


import unittest

import numpy as np

from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)

from ..test_pipelines_onnx_common import OnnxPipelineTesterMixin


if is_onnx_available():
			import onnxruntime as ort


class        _a							(			UpperCamelCase__     ,	unittest.TestCase			):
							# FIXME: add fast tests
							pass


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

							@property
							def       lowerCamelCase_ (							self:	Optional[Any]							)			->   Union[str, Any]:





									"""simple docstring"""







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

							@property
							def       lowerCamelCase_ (							self:	Optional[Any]							)			->   Optional[Any]:





									"""simple docstring"""







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

							def       lowerCamelCase_ (							self:	int							)			->   Optional[int]:





									"""simple docstring"""







									lowercase__            =      load_image(
									    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
									    '''/in_paint/overture-creations-5sI6fQgYIuo.png'''							)
									lowercase__            =      load_image(
									    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
									    '''/in_paint/overture-creations-5sI6fQgYIuo_mask.png'''							)
									lowercase__            =      OnnxStableDiffusionInpaintPipeline.from_pretrained(
									    '''runwayml/stable-diffusion-inpainting'''    ,						revision='''onnx'''    ,						safety_checker=UpperCamelCase_    ,						feature_extractor=UpperCamelCase_    ,						provider=self.gpu_provider    ,						sess_options=self.gpu_options    ,						)
									pipe.set_progress_bar_config(disable=UpperCamelCase_							)

									lowercase__            =      '''A red cat sitting on a park bench'''

									lowercase__            =      np.random.RandomState(0							)
									lowercase__            =      pipe(
									    prompt=UpperCamelCase_    ,						image=UpperCamelCase_    ,						mask_image=UpperCamelCase_    ,						guidance_scale=7.5    ,						num_inference_steps=10    ,						generator=UpperCamelCase_    ,						output_type='''np'''    ,						)
									lowercase__            =      output.images
									lowercase__            =      images[0, 255:258, 255:258, -1]

									assert images.shape == (1, 512, 512, 3)
									lowercase__            =      np.array([0.2514, 0.3007, 0.3517, 0.1790, 0.2382, 0.3167, 0.1944, 0.2273, 0.2464]							)

									assert np.abs(image_slice.flatten() - expected_slice							).max() < 1E-3


							def       lowerCamelCase_ (							self:	List[str]							)			->   str:





									"""simple docstring"""







									lowercase__            =      load_image(
									    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
									    '''/in_paint/overture-creations-5sI6fQgYIuo.png'''							)
									lowercase__            =      load_image(
									    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
									    '''/in_paint/overture-creations-5sI6fQgYIuo_mask.png'''							)
									lowercase__            =      LMSDiscreteScheduler.from_pretrained(
									    '''runwayml/stable-diffusion-inpainting'''    ,						subfolder='''scheduler'''    ,						revision='''onnx'''							)
									lowercase__            =      OnnxStableDiffusionInpaintPipeline.from_pretrained(
									    '''runwayml/stable-diffusion-inpainting'''    ,						revision='''onnx'''    ,						scheduler=UpperCamelCase_    ,						safety_checker=UpperCamelCase_    ,						feature_extractor=UpperCamelCase_    ,						provider=self.gpu_provider    ,						sess_options=self.gpu_options    ,						)
									pipe.set_progress_bar_config(disable=UpperCamelCase_							)

									lowercase__            =      '''A red cat sitting on a park bench'''

									lowercase__            =      np.random.RandomState(0							)
									lowercase__            =      pipe(
									    prompt=UpperCamelCase_    ,						image=UpperCamelCase_    ,						mask_image=UpperCamelCase_    ,						guidance_scale=7.5    ,						num_inference_steps=20    ,						generator=UpperCamelCase_    ,						output_type='''np'''    ,						)
									lowercase__            =      output.images
									lowercase__            =      images[0, 255:258, 255:258, -1]

									assert images.shape == (1, 512, 512, 3)
									lowercase__            =      np.array([0.0086, 0.0077, 0.0083, 0.0093, 0.0107, 0.0139, 0.0094, 0.0097, 0.0125]							)

									assert np.abs(image_slice.flatten() - expected_slice							).max() < 1E-3




'''simple docstring'''







from math import isqrt, loga
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: int							):



						"""simple docstring"""





						lowercase_	:     Any													=       [True] * max_number
						for i in range(2      ,      isqrt(max_number - 1							) + 1							):
												if is_prime[i]:
																		for j in range(i**2      ,      __SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE							):
																								lowercase_	:     Optional[Any]													=       False

						return [i for i in range(2      ,      __SCREAMING_SNAKE_CASE							) if is_prime[i]]
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: int = 800800      ,      __SCREAMING_SNAKE_CASE					: int = 800800							):



						"""simple docstring"""





						lowercase_	:     Union[str, Any]													=       degree * loga(__SCREAMING_SNAKE_CASE							)
						lowercase_	:     Any													=       int(__SCREAMING_SNAKE_CASE							)
						lowercase_	:     Optional[Any]													=       calculate_prime_numbers(__SCREAMING_SNAKE_CASE							)

						lowercase_	:     Optional[Any]													=       0
						lowercase_	:     List[Any]													=       0
						lowercase_	:     Union[str, Any]													=       len(__SCREAMING_SNAKE_CASE							) - 1
						while left < right:
												while (
												    prime_numbers[right] * loga(prime_numbers[left]							)
												    + prime_numbers[left] * loga(prime_numbers[right]							)
												    > upper_bound
												):
																		right -= 1
												hybrid_integers_count += right - left
												left += 1

						return hybrid_integers_count


if __name__ == "__main__":
							print(f"""{solution() = }""")



