
'''simple docstring'''

import unittest

import numpy as np
import PIL
import torch

from diffusers.image_processor import VaeImageProcessor







class 	__lowerCAmelCase    (  unittest.TestCase				):



     @property
     def     snake_case_ (self	):
          _UpperCAmelCase					:  List[Any]         =    1
          _UpperCAmelCase					:  Union[str, Any]         =    3
          _UpperCAmelCase					:  Tuple         =    8
          _UpperCAmelCase					:  int         =    8

          _UpperCAmelCase					:  str         =    torch.rand((batch_size, num_channels, height, width)	)

          return sample



     def     snake_case_ (self						,	lowerCAmelCase__	):
          if isinstance(image[0]						,	PIL.Image.Image	):
               return np.stack([np.array(lowerCAmelCase__	) for i in image]						,	axis=0	)
          elif isinstance(lowerCAmelCase__						,	torch.Tensor	):
               return image.cpu().numpy().transpose(0						,	2						,	3						,	1	)
          return image



     def     snake_case_ (self	):
          _UpperCAmelCase					:  List[Any]         =    VaeImageProcessor(do_resize=lowerCAmelCase__						,	do_normalize=lowerCAmelCase__	)

          _UpperCAmelCase					:  List[str]         =    self.dummy_sample
          _UpperCAmelCase					:  Optional[Any]         =    self.to_np(lowerCAmelCase__	)

          for output_type in ["pt", "np", "pil"]:
               _UpperCAmelCase					:  int         =    image_processor.postprocess(
                   image_processor.preprocess(lowerCAmelCase__	)						,	output_type=lowerCAmelCase__						,	)
               _UpperCAmelCase					:  Dict         =    self.to_np(lowerCAmelCase__	)
               _UpperCAmelCase					:  int         =    (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     snake_case_ (self	):
          _UpperCAmelCase					:  List[str]         =    VaeImageProcessor(do_resize=lowerCAmelCase__						,	do_normalize=lowerCAmelCase__	)
          _UpperCAmelCase					:  List[Any]         =    self.dummy_sample.cpu().numpy().transpose(0						,	2						,	3						,	1	)

          for output_type in ["pt", "np", "pil"]:
               _UpperCAmelCase					:  Tuple         =    image_processor.postprocess(image_processor.preprocess(lowerCAmelCase__	)						,	output_type=lowerCAmelCase__	)

               _UpperCAmelCase					:  Union[str, Any]         =    self.to_np(lowerCAmelCase__	)
               _UpperCAmelCase					:  Union[str, Any]         =    (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     snake_case_ (self	):
          _UpperCAmelCase					:  str         =    VaeImageProcessor(do_resize=lowerCAmelCase__						,	do_normalize=lowerCAmelCase__	)

          _UpperCAmelCase					:  List[str]         =    self.dummy_sample.cpu().numpy().transpose(0						,	2						,	3						,	1	)
          _UpperCAmelCase					:  List[Any]         =    image_processor.numpy_to_pil(lowerCAmelCase__	)

          for output_type in ["pt", "np", "pil"]:
               _UpperCAmelCase					:  Optional[Any]         =    image_processor.postprocess(image_processor.preprocess(lowerCAmelCase__	)						,	output_type=lowerCAmelCase__	)
               for i, o in zip(lowerCAmelCase__						,	lowerCAmelCase__	):
                    _UpperCAmelCase					:  int         =    np.array(lowerCAmelCase__	)
                    _UpperCAmelCase					:  Tuple         =    self.to_np(lowerCAmelCase__	) if output_type == """pil""" else (self.to_np(lowerCAmelCase__	) * 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     snake_case_ (self	):
          _UpperCAmelCase					:  str         =    VaeImageProcessor(do_resize=lowerCAmelCase__						,	do_normalize=lowerCAmelCase__	)

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

          _UpperCAmelCase					:  Tuple         =    image_processor.postprocess(
              image_processor.preprocess(lowerCAmelCase__	)						,	output_type="""np"""						,	)
          _UpperCAmelCase					:  str         =    image_processor.postprocess(
              image_processor.preprocess(lowerCAmelCase__	)						,	output_type="""np"""						,	)

          _UpperCAmelCase					:  Union[str, Any]         =    self.to_np(self.dummy_sample	)
          _UpperCAmelCase					:  Tuple         =    input_np_ad.squeeze(0	)

          _UpperCAmelCase					:  List[str]         =    image_processor.postprocess(
              image_processor.preprocess(lowerCAmelCase__	)						,	output_type="""np"""						,	)
          _UpperCAmelCase					:  str         =    image_processor.postprocess(
              image_processor.preprocess(lowerCAmelCase__	)						,	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     snake_case_ (self	):
          _UpperCAmelCase					:  Union[str, Any]         =    VaeImageProcessor(do_resize=lowerCAmelCase__						,	do_normalize=lowerCAmelCase__	)

          _UpperCAmelCase					:  List[Any]         =    self.dummy_sample
          _UpperCAmelCase					:  Dict         =    list(lowerCAmelCase__	)

          _UpperCAmelCase					:  str         =    image_processor.postprocess(
              image_processor.preprocess(lowerCAmelCase__	)						,	output_type="""np"""						,	)

          _UpperCAmelCase					:  str         =    image_processor.postprocess(
              image_processor.preprocess(lowerCAmelCase__	)						,	output_type="""np"""						,	)

          _UpperCAmelCase					:  Tuple         =    self.to_np(self.dummy_sample	)
          list(lowerCAmelCase__	)

          _UpperCAmelCase					:  Any         =    image_processor.postprocess(
              image_processor.preprocess(lowerCAmelCase__	)						,	output_type="""np"""						,	)

          _UpperCAmelCase					:  Optional[Any]         =    image_processor.postprocess(
              image_processor.preprocess(lowerCAmelCase__	)						,	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'''

from itertools import permutations







def __A  (    ):
     _UpperCAmelCase					:  Union[str, Any]         =    list(map("""""".join ,       permutations("""0123456789"""       )       )       )
     return result[99_9999]


if __name__ == "__main__":
   print(solution())


