerCAmelCase__				,    echo=lowerCAmelCase__	)	)

					lowercase					=		''' '''.join(lowerCAmelCase__	)
					if result.returncode > 0:
										lowercase					=		'''\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        lowercase	(      SCREAMING_SNAKE_CASE__	):
							pass



def  UpperCamelCase					(							lowerCAmelCase__				,    lowerCAmelCase__=False	):
					'''simple docstring'''
					try:
										lowercase					=		subprocess.check_output(lowerCAmelCase__				,    stderr=subprocess.STDOUT	)
										if return_stdout:
															if hasattr(lowerCAmelCase__				,    '''decode'''	):
																				lowercase					=		output.decode('''utf-8'''	)
															return output
					except subprocess.CalledProcessError as e:
										raise SubprocessCallException(
										    f'Command `{" ".join(lowerCAmelCase__	)}` failed with the following error:\n\n{e.output.decode()}'	) from e




