



'''simple docstring'''




import unittest

import numpy as np
import torch

from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()






class 						_UpperCamelCase  (							unittest.TestCase    ):


			'''simple docstring'''

			@property
			def UpperCamelCase__					(							self     : Optional[Any]						):





					"""simple docstring"""






					torch.manual_seed(0						)
					__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		UNetaDModel(
					    block_out_channels=(3_2, 6_4)							,     layers_per_block=2							,     sample_size=3_2							,     in_channels=3							,     out_channels=3							,     down_block_types=("""DownBlock2D""", """AttnDownBlock2D""")							,     up_block_types=("""AttnUpBlock2D""", """UpBlock2D""")							,     )
					return model



			def UpperCamelCase__					(							self     : Any						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		int           =		self.dummy_uncond_unet
					__SCREAMING_SNAKE_CASE       :		List[str]           =		PNDMScheduler()

					__SCREAMING_SNAKE_CASE       :		Any           =		PNDMPipeline(unet=lowerCAmelCase__							,     scheduler=lowerCAmelCase__						)
					pndm.to(lowerCAmelCase__						)
					pndm.set_progress_bar_config(disable=lowerCAmelCase__						)

					__SCREAMING_SNAKE_CASE       :		str           =		torch.manual_seed(0						)
					__SCREAMING_SNAKE_CASE       :		List[str]           =		pndm(generator=lowerCAmelCase__							,     num_inference_steps=2_0							,     output_type="""numpy"""						).images

					__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		torch.manual_seed(0						)
					__SCREAMING_SNAKE_CASE       :		int           =		pndm(generator=lowerCAmelCase__							,     num_inference_steps=2_0							,     output_type="""numpy"""							,     return_dict=lowerCAmelCase__						)[0]

					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		image[0, -3:, -3:, -1]
					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		image_from_tuple[0, -3:, -3:, -1]

					assert image.shape == (1, 3_2, 3_2, 3)
					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		np.array([1.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0]						)

					assert np.abs(image_slice.flatten() - expected_slice						).max() < 1E-2
					assert np.abs(image_from_tuple_slice.flatten() - expected_slice						).max() < 1E-2






@slow
@require_torch
class 						_UpperCamelCase  (							unittest.TestCase    ):


			'''simple docstring'''

			def UpperCamelCase__					(							self     : Union[str, Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Tuple           =		"""google/ddpm-cifar10-32"""

					__SCREAMING_SNAKE_CASE       :		List[Any]           =		UNetaDModel.from_pretrained(lowerCAmelCase__						)
					__SCREAMING_SNAKE_CASE       :		List[Any]           =		PNDMScheduler()

					__SCREAMING_SNAKE_CASE       :		Dict           =		PNDMPipeline(unet=lowerCAmelCase__							,     scheduler=lowerCAmelCase__						)
					pndm.to(lowerCAmelCase__						)
					pndm.set_progress_bar_config(disable=lowerCAmelCase__						)
					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		torch.manual_seed(0						)
					__SCREAMING_SNAKE_CASE       :		Any           =		pndm(generator=lowerCAmelCase__							,     output_type="""numpy"""						).images

					__SCREAMING_SNAKE_CASE       :		int           =		image[0, -3:, -3:, -1]

					assert image.shape == (1, 3_2, 3_2, 3)
					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		np.array([0.15_64, 0.1_46_45, 0.14_06, 0.1_47_15, 0.1_24_25, 0.1_40_45, 0.1_31_15, 0.1_21_75, 0.1_25]						)

					assert np.abs(image_slice.flatten() - expected_slice						).max() < 1E-2




'''simple docstring'''




import warnings

from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline  # noqa F401


warnings.warn(
    '''The `inpainting.py` script is outdated. Please use directly `from diffusers import'''
    ''' StableDiffusionInpaintPipeline` instead.'''
)