






"""simple docstring"""



import unittest

import numpy as np
import PIL
import torch

from diffusers.image_processor import VaeImageProcessor




class        lowerCAmelCase__       (  unittest.TestCase					):
   @property
   def 	__a				(						self	:     Optional[int]				):


        '''simple docstring'''
        UpperCAmelCase__		:  Dict				=				1
        UpperCAmelCase__		:  List[str]				=				3
        UpperCAmelCase__		:  Optional[int]				=				8
        UpperCAmelCase__		:  List[Any]				=				8

        UpperCAmelCase__		:  List[Any]				=				torch.rand((batch_size, num_channels, height, width)				)

        return sample
   def 	__a				(						self	:     Dict				,       snake_case__	:     List[str]				):


        '''simple docstring'''
        if isinstance(image[0]				,       PIL.Image.Image				):
             return np.stack([np.array(snake_case__				) for i in image]				,       axis=0				)
        elif isinstance(snake_case__				,       torch.Tensor				):
             return image.cpu().numpy().transpose(0				,       2				,       3				,       1				)
        return image
   def 	__a				(						self	:     List[Any]				):


        '''simple docstring'''
        UpperCAmelCase__		:  List[Any]				=				VaeImageProcessor(do_resize=snake_case__				,       do_normalize=snake_case__				)

        UpperCAmelCase__		:  int				=				self.dummy_sample
        UpperCAmelCase__		:  str				=				self.to_np(snake_case__				)

        for output_type in ["pt", "np", "pil"]:
             UpperCAmelCase__		:  Any				=				image_processor.postprocess(
                 image_processor.preprocess(snake_case__				)				,       output_type=snake_case__				,       )
             UpperCAmelCase__		:  Optional[Any]				=				self.to_np(snake_case__				)
             UpperCAmelCase__		:  List[str]				=				(input_np * 2_5_5).round() if output_type == "pil" else input_np
             assert (
                 np.abs(in_np - out_np				).max() < 1e-6
             ), f'decoded output does not match input for output_type {output_type}'
   def 	__a				(						self	:     Dict				):


        '''simple docstring'''
        UpperCAmelCase__		:  Union[str, Any]				=				VaeImageProcessor(do_resize=snake_case__				,       do_normalize=snake_case__				)
        UpperCAmelCase__		:  Optional[int]				=				self.dummy_sample.cpu().numpy().transpose(0				,       2				,       3				,       1				)

        for output_type in ["pt", "np", "pil"]:
             UpperCAmelCase__		:  Any				=				image_processor.postprocess(image_processor.preprocess(snake_case__				)				,       output_type=snake_case__				)

             UpperCAmelCase__		:  str				=				self.to_np(snake_case__				)
             UpperCAmelCase__		:  Dict				=				(input_np * 2_5_5).round() if output_type == "pil" else input_np
             assert (
                 np.abs(in_np - out_np				).max() < 1e-6
             ), f'decoded output does not match input for output_type {output_type}'
   def 	__a				(						self	:     Dict				):


        '''simple docstring'''
        UpperCAmelCase__		:  List[Any]				=				VaeImageProcessor(do_resize=snake_case__				,       do_normalize=snake_case__				)

        UpperCAmelCase__		:  int				=				self.dummy_sample.cpu().numpy().transpose(0				,       2				,       3				,       1				)
        UpperCAmelCase__		:  Union[str, Any]				=				image_processor.numpy_to_pil(snake_case__				)

        for output_type in ["pt", "np", "pil"]:
             UpperCAmelCase__		:  Any				=				image_processor.postprocess(image_processor.preprocess(snake_case__				)				,       output_type=snake_case__				)
             for i, o in zip(snake_case__				,       snake_case__				):
                  UpperCAmelCase__		:  List[str]				=				np.array(snake_case__				)
                  UpperCAmelCase__		:  Optional[int]				=				self.to_np(snake_case__				) if output_type == "pil" else (self.to_np(snake_case__				) * 2_5_5).round()
                  assert (
                      np.abs(in_np - out_np				).max() < 1e-6
                  ), f'decoded output does not match input for output_type {output_type}'
   def 	__a				(						self	:     List[str]				):


        '''simple docstring'''
        UpperCAmelCase__		:  Any				=				VaeImageProcessor(do_resize=snake_case__				,       do_normalize=snake_case__				)

        UpperCAmelCase__		:  List[str]				=				self.dummy_sample
        UpperCAmelCase__		:  int				=				input_pt_ad.squeeze(0				)

        UpperCAmelCase__		:  Any				=				image_processor.postprocess(
            image_processor.preprocess(snake_case__				)				,       output_type="np"				,       )
        UpperCAmelCase__		:  Union[str, Any]				=				image_processor.postprocess(
            image_processor.preprocess(snake_case__				)				,       output_type="np"				,       )

