



'''simple docstring'''




def _lowerCAmelCase     (      _lowerCAmelCase    )->     int:
 if not isinstance(_lowercase       ,    _lowercase    ):
  raise ValueError('Input must be an integer'    )
 if input_num <= 0:
  raise ValueError('Input must be positive'    )
 return sum(
     divisor for divisor in range(1       ,    input_num // 2 + 1    ) if input_num % divisor == 0    )


if __name__ == "__main__":
    import doctest

    doctest.testmod()












'''simple docstring'''




# Copyright 2021 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.

from pathlib import Path

import torch

from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter


_A:					str							=				"""Create a default config file for Accelerate with only a few flags set."""







def _lowerCAmelCase     (      _lowerCAmelCase="no"       ,    _lowerCAmelCase = default_json_config_file       ,    _lowerCAmelCase = False    )->     List[Any]:
 __UpperCAmelCase					=   Path(_lowerCAmelCase    )
 path.parent.mkdir(parents=_lowerCAmelCase       ,    exist_ok=_lowerCAmelCase    )
 if path.exists():
  print(
      F'Configuration already exists at {save_location}, will not override. Run `accelerate config` manually or pass a different `save_location`.'    )
  return False
 __UpperCAmelCase					=   mixed_precision.lower()
 if mixed_precision not in ["no", "fp16", "bf16", "fp8"]:
  raise ValueError(
      F'`mixed_precision` should be one of \'no\', \'fp16\', \'bf16\', or \'fp8\'. Received {mixed_precision}'    )
 __UpperCAmelCase					=   {
     'compute_environment': 'LOCAL_MACHINE',
     'mixed_precision': mixed_precision,
 }
 if torch.cuda.is_available():
  __UpperCAmelCase					=   torch.cuda.device_count()
  __UpperCAmelCase					=   num_gpus
  __UpperCAmelCase					=   False
  if num_gpus > 1:
   __UpperCAmelCase					=   'MULTI_GPU'
  else:
   __UpperCAmelCase					=   'NO'
 elif is_xpu_available() and use_xpu:
  __UpperCAmelCase					=   torch.xpu.device_count()
  __UpperCAmelCase					=   num_xpus
  __UpperCAmelCase					=   False
  if num_xpus > 1:
   __UpperCAmelCase					=   'MULTI_XPU'
  else:
   __UpperCAmelCase					=   'NO'
 elif is_npu_available():
  __UpperCAmelCase					=   torch.npu.device_count()
  __UpperCAmelCase					=   num_npus
  __UpperCAmelCase					=   False
  if num_npus > 1:
   __UpperCAmelCase					=   'MULTI_NPU'
  else:
   __UpperCAmelCase					=   'NO'
 else:
  __UpperCAmelCase					=   0
  __UpperCAmelCase					=   True
  __UpperCAmelCase					=   1
  __UpperCAmelCase					=   'NO'
 __UpperCAmelCase					=   ClusterConfig(**_lowerCAmelCase    )
 config.to_json_file(_lowerCAmelCase    )
 return path







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase    )->     List[str]:
 __UpperCAmelCase					=   parser.add_parser('default'       ,    parents=_lowerCAmelCase       ,    help=_lowerCAmelCase       ,    formatter_class=_lowerCAmelCase    )
 parser.add_argument(
     '--config_file'       ,    default=_lowerCAmelCase       ,    help=(
         'The path to use to store the config file. Will default to a file named default_config.yaml in the cache '
         'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
         'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
         'with \'huggingface\'.'
     )       ,    dest='save_location'       ,    )

 parser.add_argument(
     '--mixed_precision'       ,    choices=['no', 'fp16', 'bf16']       ,    type=_lowerCAmelCase       ,    help='Whether or not to use mixed precision training. '
     'Choose between FP16 and BF16 (bfloat16) training. '
     'BF16 training is only supported on Nvidia Ampere GPUs and PyTorch 1.10 or later.'       ,    default='no'       ,    )
 parser.set_defaults(func=_lowerCAmelCase    )
 return parser







def _lowerCAmelCase     (      _lowerCAmelCase    )->     Union[str, Any]:
 __UpperCAmelCase					=   write_basic_config(args.mixed_precision       ,    args.save_location    )
 if config_file:
  print(F'accelerate configuration saved at {config_file}'    )





