





"""simple docstring"""






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       __lowerCamelCase    (       SCREAMING_SNAKE_CASE=None							)		->       Tuple:






       """simple docstring"""




       if subparsers is not None:
              _UpperCAmelCase     =     subparsers.add_parser('env'							)
       else:
              _UpperCAmelCase     =     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       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       Union[str, Any]:






       """simple docstring"""




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

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

       _UpperCAmelCase     =     {
           """`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 / 1024 ** 3:.2f} GB""",
       }
       if pt_cuda_available:
              _UpperCAmelCase     =     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     =     (
           """\n""".join([F"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]							)
           if isinstance(_lowerCamelCase,_lowerCamelCase							)
           else F"""\t{accelerate_config}"""
       )
       print(_lowerCamelCase							)

       _UpperCAmelCase     =     accelerate_config

       return info

def       __lowerCamelCase    (       )		->       Optional[int]:






       """simple docstring"""




       _UpperCAmelCase     =     env_command_parser()
       _UpperCAmelCase     =     parser.parse_args()
       env_command(_lowerCamelCase							)
       return 0


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













"""simple docstring"""






def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       list:






       """simple docstring"""




       _UpperCAmelCase     =     False
       while is_sorted is False:  # Until all the indices are traversed keep looping
              _UpperCAmelCase     =     True
              for i in range(0,len(SCREAMING_SNAKE_CASE							) - 1,2							):  # iterating over all even indices
                     if input_list[i] > input_list[i + 1]:
                            _UpperCAmelCase    ,							_UpperCAmelCase     =     input_list[i + 1], input_list[i]
                            # swapping if elements not in order
                            _UpperCAmelCase     =     False

              for i in range(1,len(SCREAMING_SNAKE_CASE							) - 1,2							):  # iterating over all odd indices
                     if input_list[i] > input_list[i + 1]:
                            _UpperCAmelCase    ,							_UpperCAmelCase     =     input_list[i + 1], input_list[i]
                            # swapping if elements not in order
                            _UpperCAmelCase     =     False
       return input_list


if __name__ == "__main__":
    print('''Enter list to be sorted''')
    lowerCAmelCase_			=							[int(x) for x in input().split()]
    # inputing elements of the list in one line
    lowerCAmelCase_			=							odd_even_sort(input_list)
    print('''The sorted list is''')
    print(sorted_list)






