
"""simple docstring"""




import unittest

import numpy as np
import PIL
import torch

from diffusers.image_processor import VaeImageProcessor




class      UpperCamelCase	(       unittest.TestCase      ):

				"""simple docstring"""



				@property
				def 							A					(				self			)    ->    Union[str, Any]:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	1
									SCREAMING_SNAKE_CASE				=	3
									SCREAMING_SNAKE_CASE				=	8
									SCREAMING_SNAKE_CASE				=	8

									SCREAMING_SNAKE_CASE				=	torch.rand((batch_size, num_channels, height, width)			)

									return sample


				def 							A					(				self		,	lowercase__			)    ->    Dict:
									"""simple docstring"""







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


				def 							A					(				self			)    ->    int:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	VaeImageProcessor(do_resize=lowercase__		,	do_normalize=lowercase__			)

									SCREAMING_SNAKE_CASE				=	self.dummy_sample
									SCREAMING_SNAKE_CASE				=	self.to_np(lowercase__			)

									for output_type in ["pt", "np", "pil"]:
														SCREAMING_SNAKE_CASE				=	image_processor.postprocess(
														    image_processor.preprocess(lowercase__			)		,	output_type=lowercase__		,	)
														SCREAMING_SNAKE_CASE				=	self.to_np(lowercase__			)
														SCREAMING_SNAKE_CASE				=	(input_np * 255).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			)    ->    Any:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	VaeImageProcessor(do_resize=lowercase__		,	do_normalize=lowercase__			)
									SCREAMING_SNAKE_CASE				=	self.dummy_sample.cpu().numpy().transpose(0		,	2		,	3		,	1			)

									for output_type in ["pt", "np", "pil"]:
														SCREAMING_SNAKE_CASE				=	image_processor.postprocess(image_processor.preprocess(lowercase__			)		,	output_type=lowercase__			)

														SCREAMING_SNAKE_CASE				=	self.to_np(lowercase__			)
														SCREAMING_SNAKE_CASE				=	(input_np * 255).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			)    ->    str:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE				=	VaeImageProcessor(do_resize=lowercase__		,	do_normalize=lowercase__			)

									SCREAMING_SNAKE_CASE				=	self.dummy_sample.cpu().numpy().transpose(0		,	2		,	3		,	1			)
									SCREAMING_SNAKE_CASE				=	image_processor.numpy_to_pil(lowercase__			)

									for output_type in ["pt", "np", "pil"]:
														SCREAMING_SNAKE_CASE				=	image_processor.postprocess(image_processor.preprocess(lowercase__			)		,	output_type=lowercase__			)
														for i, o in zip(lowercase__		,	lowercase__			):
																			SCREAMING_SNAKE_CASE				=	np.array(lowercase__			)
																			SCREAMING_SNAKE_CASE				=	self.to_np(lowercase__			) if output_type == 'pil' else (self.to_np(lowercase__			) * 255).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"""







									SCREAMING_SNAKE_CASE				=	VaeImageProcessor(do_resize=lowercase__		,	do_normalize=lowercase__			)

									SCREAMING_SNAKE_CASE				=	self.dummy_sample
									SCREAMING_SNAKE_CASE				=	input_pt_ad.squeeze(0			)

									SCREAMING_SNAKE_CASE				=	image_processor.postprocess(
									    image_processor.preprocess(lowercase__			)		,	output_type='np'		,	)
									SCREAMING_SNAKE_CASE				=	image_processor.postprocess(
									    image_processor.preprocess(lowercase__			)		,	output_type='np'		,	)

									SCREAMING_SNAKE_CASE				=	self.to_np(self.dummy_sample			)
									SCREAMING_SNAKE_CASE				=	input_np_ad.squeeze(0			)

									SCREAMING_SNAKE_CASE				=	image_processor.postprocess(
									    image_processor.preprocess(lowercase__			)		,	output_type='np'		,	)
									SCREAMING_SNAKE_CASE				=	image_processor.postprocess(
									    image_processor.preprocess(lowercase__			)		,	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"""







									SCREAMING_SNAKE_CASE				=	VaeImageProcessor(do_resize=lowercase__		,	do_normalize=lowercase__			)

									SCREAMING_SNAKE_CASE				=	self.dummy_sample
									SCREAMING_SNAKE_CASE				=	list(lowercase__			)

									SCREAMING_SNAKE_CASE				=	image_processor.postprocess(
									    image_processor.preprocess(lowercase__			)		,	output_type='np'		,	)

									SCREAMING_SNAKE_CASE				=	image_processor.postprocess(
									    image_processor.preprocess(lowercase__			)		,	output_type='np'		,	)

									SCREAMING_SNAKE_CASE				=	self.to_np(self.dummy_sample			)
									list(lowercase__			)

									SCREAMING_SNAKE_CASE				=	image_processor.postprocess(
									    image_processor.preprocess(lowercase__			)		,	output_type='np'		,	)

									SCREAMING_SNAKE_CASE				=	image_processor.postprocess(
									    image_processor.preprocess(lowercase__			)		,	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'''


def 					_lowerCamelCase    (      lowerCamelCase_					:							str   ):



     """simple docstring"""





     UpperCAmelCase_							:   str   =      str(lowerCamelCase_   ).strip()
     if not oct_string:
          raise ValueError('Empty string was passed to the function'   )
     UpperCAmelCase_							:   Tuple   =      oct_string[0] == '-'
     if is_negative:
          UpperCAmelCase_							:   Tuple   =      oct_string[1:]
     if not oct_string.isdigit() or not all(0 <= int(lowerCamelCase_   ) <= 7 for char in oct_string   ):
          raise ValueError('Non-octal value was passed to the function'   )
     UpperCAmelCase_							:   str   =      0
     for char in oct_string:
          UpperCAmelCase_							:   List[Any]   =      8 * decimal_number + int(lowerCamelCase_   )
     if is_negative:
          UpperCAmelCase_							:   List[Any]   =      -decimal_number
     return decimal_number


if __name__ == "__main__":
 from doctest import testmod

 testmod()






