


import unittest

import numpy as np

from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    load_numpy,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)


if is_onnx_available():
			import onnxruntime as ort




@nightly
@require_onnxruntime
@require_torch_gpu
class    UpperCAmelCase					(       unittest.TestCase    ):




			@property
			def   lowerCamelCase_					(						self							:		int						):







						"""simple docstring"""







						return (
						    "CUDAExecutionProvider",
						    {
						        "gpu_mem_limit": "15000000000",  # 15GB
						        "arena_extend_strategy": "kSameAsRequested",
						    },
						)




			@property
			def   lowerCamelCase_					(						self							:		Dict						):







						"""simple docstring"""







						UpperCamelCase         =					ort.SessionOptions()
						UpperCamelCase         =					False
						return options





			def   lowerCamelCase_					(						self							:		Dict						):







						"""simple docstring"""







						UpperCamelCase         =					load_image(
						    """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"""
						    """/in_paint/overture-creations-5sI6fQgYIuo.png"""						)
						UpperCamelCase         =					load_image(
						    """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"""
						    """/in_paint/overture-creations-5sI6fQgYIuo_mask.png"""						)
						UpperCamelCase         =					load_numpy(
						    """https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"""
						    """/in_paint/red_cat_sitting_on_a_park_bench_onnx.npy"""						)

						# using the PNDM scheduler by default
						UpperCamelCase         =					OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
						    """CompVis/stable-diffusion-v1-4"""       ,       revision="""onnx"""       ,       safety_checker=__magic_name__       ,       feature_extractor=__magic_name__       ,       provider=self.gpu_provider       ,       sess_options=self.gpu_options       ,       )
						pipe.set_progress_bar_config(disable=__magic_name__						)

						UpperCamelCase         =					"""A red cat sitting on a park bench"""

						UpperCamelCase         =					np.random.RandomState(0						)
						UpperCamelCase         =					pipe(
						    prompt=__magic_name__       ,       image=__magic_name__       ,       mask_image=__magic_name__       ,       strength=0.75       ,       guidance_scale=7.5       ,       num_inference_steps=1_5       ,       generator=__magic_name__       ,       output_type="""np"""       ,       )

						UpperCamelCase         =					output.images[0]

						assert image.shape == (5_1_2, 5_1_2, 3)
						assert np.abs(expected_image - image						).max() < 1e-2








from ..utils import DummyObject, requires_backends




class    UpperCAmelCase					(       metaclass=__snake_case    ):
			lowercase						= ["""keras_nlp"""]




			def __init__(						self							:		List[str]       ,       *__magic_name__							:		str       ,       **__magic_name__							:		int						):







						"""simple docstring"""







						requires_backends(self       ,       ["""keras_nlp"""]						)




