


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






class        _a							:

							def __init__(							self:	Any							)			->   Tuple:





									"""simple docstring"""







									lowercase__            =      ''''''
									lowercase__            =      ''''''
									lowercase__            =      []

							def       lowerCamelCase_ (							self:	Union[str, Any]    ,						UpperCamelCase_:	int    ,						UpperCamelCase_:	int							)			->   int:





									"""simple docstring"""







									if m == -1:
											return n + 1
									elif n == -1:
											return m + 1
									elif self.dp[m][n] > -1:
											return self.dp[m][n]
									else:
											if self.worda[m] == self.worda[n]:
													lowercase__            =      self.__min_dist_top_down_dp(m - 1    ,						n - 1							)
											else:
													lowercase__            =      self.__min_dist_top_down_dp(UpperCamelCase_    ,						n - 1							)
													lowercase__            =      self.__min_dist_top_down_dp(m - 1    ,						UpperCamelCase_							)
													lowercase__            =      self.__min_dist_top_down_dp(m - 1    ,						n - 1							)
													lowercase__            =      1 + min(UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_							)

											return self.dp[m][n]

							def       lowerCamelCase_ (							self:	Union[str, Any]    ,						UpperCamelCase_:	str    ,						UpperCamelCase_:	str							)			->   int:





									"""simple docstring"""







									lowercase__            =      worda
									lowercase__            =      worda
									lowercase__            =      [[-1 for _ in range(len(UpperCamelCase_							)							)] for _ in range(len(UpperCamelCase_							)							)]

									return self.__min_dist_top_down_dp(len(UpperCamelCase_							) - 1    ,						len(UpperCamelCase_							) - 1							)


							def       lowerCamelCase_ (							self:	int    ,						UpperCamelCase_:	str    ,						UpperCamelCase_:	str							)			->   int:





									"""simple docstring"""







									lowercase__            =      worda
									lowercase__            =      worda
									lowercase__            =      len(UpperCamelCase_							)
									lowercase__            =      len(UpperCamelCase_							)
									lowercase__            =      [[0 for _ in range(n + 1							)] for _ in range(m + 1							)]

									for i in range(m + 1							):
											for j in range(n + 1							):
													if i == 0:  # first string is empty
															lowercase__            =      j
													elif j == 0:  # second string is empty
															lowercase__            =      i
													elif worda[i - 1] == worda[j - 1]:  # last characters are equal
															lowercase__            =      self.dp[i - 1][j - 1]
													else:
															lowercase__            =      self.dp[i][j - 1]
															lowercase__            =      self.dp[i - 1][j]
															lowercase__            =      self.dp[i - 1][j - 1]
															lowercase__            =      1 + min(UpperCamelCase_    ,						UpperCamelCase_    ,						UpperCamelCase_							)
									return self.dp[m][n]


if __name__ == "__main__":
			lowerCAmelCase       =							EditDistance()

			print('****************** Testing Edit Distance DP Algorithm ******************')
			print()

			lowerCAmelCase       =							input('Enter the first string: ').strip()
			lowerCAmelCase       =							input('Enter the second string: ').strip()

			print()
			print(f"""The minimum edit distance is: {solver.min_dist_top_down(Sa, Sa)}""")
			print(f"""The minimum edit distance is: {solver.min_dist_bottom_up(Sa, Sa)}""")
			print()
			print('*************** End of Testing Edit Distance DP Algorithm ***************')


