






"""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 		__lowerCamelCase				( unittest.TestCase			):





		'''simple docstring'''






		@property
		def    lowerCamelCase       (   self							:	Tuple	):
				return (
				    "CUDAExecutionProvider",
				    {
				        "gpu_mem_limit": "15000000000",  # 15GB
				        "arena_extend_strategy": "kSameAsRequested",
				    },
				)





		@property
		def    lowerCamelCase       (   self							:	List[str]	):
				lowerCAmelCase_   :							Optional[int]									=			ort.SessionOptions()
				lowerCAmelCase_   :							str									=			False
				return options





		def    lowerCamelCase       (   self							:	Optional[int]	):
				lowerCAmelCase_   :							Tuple									=			load_image(
				    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
				    "/in_paint/overture-creations-5sI6fQgYIuo.png"	)
				lowerCAmelCase_   :							Optional[int]									=			load_image(
				    "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main"
				    "/in_paint/overture-creations-5sI6fQgYIuo_mask.png"	)
				lowerCAmelCase_   :							List[Any]									=			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
				lowerCAmelCase_   :							List[Any]									=			OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
				    "CompVis/stable-diffusion-v1-4"						,			revision="onnx"						,			safety_checker=__UpperCAmelCase						,			feature_extractor=__UpperCAmelCase						,			provider=self.gpu_provider						,			sess_options=self.gpu_options						,			)
				pipe.set_progress_bar_config(disable=__UpperCAmelCase	)

				lowerCAmelCase_   :							int									=			"A red cat sitting on a park bench"

				lowerCAmelCase_   :							Optional[Any]									=			np.random.RandomState(0	)
				lowerCAmelCase_   :							Optional[Any]									=			pipe(
				    prompt=__UpperCAmelCase						,			image=__UpperCAmelCase						,			mask_image=__UpperCAmelCase						,			strength=0.75						,			guidance_scale=7.5						,			num_inference_steps=15						,			generator=__UpperCAmelCase						,			output_type="np"						,			)

				lowerCAmelCase_   :							str									=			output.images[0]

				assert image.shape == (5_12, 5_12, 3)
				assert np.abs(expected_image - image	).max() < 1e-2




"""simple docstring"""







class 						_A  :







    """simple docstring"""




    def __init__(					self				:    int				, __UpperCAmelCase				:    int):
      a						:		Tuple      							=			size
      a						:		Dict      							=			[0] * size
      a						:		Optional[int]      							=			[0] * size






    @staticmethod
    def 	__snake_case							(					__UpperCAmelCase				:    int):
      return index | (index + 1)






    @staticmethod
    def 	__snake_case							(					__UpperCAmelCase				:    int):
      return (index & (index + 1)) - 1






    def 	__snake_case							(					self				:    List[str]				, __UpperCAmelCase				:    int				, __UpperCAmelCase				:    int):
      a						:		Union[str, Any]      							=			value
      while index < self.size:
        a						:		Dict      							=			self.get_prev(__UpperCAmelCase) + 1
        if current_left_border == index:
          a						:		Optional[int]      							=			value
        else:
          a						:		Any      							=			max(__UpperCAmelCase				, __UpperCAmelCase				, __UpperCAmelCase)
        a						:		Optional[int]      							=			self.get_next(__UpperCAmelCase)






    def 	__snake_case							(					self				:    Union[str, Any]				, __UpperCAmelCase				:    int				, __UpperCAmelCase				:    int):
      right -= 1  # Because of right is exclusive
      a						:		List[str]      							=			0
      while left <= right:
        a						:		Dict      							=			self.get_prev(__UpperCAmelCase)
        if left <= current_left:
          a						:		Optional[int]      							=			max(__UpperCAmelCase				, self.tree[right])
          a						:		Optional[Any]      							=			current_left
        else:
          a						:		List[str]      							=			max(__UpperCAmelCase				, self.arr[right])
          right -= 1
      return result


if __name__ == "__main__":
 import doctest

 doctest.testmod()






