

'''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 	_lowerCAmelCase (						_UpperCamelCase						:					Dict    )				->      Optional[int]:
     """simple docstring"""




     return EnvironmentCommand()


def 	_lowerCAmelCase (						_UpperCamelCase						:					int    )				->      str:
     """simple docstring"""




     return EnvironmentCommand(args.accelerate_config_file    )







class 							A__   (	A__  ):





  @staticmethod
  def 						A  (		_a				:     ArgumentParser			)     ->   List[Any]:





       '''simple docstring'''






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





  def __init__(		self				:     Optional[int]							, _a				:     List[Any]							, *_a				:     Dict			)     ->   None:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							   =accelerate_config_file





  def 						A  (		self				:     List[Any]			)     ->   Optional[Any]:





       '''simple docstring'''






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

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

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

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

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

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

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

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

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

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

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

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

       _SCREAMING_SNAKE_CASE							   ={
           '`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(_a			)			)

       return info





  @staticmethod
  def 						A  (		_a				:     Union[str, Any]			)     ->   Dict:





       '''simple docstring'''






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



'''simple docstring'''
from ..utils import DummyObject, requires_backends







class 							A__   (	metaclass=A__  ):
  A__					=    ['note_seq']





  def __init__(		self				:     List[str]							, *_a				:     Any							, **_a				:     Dict			)     ->   Optional[Any]:





       '''simple docstring'''






       requires_backends(self							, ['note_seq']			)





  @classmethod
  def 						A  (		cls				:     Any							, *_a				:     str							, **_a				:     List[Any]			)     ->   List[str]:





       '''simple docstring'''






       requires_backends(cls							, ['note_seq']			)





  @classmethod
  def 						A  (		cls				:     int							, *_a				:     Optional[Any]							, **_a				:     Optional[int]			)     ->   Tuple:





       '''simple docstring'''






       requires_backends(cls							, ['note_seq']			)
