


'''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      UpperCAmelCase__   (      UpperCAmelCase_       :							str				)	->						Optional[Any]:
     return EnvironmentCommand()



def      UpperCAmelCase__   (      UpperCAmelCase_       :							List[Any]				)	->						Tuple:
     return EnvironmentCommand(args.accelerate_config_file				)





class   UpperCAmelCase_    (__a    ):





    """simple docstring"""






    @staticmethod
    def  lowercase_							(				SCREAMING_SNAKE_CASE_      )							->	str:
         __lowerCamelCase  :      int														=						parser.add_parser('env'      )
         download_parser.set_defaults(func=_lowercase      )
         download_parser.add_argument(
             '--accelerate-config_file'     ,	default=_lowercase     ,	help='The accelerate config file to use for the default values in the launching script.'     ,	)
         download_parser.set_defaults(func=_lowercase      )







    def __init__(				self     ,	SCREAMING_SNAKE_CASE_     ,	*SCREAMING_SNAKE_CASE_      )							->	Tuple:
         __lowerCamelCase  :      List[str]														=						accelerate_config_file







    def  lowercase_							(				self      )							->	Dict:
         __lowerCamelCase  :      List[Any]														=						'''not installed'''
         if is_safetensors_available():
              import safetensors

              __lowerCamelCase  :      Dict														=						safetensors.__version__
         elif importlib.util.find_spec('safetensors'      ) is not None:
              import safetensors

              __lowerCamelCase  :      Optional[Any]														=						f'{safetensors.__version__} but is ignored because of PyTorch version too old.'

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

              __lowerCamelCase  :      int														=						accelerate.__version__
              # Get the default from the config file.
              if self._accelerate_config_file is not None or os.path.isfile(_lowercase      ):
                   __lowerCamelCase  :      int														=						load_config_from_file(self._accelerate_config_file      ).to_dict()

              __lowerCamelCase  :      Any														=						(
                  '''\n'''.join([f'\t- {prop}: {val}' for prop, val in accelerate_config.items()]      )
                  if isinstance(_lowercase     ,	_lowercase      )
                  else f'\t{accelerate_config}'
              )

         __lowerCamelCase  :      int														=						'''not installed'''
         __lowerCamelCase  :      Dict														=						'''NA'''
         if is_torch_available():
              import torch

              __lowerCamelCase  :      List[Any]														=						torch.__version__
              __lowerCamelCase  :      List[Any]														=						torch.cuda.is_available()

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

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

         __lowerCamelCase  :      Optional[int]														=						'''not installed'''
         __lowerCamelCase  :      str														=						'''not installed'''
         __lowerCamelCase  :      Tuple														=						'''not installed'''
         __lowerCamelCase  :      Tuple														=						'''NA'''
         if is_flax_available():
              import flax
              import jax
              import jaxlib

              __lowerCamelCase  :      Optional[Any]														=						flax.__version__
              __lowerCamelCase  :      Union[str, Any]														=						jax.__version__
              __lowerCamelCase  :      Optional[Any]														=						jaxlib.__version__
              __lowerCamelCase  :      Optional[int]														=						jax.lib.xla_bridge.get_backend().platform

         __lowerCamelCase  :      Union[str, 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(_lowercase      )      )

         return info







    @staticmethod
    def  lowercase_							(				SCREAMING_SNAKE_CASE_      )							->	Tuple:
         return "\n".join([f'- {prop}: {val}' for prop, val in d.items()]      ) + "\n"







import torch




def    lowerCAmelCase_  (		)     ->					int:







 '''simple docstring'''
 if torch.cuda.is_available():
  _UpperCamelCase:  Any    						=			torch.cuda.device_count()
 else:
  _UpperCamelCase:  Union[str, Any]    						=			0
 print(F"""Successfully ran on {num_gpus} GPUs"""		)


if __name__ == "__main__":
  main()