

'''simple docstring'''

UpperCAmelCase					 =	[
    '''Audio''',
    '''Array2D''',
    '''Array3D''',
    '''Array4D''',
    '''Array5D''',
    '''ClassLabel''',
    '''Features''',
    '''Sequence''',
    '''Value''',
    '''Image''',
    '''Translation''',
    '''TranslationVariableLanguages''',
]
from .audio import Audio
from .features import ArrayaD, ArrayaD, ArrayaD, ArrayaD, ClassLabel, Features, Sequence, Value
from .image import Image
from .translation import Translation, TranslationVariableLanguages





'''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				(						lowercase__    :	Union[str, Any]			):






     '''simple docstring'''





     return EnvironmentCommand()

def 					__UpperCamelCase				(						lowercase__    :	Any			):






     '''simple docstring'''





     return EnvironmentCommand(args.accelerate_config_file			)







class 	lowerCAmelCase  (   A ):







       @staticmethod
       def       snake_case (				__lowercase      :			ArgumentParser   ):







            """simple docstring"""







            __lowercase      		=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      :			int    ,   __lowercase      :			Any    ,   *__lowercase      :			str   ):







            """simple docstring"""







            __lowercase      		=accelerate_config_file







       def       snake_case (				self      :			Optional[int]   ):







            """simple docstring"""







            __lowercase      		='not installed'
            if is_safetensors_available():
                 import safetensors

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

                 __lowercase      		=f'''{safetensors.__version__} but is ignored because of PyTorch version too old.'''

            __lowercase      		='not installed'
            __lowercase      		=__lowercase      		='not found'
            if is_accelerate_available():
                 import accelerate
                 from accelerate.commands.config import default_config_file, load_config_from_file

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

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

            __lowercase      		='not installed'
            __lowercase      		='NA'
            if is_torch_available():
                 import torch

                 __lowercase      		=torch.__version__
                 __lowercase      		=torch.cuda.is_available()

            __lowercase      		='not installed'
            __lowercase      		='NA'
            if is_tf_available():
                 import tensorflow as tf

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

            __lowercase      		='not installed'
            __lowercase      		='not installed'
            __lowercase      		='not installed'
            __lowercase      		='NA'
            if is_flax_available():
                 import flax
                 import jax
                 import jaxlib

                 __lowercase      		=flax.__version__
                 __lowercase      		=jax.__version__
                 __lowercase      		=jaxlib.__version__
                 __lowercase      		=jax.lib.xla_bridge.get_backend().platform

            __lowercase      		={
                '`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       snake_case (				__lowercase      :			Optional[Any]   ):







            """simple docstring"""







            return "\n".join([f'''- {prop}: {val}''' for prop, val in d.items()]   ) + "\n"


