"""simple docstring"""






import importlib.util
import os
import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import (
    is_accelerate_available,
    is_flax_available,
    is_safetensors_available,
    is_tf_available,
    is_torch_available,
)
from . import BaseTransformersCLICommand



def SCREAMING_SNAKE_CASE__			(   __UpperCAmelCase )  ->  Any:
   return EnvironmentCommand()



def SCREAMING_SNAKE_CASE__			(   __UpperCAmelCase )  ->  str:
   return EnvironmentCommand(args.accelerate_config_file )




class     UpperCAmelCase						(_UpperCAmelCase  ):



    """simple docstring"""

    @staticmethod
    def _snake_case			(   _UpperCAmelCase							):
       lowercase__:   Optional[Any]					=      parser.add_parser('''env'''							)
       download_parser.set_defaults(func=_UpperCAmelCase							)
       download_parser.add_argument(
           '''--accelerate-config_file'''    ,			default=_UpperCAmelCase    ,			help='''The accelerate config file to use for the default values in the launching script.'''    ,			)
       download_parser.set_defaults(func=_UpperCAmelCase							)






    def __init__(   self    ,			_UpperCAmelCase    ,			*_UpperCAmelCase							):
       lowercase__:   int					=      accelerate_config_file






    def _snake_case			(   self							):
       lowercase__:   Optional[int]					=      '''not installed'''
       if is_safetensors_available():
          import safetensors

          lowercase__:   Optional[int]					=      safetensors.__version__
       elif importlib.util.find_spec('''safetensors'''							) is not None:
          import safetensors

          lowercase__:   Optional[int]					=      F"""{safetensors.__version__} but is ignored because of PyTorch version too old."""

       lowercase__:   List[str]					=      '''not installed'''
       lowercase__:   List[Any]					=      '''not found'''
       if is_accelerate_available():
          import accelerate
          from accelerate.commands.config import default_config_file, load_config_from_file

          lowercase__:   List[str]					=      accelerate.__version__
          # Get the default from the config file.
          if self._accelerate_config_file is not None or os.path.isfile(_UpperCAmelCase							):
             lowercase__:   Union[str, Any]					=      load_config_from_file(self._accelerate_config_file							).to_dict()

          lowercase__:   List[str]					=      (
              '''\n'''.join([F"""\t- {prop}: {val}""" for prop, val in accelerate_config.items()]							)
              if isinstance(_UpperCAmelCase    ,			_UpperCAmelCase							)
              else F"""\t{accelerate_config}"""
          )

       lowercase__:   Union[str, Any]					=      '''not installed'''
       lowercase__:   str					=      '''NA'''
       if is_torch_available():
          import torch

          lowercase__:   int					=      torch.__version__
          lowercase__:   Any					=      torch.cuda.is_available()

       lowercase__:   Optional[int]					=      '''not installed'''
       lowercase__:   Optional[int]					=      '''NA'''
       if is_tf_available():
          import tensorflow as tf

          lowercase__:   int					=      tf.__version__
          try:
             # deprecated in v2.1
             lowercase__:   List[str]					=      tf.test.is_gpu_available()
          except AttributeError:
             # returns list of devices, convert to bool
             lowercase__:   List[str]					=      bool(tf.config.list_physical_devices('''GPU'''							)							)

       lowercase__:   int					=      '''not installed'''
       lowercase__:   Union[str, Any]					=      '''not installed'''
       lowercase__:   Tuple					=      '''not installed'''
       lowercase__:   Any					=      '''NA'''
       if is_flax_available():
          import flax
          import jax
          import jaxlib

          lowercase__:   Dict					=      flax.__version__
          lowercase__:   List[Any]					=      jax.__version__
          lowercase__:   Dict					=      jaxlib.__version__
          lowercase__:   Dict					=      jax.lib.xla_bridge.get_backend().platform

       lowercase__:   Optional[Any]					=      {
           '''`transformers` version''': version,
           '''Platform''': platform.platform(),
           '''Python version''': platform.python_version(),
           '''Huggingface_hub version''': huggingface_hub.__version__,
           '''Safetensors version''': F"""{safetensors_version}""",
           '''Accelerate version''': F"""{accelerate_version}""",
           '''Accelerate config''': F"""{accelerate_config_str}""",
           '''PyTorch version (GPU?)''': F"""{pt_version} ({pt_cuda_available})""",
           '''Tensorflow version (GPU?)''': F"""{tf_version} ({tf_cuda_available})""",
           '''Flax version (CPU?/GPU?/TPU?)''': F"""{flax_version} ({jax_backend})""",
           '''Jax version''': F"""{jax_version}""",
           '''JaxLib version''': F"""{jaxlib_version}""",
           '''Using GPU in script?''': '''<fill in>''',
           '''Using distributed or parallel set-up in script?''': '''<fill in>''',
       }

       print('''\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'''							)
       print(self.format_dict(_UpperCAmelCase							)							)

       return info






    @staticmethod
    def _snake_case			(   _UpperCAmelCase							):
       return "\n".join([F"""- {prop}: {val}""" for prop, val in d.items()]							) + "\n"

"""simple docstring"""






def SCREAMING_SNAKE_CASE__			(   __UpperCAmelCase=2_8_1_2_3 )  ->  Any:
   lowercase__:   Optional[Any]					=      [1] * (limit + 1)

   for i in range(2       ,    int(limit**0.5 ) + 1 ):
      sum_divs[i * i] += i
      for k in range(i + 1       ,    limit // i + 1 ):
         sum_divs[k * i] += k + i

   lowercase__:   Union[str, Any]					=      set()
   lowercase__:   Optional[Any]					=      0

   for n in range(1       ,    limit + 1 ):
      if sum_divs[n] > n:
         abundants.add(__UpperCAmelCase )

      if not any((n - a in abundants) for a in abundants ):
         res += n

   return res


if __name__ == "__main__":
       print(solution())
