




# 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 lowerCamelCase__  (     _lowercase=None ):

     '''simple docstring'''


     if subparsers is not None:
          UpperCAmelCase_     :				Optional[Any]  =     subparsers.add_parser('''env''' )
     else:
          UpperCAmelCase_     :				List[str]  =     argparse.ArgumentParser('''Accelerate env command''' )

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

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







def lowerCamelCase__  (     _lowercase ):

     '''simple docstring'''


     UpperCAmelCase_     :				Dict  =     torch.__version__
     UpperCAmelCase_     :				Optional[Any]  =     torch.cuda.is_available()
     UpperCAmelCase_     :				int  =     is_xpu_available()
     UpperCAmelCase_     :				Union[str, Any]  =     is_npu_available()

     UpperCAmelCase_     :				Optional[Any]  =     '''Not found'''
     # Get the default from the config file.
     if args.config_file is not None or os.path.isfile(_lowercase ):
          UpperCAmelCase_     :				List[Any]  =     load_config_from_file(args.config_file ).to_dict()

     UpperCAmelCase_     :				Tuple  =     {
         '''`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(_lowercase ),
         '''PyTorch NPU available''': str(_lowercase ),
         '''System RAM''': f'''{psutil.virtual_memory().total / 1024 ** 3:.2f} GB''',
     }
     if pt_cuda_available:
          UpperCAmelCase_     :				int  =     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_     :				Optional[int]  =     (
         '''\n'''.join([f'''\t- {prop}: {val}''' for prop, val in accelerate_config.items()] )
         if isinstance(_lowercase					,		_lowercase )
         else f'''\t{accelerate_config}'''
     )
     print(_lowercase )

     UpperCAmelCase_     :				int  =     accelerate_config

     return info







def lowerCamelCase__  (     ):

     '''simple docstring'''


     UpperCAmelCase_     :				List[str]  =     env_command_parser()
     UpperCAmelCase_     :				Tuple  =     parser.parse_args()
     env_command(_lowercase )
     return 0


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




"""simple docstring"""







from __future__ import annotations

def       _lowerCamelCase				(							UpperCAmelCase_ :       float,	UpperCAmelCase_ :       float,	UpperCAmelCase_ :       float,	)	-> tuple:






	"""simple docstring"""





	if (electron_conc, hole_conc, intrinsic_conc).count(0     ) != 1:
		raise ValueError("You cannot supply more or less than 2 values"     )
	elif electron_conc < 0:
		raise ValueError("Electron concentration cannot be negative in a semiconductor"     )
	elif hole_conc < 0:
		raise ValueError("Hole concentration cannot be negative in a semiconductor"     )
	elif intrinsic_conc < 0:
		raise ValueError(
		    "Intrinsic concentration cannot be negative in a semiconductor"     )
	elif electron_conc == 0:
		return (
		    "electron_conc",
		    intrinsic_conc**2 / hole_conc,
		)
	elif hole_conc == 0:
		return (
		    "hole_conc",
		    intrinsic_conc**2 / electron_conc,
		)
	elif intrinsic_conc == 0:
		return (
		    "intrinsic_conc",
		    (electron_conc * hole_conc) ** 0.5,
		)
	else:
		return (-1, -1)


if __name__ == "__main__":
			import doctest

			doctest.testmod()




