


import argparse
import os
import subprocess

from packaging.version import Version, parse

from accelerate.commands.config.config_args import default_config_file, load_config_from_file


lowerCAmelCase__			:      Tuple								='''Run commands across TPU VMs for initial setup before running `accelerate launch`.'''






def 						a__			(				A__=None				):






			if subparsers is not None:
						SCREAMING_SNAKE_CASE_		:     Optional[int]					=					subparsers.add_parser('tpu-config',      description=_description				)
			else:
						SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					argparse.ArgumentParser('Accelerate tpu-config command',      description=_description				)
			# Core arguments
			SCREAMING_SNAKE_CASE_		:     Dict					=					parser.add_argument_group(
			    'Config Arguments',      'Arguments that can be configured through `accelerate config`.'				)
			config_args.add_argument(
			    '--config_file',      type=_lowercase,      default=_lowercase,      help='Path to the config file to use for accelerate.',      )
			config_args.add_argument(
			    '--tpu_name',      default=_lowercase,      help='The name of the TPU to use. If not specified, will use the TPU specified in the config file.',      )
			config_args.add_argument(
			    '--tpu_zone',      default=_lowercase,      help='The zone of the TPU to use. If not specified, will use the zone specified in the config file.',      )
			SCREAMING_SNAKE_CASE_		:     int					=					parser.add_argument_group('TPU Arguments',      'Arguments for options ran inside the TPU.'				)
			pod_args.add_argument(
			    '--use_alpha',      action='store_true',      help='Whether to use `gcloud alpha` when running the TPU training script instead of `gcloud`.',      )
			pod_args.add_argument(
			    '--command_file',      default=_lowercase,      help='The path to the file containing the commands to run on the pod on startup.',      )
			pod_args.add_argument(
			    '--command',      action='append',      nargs='+',      help='A command to run on the pod. Can be passed multiple times.',      )
			pod_args.add_argument(
			    '--install_accelerate',      action='store_true',      help='Whether to install accelerate on the pod. Defaults to False.',      )
			pod_args.add_argument(
			    '--accelerate_version',      default='latest',      help='The version of accelerate to install on the pod. If not specified, will use the latest pypi version. Specify \'dev\' to install from GitHub.',      )
			pod_args.add_argument(
			    '--debug',      action='store_true',      help='If set, will print the command that would be run instead of running it.'				)

			if subparsers is not None:
						parser.set_defaults(func=_lowercase				)
			return parser






def 						a__			(				A__				):
			SCREAMING_SNAKE_CASE_		:     List[Any]					=					None

			# Get the default from the config file if it exists.
			if args.config_file is not None or os.path.isfile(_lowercase				):
						SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					load_config_from_file(args.config_file				)
						if not args.command_file and defaults.command_file is not None and not args.command:
									SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					defaults.command_file
						if not args.command and defaults.commands is not None:
									SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					defaults.commands
						if not args.tpu_name:
									SCREAMING_SNAKE_CASE_		:     List[Any]					=					defaults.tpu_name
						if not args.tpu_zone:
									SCREAMING_SNAKE_CASE_		:     str					=					defaults.tpu_zone
			if args.accelerate_version == "dev":
						SCREAMING_SNAKE_CASE_		:     List[str]					=					"git+https://github.com/huggingface/accelerate.git"
			elif args.accelerate_version == "latest":
						SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					"accelerate -U"
			elif isinstance(parse(args.accelerate_version				),      _lowercase				):
						SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					F'''accelerate=={args.accelerate_version}'''

			if not args.command_file and not args.command:
						raise ValueError('You must specify either a command file or a command to run on the pod.'				)

			if args.command_file:
						with open(args.command_file,      'r'				) as f:
									SCREAMING_SNAKE_CASE_		:     List[str]					=					[f.read().splitlines()]

    # To turn list of lists into list of strings
			if isinstance(args.command[0],      _lowercase				):
						SCREAMING_SNAKE_CASE_		:     List[str]					=					[line for cmd in args.command for line in cmd]
			# Default to the shared folder and install accelerate
			SCREAMING_SNAKE_CASE_		:     int					=					["cd /usr/share"]
			if args.install_accelerate:
						new_cmd += [F'''pip install {args.accelerate_version}''']
			new_cmd += args.command
			SCREAMING_SNAKE_CASE_		:     List[str]					=					"; ".join(_lowercase				)

			# Then send it to gcloud
			# Eventually try to use google-api-core to do this instead of subprocess
			SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					["gcloud"]
			if args.use_alpha:
						cmd += ["alpha"]
			cmd += [
			    "compute",
			    "tpus",
			    "tpu-vm",
			    "ssh",
			    args.tpu_name,
			    "--zone",
			    args.tpu_zone,
			    "--command",
			    args.command,
			    "--worker",
			    "all",
			]
			if args.debug:
						print(F'''Running {' '.join(_lowercase				)}'''				)
						return
			subprocess.run(_lowercase				)
			print('Successfully setup pod.'				)






def 						a__			(				):
			SCREAMING_SNAKE_CASE_		:     Tuple					=					tpu_command_parser()
			SCREAMING_SNAKE_CASE_		:     int					=					parser.parse_args()

			tpu_command_launcher(_lowercase				)












"""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"""   )


