






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      a_ (      _A  )			->			int:







				"""simple docstring"""
				return EnvironmentCommand()
def      a_ (      _A  )			->			List[Any]:







				"""simple docstring"""
				return EnvironmentCommand(args.accelerate_config_file  )


class   __SCREAMING_SNAKE_CASE(	a_	):
							@staticmethod
							def lowerCAmelCase_ (     UpperCamelCase:      ArgumentParser						)		->		Any:
											snake_case__									=     parser.add_parser('env'						)
											download_parser.set_defaults(func=UpperCamelCase						)
											download_parser.add_argument(
											    '--accelerate-config_file'       ,	default=UpperCamelCase       ,	help='The accelerate config file to use for the default values in the launching script.'       ,	)
											download_parser.set_defaults(func=UpperCamelCase						)
							def __init__(     self:      Optional[int]       ,	UpperCamelCase:      str       ,	*UpperCamelCase:      Optional[int]						)		->		None:
											snake_case__									=     accelerate_config_file
							def lowerCAmelCase_ (     self:      List[str]						)		->		Union[str, Any]:
											snake_case__									=     'not installed'
											if is_safetensors_available():
															import safetensors

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

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

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

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

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

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

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

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

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

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

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

											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(UpperCamelCase						)						)

											return info


							@staticmethod
							def lowerCAmelCase_ (     UpperCamelCase:      Dict						)		->		str:
											return "\n".join([F'''- {prop}: {val}''' for prop, val in d.items()]						) + "\n"












from __future__ import annotations
def      a_ (      _A      ,   _A  )			->			str:







				"""simple docstring"""
				# Checks if the entire collection has been sorted
				if len(_A  ) <= 1 or n <= 1:
								return

				insert_next(_A      ,   n - 1  )
				rec_insertion_sort(_A      ,   n - 1  )
def      a_ (      _A      ,   _A  )			->			Tuple:







				"""simple docstring"""
				# Checks order between adjacent elements
				if index >= len(_A  ) or collection[index - 1] <= collection[index]:
								return

				# Swaps adjacent elements since they are not in ascending order
				snake_case__							,						snake_case__									=     (
				    collection[index],
				    collection[index - 1],
				)

				insert_next(_A      ,   index + 1  )


if __name__ == "__main__":
							__UpperCamelCase					:		Optional[int]	  =						input("""Enter integers separated by spaces: """)
							__UpperCamelCase					:		list[int]	  =						[int(num) for num in numbers.split()]
							rec_insertion_sort(number_list, len(number_list))
							print(number_list)




