import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand






def _lowerCamelCase  (		snake_case  ):
							return EnvironmentCommand()



class        lowerCamelCase__				(   UpperCAmelCase				):





			@staticmethod
			def   SCREAMING_SNAKE_CASE__     (       lowercase__	:	ArgumentParser						):
										_lowerCAmelCase							=							parser.add_parser('env'						)
										download_parser.set_defaults(func=lowercase__						)





			def   SCREAMING_SNAKE_CASE__     (       self	:	Union[str, Any]						):
										_lowerCAmelCase							=							huggingface_hub.__version__

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

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

										_lowerCAmelCase							=							'not installed'
										if is_transformers_available():
																	import transformers

																	_lowerCAmelCase							=							transformers.__version__

										_lowerCAmelCase							=							'not installed'
										if is_accelerate_available():
																	import accelerate

																	_lowerCAmelCase							=							accelerate.__version__

										_lowerCAmelCase							=							'not installed'
										if is_xformers_available():
																	import xformers

																	_lowerCAmelCase							=							xformers.__version__

										_lowerCAmelCase							=							{
										    '`diffusers` version': version,
										    'Platform': platform.platform(),
										    'Python version': platform.python_version(),
										    'PyTorch version (GPU?)': f'{pt_version} ({pt_cuda_available})',
										    'Huggingface_hub version': hub_version,
										    'Transformers version': transformers_version,
										    'Accelerate version': accelerate_version,
										    'xFormers version': xformers_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   SCREAMING_SNAKE_CASE__     (       lowercase__	:	Union[str, Any]						):
										return "\n".join([f'- {prop}: {val}' for prop, val in d.items()]						) + "\n"







from __future__ import annotations

from random import choice






def _lowerCamelCase  (		snake_case  ):
							return choice(snake_case  )






def _lowerCamelCase  (		snake_case     , snake_case  ):
							_lowerCAmelCase							=							random_pivot(snake_case  )

							# partition based on pivot
							# linear time
							_lowerCAmelCase							=							[e for e in lst if e < pivot]
							_lowerCAmelCase							=							[e for e in lst if e > pivot]

							# if we get lucky, pivot might be the element we want.
							# we can easily see this:
							# small (elements smaller than k)
							# + pivot (kth element)
							# + big (elements larger than k)
							if len(snake_case  ) == k - 1:
														return pivot
							# pivot is in elements bigger than k
							elif len(snake_case  ) < k - 1:
														return kth_number(snake_case     , k - len(snake_case  ) - 1  )
							# pivot is in elements smaller than k
							else:
														return kth_number(snake_case     , snake_case  )


if __name__ == "__main__":
				import doctest

				doctest.testmod()






