





'''simple docstring'''
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      snake_case     (    unittest.TestCase       ):




 """simple docstring"""



 @property
 def        _lowerCamelCase					(       self       :							Optional[int]	):
        return (
            "CUDAExecutionProvider",
            {
                "gpu_mem_limit": "15000000000",  # 15GB
                "arena_extend_strategy": "kSameAsRequested",
            },
        )






 @property
 def        _lowerCamelCase					(       self       :							List[str]	):
        __UpperCamelCase       =  ort.SessionOptions()
        __UpperCamelCase       =  False
        return options






 def        _lowerCamelCase					(       self       :							Union[str, Any]	):
        __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=__SCREAMING_SNAKE_CASE							,	feature_extractor=__SCREAMING_SNAKE_CASE							,	provider=self.gpu_provider							,	sess_options=self.gpu_options							,	)
        pipe.set_progress_bar_config(disable=__SCREAMING_SNAKE_CASE	)

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

        __UpperCamelCase       =  np.random.RandomState(0	)
        __UpperCamelCase       =  pipe(
            prompt=__SCREAMING_SNAKE_CASE							,	image=__SCREAMING_SNAKE_CASE							,	mask_image=__SCREAMING_SNAKE_CASE							,	strength=0.75							,	guidance_scale=7.5							,	num_inference_steps=1_5							,	generator=__SCREAMING_SNAKE_CASE							,	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


'''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() = }""")



