'''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     __snake_case			(							lowerCAmelCase							:  Optional[Any]      ):
 return EnvironmentCommand()



def     __snake_case			(							lowerCAmelCase							:  Tuple      ):
 return EnvironmentCommand(args.accelerate_config_file      )

class 	_lowercase(  SCREAMING_SNAKE_CASE_					):



   """simple docstring"""





   @staticmethod
   def       snake_case						(				a:     ArgumentParser						):
    __UpperCAmelCase								=       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:     str      ,a:     str      ,*a:     Tuple						):
    __UpperCAmelCase								=       accelerate_config_file





   def       snake_case						(				self:     List[str]						):
    __UpperCAmelCase								=       'not installed'
    if is_safetensors_available():
     import safetensors

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

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

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

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

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

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

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

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

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

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

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

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








'''simple docstring'''





def 			a_	(				_lowerCAmelCase			,_lowerCAmelCase			) -> tuple[float, float]:

  # Check if the input is valid
  if not len(_lowerCAmelCase			) == len(_lowerCAmelCase			) == 3:
    raise ValueError('Please enter a valid equation.'			)
  if equationa[0] == equationa[1] == equationa[0] == equationa[1] == 0:
    raise ValueError('Both a & b of two equations can\'t be zero.'			)

  # Extract the coefficients
  __lowerCamelCase			,__lowerCamelCase			,__lowerCamelCase			:			Union[str, Any]       			=					equationa
  __lowerCamelCase			,__lowerCamelCase			,__lowerCamelCase			:			Any       			=					equationa

  # Calculate the determinants of the matrices
  __lowerCamelCase			:			Union[str, Any]       			=					aa * ba - aa * ba
  __lowerCamelCase			:			Dict       			=					ca * ba - ca * ba
  __lowerCamelCase			:			List[str]       			=					aa * ca - aa * ca

  # Check if the system of linear equations has a solution (using Cramer's rule)
  if determinant == 0:
    if determinant_x == determinant_y == 0:
      raise ValueError('Infinite solutions. (Consistent system)'			)
    else:
      raise ValueError('No solution. (Inconsistent system)'			)
  else:
    if determinant_x == determinant_y == 0:
      # Trivial solution (Inconsistent system)
      return (0.0, 0.0)
    else:
      __lowerCamelCase			:			Tuple       			=					determinant_x / determinant
      __lowerCamelCase			:			Union[str, Any]       			=					determinant_y / determinant
      # Non-Trivial Solution (Consistent system)
      return (x, y)






