




'''simple docstring'''






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 		UpperCamelCase__      (		__SCREAMING_SNAKE_CASE		)    ->   Optional[Any]:
      return EnvironmentCommand()






class        lowercase_      (						lowerCAmelCase_							):





     @staticmethod
     def 			_lowerCAmelCase      (     __lowerCamelCase     :					ArgumentParser			):
           snake_case__       :   Any	      =    parser.add_parser('env'			)
           download_parser.set_defaults(func=__lowerCamelCase			)





     def 			_lowerCAmelCase      (     self     :					str			):
           snake_case__       :   str	      =    huggingface_hub.__version__

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

                 snake_case__       :   Union[str, Any]	      =    torch.__version__
                 snake_case__       :   List[str]	      =    torch.cuda.is_available()

           snake_case__       :   Union[str, Any]	      =    'not installed'
           if is_transformers_available():
                 import transformers

                 snake_case__       :   Any	      =    transformers.__version__

           snake_case__       :   Union[str, Any]	      =    'not installed'
           if is_accelerate_available():
                 import accelerate

                 snake_case__       :   int	      =    accelerate.__version__

           snake_case__       :   Tuple	      =    'not installed'
           if is_xformers_available():
                 import xformers

                 snake_case__       :   List[str]	      =    xformers.__version__

           snake_case__       :   Tuple	      =    {
               '`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(__lowerCamelCase			)			)

           return info





     @staticmethod
     def 			_lowerCAmelCase      (     __lowerCamelCase     :					Union[str, Any]			):
           return "\n".join([F"- {prop}: {val}" for prop, val in d.items()]			) + "\n"






'''simple docstring'''






import functools






def 		UpperCamelCase__      (		__SCREAMING_SNAKE_CASE				,      __SCREAMING_SNAKE_CASE		)    ->   int:
      snake_case__       :   Any	      =    len(__SCREAMING_SNAKE_CASE		)
      snake_case__       :   List[str]	      =    len(__SCREAMING_SNAKE_CASE		)

      @functools.cache
      def min_distance(__SCREAMING_SNAKE_CASE				,      __SCREAMING_SNAKE_CASE		) -> int:
            # if first word index is overflow - delete all from the second word
            if indexa >= len_worda:
                  return len_worda - indexa
            # if second word index is overflow - delete all from the first word
            if indexa >= len_worda:
                  return len_worda - indexa
            snake_case__       :   Union[str, Any]	      =    int(worda[indexa] != worda[indexa]		)  # current letters not identical
            return min(
                1 + min_distance(indexa + 1				,      __SCREAMING_SNAKE_CASE		)				,      1 + min_distance(__SCREAMING_SNAKE_CASE				,      indexa + 1		)				,      diff + min_distance(indexa + 1				,      indexa + 1		)				,      )

      return min_distance(0				,      0		)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
