
'''simple docstring'''





import unittest
from dataclasses import dataclass
from typing import List, Union

import numpy as np
import PIL.Image

from diffusers.utils.outputs import BaseOutput


@dataclass
class 	UpperCamelCase__					(      SCREAMING_SNAKE_CASE):
 UpperCAmelCase__      :      Union[List[PIL.Image.Image], np.ndarray]


class 	UpperCamelCase__					(      unittest.TestCase):






 def 		lowercase_  (     self					:Optional[int]     )			->     List[str]:







       '''simple docstring'''



       __A    		=     CustomOutput(images=np.random.rand(1		,			3		,			4		,			4     )     )

       # check every way of getting the attribute
       assert isinstance(outputs.images		,			np.ndarray     )
       assert outputs.images.shape == (1, 3, 4, 4)
       assert isinstance(outputs['images']		,			np.ndarray     )
       assert outputs["images"].shape == (1, 3, 4, 4)
       assert isinstance(outputs[0]		,			np.ndarray     )
       assert outputs[0].shape == (1, 3, 4, 4)

       # test with a non-tensor attribute
       __A    		=     CustomOutput(images=[PIL.Image.new('RGB'		,			(4, 4)     )]     )

       # check every way of getting the attribute
       assert isinstance(outputs.images		,			_A     )
       assert isinstance(outputs.images[0]		,			PIL.Image.Image     )
       assert isinstance(outputs['images']		,			_A     )
       assert isinstance(outputs['images'][0]		,			PIL.Image.Image     )
       assert isinstance(outputs[0]		,			_A     )
       assert isinstance(outputs[0][0]		,			PIL.Image.Image     )






 def 		lowercase_  (     self					:Union[str, Any]     )			->     List[Any]:







       '''simple docstring'''



       __A    		=     CustomOutput({'images': np.random.rand(1		,			3		,			4		,			4     )}     )

       # check every way of getting the attribute
       assert isinstance(outputs.images		,			np.ndarray     )
       assert outputs.images.shape == (1, 3, 4, 4)
       assert isinstance(outputs['images']		,			np.ndarray     )
       assert outputs["images"].shape == (1, 3, 4, 4)
       assert isinstance(outputs[0]		,			np.ndarray     )
       assert outputs[0].shape == (1, 3, 4, 4)

       # test with a non-tensor attribute
       __A    		=     CustomOutput({'images': [PIL.Image.new('RGB'		,			(4, 4)     )]}     )

       # check every way of getting the attribute
       assert isinstance(outputs.images		,			_A     )
       assert isinstance(outputs.images[0]		,			PIL.Image.Image     )
       assert isinstance(outputs['images']		,			_A     )
       assert isinstance(outputs['images'][0]		,			PIL.Image.Image     )
       assert isinstance(outputs[0]		,			_A     )
       assert isinstance(outputs[0][0]		,			PIL.Image.Image     )








'''simple docstring'''





import itertools
from pathlib import Path





def     snake_case							(						UpperCAmelCase		)->     int:







      """simple docstring"""
      __A    		=     [tuple(UpperCAmelCase		) for login in logins]

      __A    		=     {char for login in split_logins for char in login}

      for permutation in itertools.permutations(UpperCAmelCase		):
            __A    		=     True
            for login in logins:
                  if not (
                      permutation.index(login[0]		)
                      < permutation.index(login[1]		)
                      < permutation.index(login[2]		)
                  ):
                        __A    		=     False
                        break

            if satisfied:
                  return int(''.join(UpperCAmelCase		)		)

      raise Exception('Unable to find the secret passcode'		)





def     snake_case							(						UpperCAmelCase = "keylog.txt"		)->     int:







      """simple docstring"""
      __A    		=     Path(UpperCAmelCase		).parent.joinpath(UpperCAmelCase		).read_text().splitlines()

      return find_secret_passcode(UpperCAmelCase		)


if __name__ == "__main__":
 print(f'''{solution() = }''')






