


"""simple docstring"""




from __future__ import annotations


def     lowercase			(SCREAMING_SNAKE_CASE_		:				str  )   ->						list[int]:
						return [ord(SCREAMING_SNAKE_CASE_  ) - 96 for elem in plain]


def     lowercase			(SCREAMING_SNAKE_CASE_		:				list[int]  )   ->						str:
						return "".join(chr(elem + 96  ) for elem in encoded  )


def     lowercase			()   ->						None:
						SCREAMING_SNAKE_CASE													=					encode(input('-> '  ).strip().lower()  )
						print('Encoded: ' ,			SCREAMING_SNAKE_CASE_  )
						print('Decoded:' ,			decode(SCREAMING_SNAKE_CASE_  )  )


if __name__ == "__main__":
	main()






"""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 							__A						(	self				)     ->							List[Any]:
								return (
								    "CUDAExecutionProvider",
								    {
								        "gpu_mem_limit": "15000000000",  # 15GB
								        "arena_extend_strategy": "kSameAsRequested",
								    },
								)







		@property
		def 							__A						(	self				)     ->							List[str]:
								SCREAMING_SNAKE_CASE													=					ort.SessionOptions()
								SCREAMING_SNAKE_CASE													=					False
								return options







		def 							__A						(	self				)     ->							Dict:
								SCREAMING_SNAKE_CASE													=					load_image(
								    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
								    '/in_paint/overture-creations-5sI6fQgYIuo.png'				)
								SCREAMING_SNAKE_CASE													=					load_image(
								    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
								    '/in_paint/overture-creations-5sI6fQgYIuo_mask.png'				)
								SCREAMING_SNAKE_CASE													=					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
								SCREAMING_SNAKE_CASE													=					OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
								    'CompVis/stable-diffusion-v1-4'						,       revision='onnx'						,       safety_checker=lowerCAmelCase__						,       feature_extractor=lowerCAmelCase__						,       provider=self.gpu_provider						,       sess_options=self.gpu_options						,       )
								pipe.set_progress_bar_config(disable=lowerCAmelCase__				)

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

								SCREAMING_SNAKE_CASE													=					np.random.RandomState(0				)
								SCREAMING_SNAKE_CASE													=					pipe(
								    prompt=lowerCAmelCase__						,       image=lowerCAmelCase__						,       mask_image=lowerCAmelCase__						,       strength=0.75						,       guidance_scale=7.5						,       num_inference_steps=15						,       generator=lowerCAmelCase__						,       output_type='np'						,       )

								SCREAMING_SNAKE_CASE													=					output.images[0]

								assert image.shape == (512, 512, 3)
								assert np.abs(expected_image - image				).max() < 1e-2


