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 							UpperCamelCase				(    lowerCAmelCase_=None   )		->						Dict:




       '''simple docstring'''






       if subparsers is not None:
              _A=	subparsers.add_parser('env'   )
       else:
              _A=	argparse.ArgumentParser('Accelerate env command'   )

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

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

def 							UpperCamelCase				(    lowerCAmelCase_   )		->						Optional[Any]:




       '''simple docstring'''






       _A=	torch.__version__
       _A=	torch.cuda.is_available()
       _A=	is_xpu_available()
       _A=	is_npu_available()

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

       _A=	{
           '`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(__lowerCAmelCase   ),
           'PyTorch NPU available': str(__lowerCAmelCase   ),
           'System RAM': F"{psutil.virtual_memory().total / 10_24 ** 3:.2f} GB",
       }
       if pt_cuda_available:
              _A=	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:'   )
       _A=	(
           '\n'.join([F"\t- {prop}: {val}" for prop, val in accelerate_config.items()]   )
           if isinstance(__lowerCAmelCase       ,					__lowerCAmelCase   )
           else F"\t{accelerate_config}"
       )
       print(__lowerCAmelCase   )

       _A=	accelerate_config

       return info

def 							UpperCamelCase				(    )		->						int:




       '''simple docstring'''






       _A=	env_command_parser()
       _A=	parser.parse_args()
       env_command(__lowerCAmelCase   )
       return 0


if __name__ == "__main__":
      raise SystemExit(main())
import pickle
import unittest

import torch

from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu





@require_cpu
class      lowerCAmelCase						(					unittest.TestCase			):



     def 			a__  (					self       ):
            _A=	torch.nn.Linear(10				,      10       )
            _A=	torch.optim.SGD(model.parameters()				,      0.1       )
            _A=	Accelerator()
            _A=	accelerator.prepare(lowerCAmelCase__       )
            try:
                   pickle.loads(pickle.dumps(lowerCAmelCase__       )       )
            except Exception as e:
                   self.fail(f"Accelerated optimizer pickling failed with {e}"       )
            AcceleratorState._reset_state()