        UpperCAmelCase__		:  Dict				=				self.to_np(self.dummy_sample				)
        UpperCAmelCase__		:  Any				=				input_np_ad.squeeze(0				)

        UpperCAmelCase__		:  int				=				image_processor.postprocess(
            image_processor.preprocess(snake_case__				)				,       output_type="np"				,       )
        UpperCAmelCase__		:  Tuple				=				image_processor.postprocess(
            image_processor.preprocess(snake_case__				)				,       output_type="np"				,       )

        assert np.abs(out_pt_ad - out_pt_ad				).max() < 1e-6
        assert np.abs(out_np_ad - out_np_ad				).max() < 1e-6




   def 	__a				(						self	:     Optional[Any]				):


        '''simple docstring'''
        UpperCAmelCase__		:  Any				=				VaeImageProcessor(do_resize=snake_case__				,       do_normalize=snake_case__				)

        UpperCAmelCase__		:  Dict				=				self.dummy_sample
        UpperCAmelCase__		:  List[Any]				=				list(snake_case__				)

        UpperCAmelCase__		:  int				=				image_processor.postprocess(
            image_processor.preprocess(snake_case__				)				,       output_type="np"				,       )

        UpperCAmelCase__		:  Dict				=				image_processor.postprocess(
            image_processor.preprocess(snake_case__				)				,       output_type="np"				,       )

        UpperCAmelCase__		:  List[Any]				=				self.to_np(self.dummy_sample				)
        list(snake_case__				)

        UpperCAmelCase__		:  Optional[int]				=				image_processor.postprocess(
            image_processor.preprocess(snake_case__				)				,       output_type="np"				,       )

        UpperCAmelCase__		:  Optional[int]				=				image_processor.postprocess(
            image_processor.preprocess(snake_case__				)				,       output_type="np"				,       )

        assert np.abs(out_pt_ad - out_pt_list				).max() < 1e-6
        assert np.abs(out_np_ad - out_np_list				).max() < 1e-6






'''simple docstring'''







import sys

sys.set_int_max_str_digits(0)  # type: ignore






def       lowerCAmelCase__       (				lowerCamelCase     :			int   ):
       _A     :	Optional[Any]      =					[0] * 11
       _A     :	str      =					[0] * 11

       # mark last 9 numbers
       for _ in range(9   ):
              _A     :	int      =					1
              _A     :	Optional[int]      =					number // 10
       # flag
       _A     :	List[Any]      =					True

       # check last 9 numbers for pandigitality

       for x in range(9   ):
              if not check_last[x + 1]:
                     _A     :	Optional[int]      =					False
       if not f:
              return f

       # mark first 9 numbers
       _A     :	Optional[int]      =					int(str(lowerCamelCase   )[:9]   )

       for _ in range(9   ):
              _A     :	Optional[Any]      =					1
              _A     :	str      =					number // 10

       # check first 9 numbers for pandigitality

       for x in range(9   ):
              if not check_front[x + 1]:
                     _A     :	Optional[Any]      =					False
       return f






def       lowerCAmelCase__       (				lowerCamelCase     :			int   ):
       _A     :	Dict      =					[0] * 11

       # mark last 9 numbers
       for _ in range(9   ):
              _A     :	List[str]      =					1
              _A     :	Dict      =					number // 10
       # flag
       _A     :	Optional[int]      =					True

       # check last 9 numbers for pandigitality

       for x in range(9   ):
              if not check_last[x + 1]:
                     _A     :	List[str]      =					False
       return f






def       lowerCAmelCase__       (				):
       _A     :	List[Any]      =					1
       _A     :	Dict      =					1
       _A     :	Dict      =					2
       # temporary Fibonacci numbers

       _A     :	List[Any]      =					1
       _A     :	Union[str, Any]      =					1
       _A     :	List[Any]      =					2
       # temporary Fibonacci numbers mod 1e9

       # mod m=1e9, done for fast optimisation
       _A     :	Tuple      =					[0] * 1000000
       _A     :	Any      =					1000000000

       for x in range(1000000   ):
              _A     :	Tuple      =					(aa + ba) % m
              _A     :	Optional[Any]      =					ba % m
              _A     :	str      =					ca % m
              if checka(lowerCamelCase   ):
                     _A     :	Dict      =					1

       for x in range(1000000   ):
              _A     :	List[str]      =					a + b
              _A     :	Optional[int]      =					b
              _A     :	str      =					c
              # perform check only if in tocheck
              if tocheck[x + 3] and check(lowerCamelCase   ):
                     return x + 3  # first 2 already done
       return -1


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






