


"""simple docstring"""






# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os
import platform

import numpy as np
import psutil
import torch

from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file

from ..utils import is_npu_available, is_xpu_available





def 				A_       ( snake_case__=None		)					->  Optional[int]:
			if subparsers is not None:
						_UpperCamelCase					:Union[str, Any]					     =	subparsers.add_parser('''env'''		)
			else:
						_UpperCamelCase					:Optional[Any]					     =	argparse.ArgumentParser('''Accelerate env command'''		)

			parser.add_argument(
			    '''--config_file'''       ,					default=snake_case__       ,					help='''The config file to use for the default values in the launching script.'''		)

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





def 				A_       ( snake_case__		)					->  List[str]:
			_UpperCamelCase					:Tuple					     =	torch.__version__
			_UpperCamelCase					:str					     =	torch.cuda.is_available()
			_UpperCamelCase					:List[Any]					     =	is_xpu_available()
			_UpperCamelCase					:List[Any]					     =	is_npu_available()

			_UpperCamelCase					:Dict					     =	'''Not found'''
			# Get the default from the config file.
			if args.config_file is not None or os.path.isfile(snake_case__		):
						_UpperCamelCase					:Tuple					     =	load_config_from_file(args.config_file		).to_dict()

			_UpperCamelCase					:List[Any]					     =	{
			    '''`Accelerate` version''': version,
			    '''Platform''': platform.platform(),
			    '''Python version''': platform.python_version(),
			    '''Numpy version''': np.__version__,
			    '''PyTorch version (GPU?)''': f"{pt_version} ({pt_cuda_available})",
			    '''PyTorch XPU available''': str(snake_case__		),
			    '''PyTorch NPU available''': str(snake_case__		),
			    '''System RAM''': f"{psutil.virtual_memory().total / 10_24 ** 3:.2f} GB",
			}
			if pt_cuda_available:
						_UpperCamelCase					:Optional[Any]					     =	torch.cuda.get_device_name()

			print('''\nCopy-and-paste the text below in your GitHub issue\n'''		)
			print('''\n'''.join([f"- {prop}: {val}" for prop, val in info.items()]		)		)

			print('''- `Accelerate` default config:''' if args.config_file is None else '''- `Accelerate` config passed:'''		)
			_UpperCamelCase					:str					     =	(
			    '''\n'''.join([f"\t- {prop}: {val}" for prop, val in accelerate_config.items()]		)
			    if isinstance(snake_case__       ,					snake_case__		)
			    else f"\t{accelerate_config}"
			)
			print(snake_case__		)

			_UpperCamelCase					:List[Any]					     =	accelerate_config

			return info





def 				A_       ( )					->  int:
			_UpperCamelCase					:Tuple					     =	env_command_parser()
			_UpperCamelCase					:Any					     =	parser.parse_args()
			env_command(snake_case__		)
			return 0


if __name__ == "__main__":
					raise SystemExit(main())





"""simple docstring"""






def 				A_       ( snake_case__       ,					snake_case__ = " "		)					->  list:
			_UpperCamelCase					:List[str]					     =	[]

			_UpperCamelCase					:int					     =	0
			for index, char in enumerate(snake_case__		):
						if char == separator:
									split_words.append(string[last_index:index]		)
									_UpperCamelCase					:Dict					     =	index + 1
						elif index + 1 == len(snake_case__		):
									split_words.append(string[last_index : index + 1]		)
			return split_words


if __name__ == "__main__":
					from doctest import testmod

					testmod()

