




"""simple docstring"""





import unittest

import numpy as np
import PIL
import torch

from diffusers.image_processor import VaeImageProcessor

class    __lowercase							(      unittest.TestCase						):


				'''simple docstring'''


				@property
				def    _lowerCamelCase       ( self :  Dict   ):
										snake_case__							:       List[Any]				      =       1
										snake_case__							:       List[str]				      =       3
										snake_case__							:       Optional[Any]				      =       8
										snake_case__							:       Union[str, Any]				      =       8

										snake_case__							:       List[str]				      =       torch.rand((batch_size, num_channels, height, width)   )

										return sample

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

				def    _lowerCamelCase       ( self :  Tuple   ):
										snake_case__							:       Any				      =       VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE_   ,do_normalize=SCREAMING_SNAKE_CASE_   )

										snake_case__							:       Tuple				      =       self.dummy_sample
										snake_case__							:       Optional[int]				      =       self.to_np(SCREAMING_SNAKE_CASE_   )

										for output_type in ["pt", "np", "pil"]:
																snake_case__							:       Optional[int]				      =       image_processor.postprocess(
																    image_processor.preprocess(SCREAMING_SNAKE_CASE_   )   ,output_type=SCREAMING_SNAKE_CASE_   ,)
																snake_case__							:       str				      =       self.to_np(SCREAMING_SNAKE_CASE_   )
																snake_case__							:       Optional[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    _lowerCamelCase       ( self :  List[Any]   ):
										snake_case__							:       Tuple				      =       VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE_   ,do_normalize=SCREAMING_SNAKE_CASE_   )
										snake_case__							:       Tuple				      =       self.dummy_sample.cpu().numpy().transpose(0   ,2   ,3   ,1   )

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

																snake_case__							:       int				      =       self.to_np(SCREAMING_SNAKE_CASE_   )
																snake_case__							:       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    _lowerCamelCase       ( self :  Optional[int]   ):
										snake_case__							:       Optional[Any]				      =       VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE_   ,do_normalize=SCREAMING_SNAKE_CASE_   )

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

										for output_type in ["pt", "np", "pil"]:
																snake_case__							:       Optional[int]				      =       image_processor.postprocess(image_processor.preprocess(SCREAMING_SNAKE_CASE_   )   ,output_type=SCREAMING_SNAKE_CASE_   )
																for i, o in zip(SCREAMING_SNAKE_CASE_   ,SCREAMING_SNAKE_CASE_   ):
																						snake_case__							:       List[str]				      =       np.array(SCREAMING_SNAKE_CASE_   )
																						snake_case__							:       int				      =       self.to_np(SCREAMING_SNAKE_CASE_   ) if output_type == '''pil''' else (self.to_np(SCREAMING_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    _lowerCamelCase       ( self :  Any   ):
										snake_case__							:       Tuple				      =       VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE_   ,do_normalize=SCREAMING_SNAKE_CASE_   )

										snake_case__							:       Any				      =       self.dummy_sample
										snake_case__							:       List[Any]				      =       input_pt_ad.squeeze(0   )

										snake_case__							:       int				      =       image_processor.postprocess(
										    image_processor.preprocess(SCREAMING_SNAKE_CASE_   )   ,output_type='''np'''   ,)
										snake_case__							:       List[Any]				      =       image_processor.postprocess(
										    image_processor.preprocess(SCREAMING_SNAKE_CASE_   )   ,output_type='''np'''   ,)

										snake_case__							:       List[str]				      =       self.to_np(self.dummy_sample   )
										snake_case__							:       str				      =       input_np_ad.squeeze(0   )

										snake_case__							:       str				      =       image_processor.postprocess(
										    image_processor.preprocess(SCREAMING_SNAKE_CASE_   )   ,output_type='''np'''   ,)
										snake_case__							:       Optional[int]				      =       image_processor.postprocess(
										    image_processor.preprocess(SCREAMING_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    _lowerCamelCase       ( self :  Union[str, Any]   ):
										snake_case__							:       Optional[Any]				      =       VaeImageProcessor(do_resize=SCREAMING_SNAKE_CASE_   ,do_normalize=SCREAMING_SNAKE_CASE_   )

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

										snake_case__							:       str				      =       image_processor.postprocess(
										    image_processor.preprocess(SCREAMING_SNAKE_CASE_   )   ,output_type='''np'''   ,)

										snake_case__							:       Tuple				      =       image_processor.postprocess(
										    image_processor.preprocess(SCREAMING_SNAKE_CASE_   )   ,output_type='''np'''   ,)

										snake_case__							:       Optional[Any]				      =       self.to_np(self.dummy_sample   )
										list(SCREAMING_SNAKE_CASE_   )

										snake_case__							:       Dict				      =       image_processor.postprocess(
										    image_processor.preprocess(SCREAMING_SNAKE_CASE_   )   ,output_type='''np'''   ,)

										snake_case__							:       Dict				      =       image_processor.postprocess(
										    image_processor.preprocess(SCREAMING_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"""





from __future__ import annotations

from enum import Enum, unique
from typing import TypeVar

# Create a generic variable that can be 'Enum', or any subclass.
_lowercase						   =     TypeVar("""T""", bound="""Enum""")

@unique
class    __lowercase							(      snake_case_						):


				'''simple docstring'''


				_lowerCAmelCase						      =80
				_lowerCAmelCase						      =70
				_lowerCAmelCase						      =60
				_lowerCAmelCase						      =50
				_lowerCAmelCase						      =40
				_lowerCAmelCase						      =30
				_lowerCAmelCase						      =20
				_lowerCAmelCase						      =10







@unique
class    __lowercase							(      snake_case_						):


				'''simple docstring'''


				_lowerCAmelCase						      =24
				_lowerCAmelCase						      =21
				_lowerCAmelCase						      =18
				_lowerCAmelCase						      =15
				_lowerCAmelCase						      =12
				_lowerCAmelCase						      =9
				_lowerCAmelCase						      =6
				_lowerCAmelCase						      =3
				_lowerCAmelCase						      =2
				_lowerCAmelCase						      =1
				_lowerCAmelCase						      =-1
				_lowerCAmelCase						      =-2
				_lowerCAmelCase						      =-3
				_lowerCAmelCase						      =-6
				_lowerCAmelCase						      =-9
				_lowerCAmelCase						      =-12
				_lowerCAmelCase						      =-15
				_lowerCAmelCase						      =-18
				_lowerCAmelCase						      =-21
				_lowerCAmelCase						      =-24

				@classmethod
				def    _lowerCamelCase       ( cls :  type[T]   ):
										return {unit.name: unit.value for unit in cls if unit.value > 0}





				@classmethod
				def    _lowerCamelCase       ( cls :  type[T]   ):
										return {unit.name: unit.value for unit in cls if unit.value < 0}







def 		lowerCAmelCase				(			lowerCamelCase		):
						'''simple docstring'''


						snake_case__							:       List[Any]				      =       SIUnit.get_positive() if value > 0 else SIUnit.get_negative()
						for name_prefix, value_prefix in prefixes.items():
												snake_case__							:       Optional[int]				      =       value / (10**value_prefix)
												if numerical_part > 1:
																		return f'''{numerical_part!s} {name_prefix}'''
						return str(lowerCamelCase		)

def 		lowerCAmelCase				(			lowerCamelCase		):
						'''simple docstring'''


						for prefix in BinaryUnit:
												snake_case__							:       int				      =       value / (2**prefix.value)
												if numerical_part > 1:
																		return f'''{numerical_part!s} {prefix.name}'''
						return str(lowerCamelCase		)


if __name__ == "__main__":
							import doctest

							doctest.testmod()


