


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        __lowercase						(      __SCREAMING_SNAKE_CASE		)				->					Dict:
     """simple docstring"""




     return EnvironmentCommand()




def        __lowercase						(      __SCREAMING_SNAKE_CASE		)				->					Tuple:
     """simple docstring"""




     return EnvironmentCommand(args.accelerate_config_file		)



class  lowerCAmelCase_						(       __UpperCAmelCase      ):





  """simple docstring"""



  @staticmethod
  def __a						(					SCREAMING_SNAKE_CASE__     :							Any						):





       '''simple docstring'''

       __a       =   parser.add_parser("""env"""						)
       download_parser.set_defaults(func=SCREAMING_SNAKE_CASE__						)
       download_parser.add_argument(
           """--accelerate-config_file"""				,							default=SCREAMING_SNAKE_CASE__				,							help="""The accelerate config file to use for the default values in the launching script."""				,							)
       download_parser.set_defaults(func=SCREAMING_SNAKE_CASE__						)

  def __init__(					self     :							List[Any]				,							SCREAMING_SNAKE_CASE__     :							Optional[int]				,							*SCREAMING_SNAKE_CASE__     :							int						):





       '''simple docstring'''

       __a       =   accelerate_config_file

  def __a						(					self     :							Optional[Any]						):





       '''simple docstring'''

       __a       =   """not installed"""
       if is_safetensors_available():
            import safetensors

            __a       =   safetensors.__version__
       elif importlib.util.find_spec("""safetensors"""						) is not None:
            import safetensors

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

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

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

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

       __a       =   """not installed"""
       __a       =   """NA"""
       if is_torch_available():
            import torch

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

       __a       =   """not installed"""
       __a       =   """NA"""
       if is_tf_available():
            import tensorflow as tf

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

       __a       =   """not installed"""
       __a       =   """not installed"""
       __a       =   """not installed"""
       __a       =   """NA"""
       if is_flax_available():
            import flax
            import jax
            import jaxlib

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

       __a       =   {
           """`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(SCREAMING_SNAKE_CASE__						)						)

       return info


  @staticmethod
  def __a						(					SCREAMING_SNAKE_CASE__     :							Dict						):





       '''simple docstring'''

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










'''simple docstring'''







def        __lowercase						(      __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE		)				->					str:
     """simple docstring"""




     __a       =   """"""
     for word_or_phrase in separated:
          if not isinstance(__SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE		):
               raise Exception("""join() accepts only strings to be joined"""		)
          joined += word_or_phrase + separator
     return joined.strip(__SCREAMING_SNAKE_CASE		)


if __name__ == "__main__":
 from doctest import testmod

 testmod()






