




"""simple docstring"""







import random
import unittest

import torch

from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin




@skip_mps
class       lowerCAmelCase__       (			lowerCAmelCase_  ,			lowerCAmelCase_  ,			unittest.TestCase    ):


				"""simple docstring"""





				__UpperCAmelCase :     Dict       =      IFInpaintingSuperResolutionPipeline
				__UpperCAmelCase :     int       =      TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"width", "height"}
				__UpperCAmelCase :     Union[str, Any]       =      TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS.union({"original_image"}    )
				__UpperCAmelCase :     Union[str, Any]       =      PipelineTesterMixin.required_optional_params - {"latents"}



				def       snake_case    (     self					:	int						):
						return self._get_superresolution_dummy_components()



				def       snake_case    (     self					:	Union[str, Any]    ,   lowercase__					:	Union[str, Any]    ,   lowercase__					:	Optional[int]=0						):





						if str(UpperCamelCase__						).startswith("mps"						):
								__lowercase				:		Any												=				torch.manual_seed(UpperCamelCase__						)
						else:
								__lowercase				:		List[str]												=				torch.Generator(device=UpperCamelCase__						).manual_seed(UpperCamelCase__						)

						__lowercase				:		Tuple												=				floats_tensor((1, 3, 1_6, 1_6)    ,   rng=random.Random(UpperCamelCase__						)						).to(UpperCamelCase__						)
						__lowercase				:		Optional[int]												=				floats_tensor((1, 3, 3_2, 3_2)    ,   rng=random.Random(UpperCamelCase__						)						).to(UpperCamelCase__						)
						__lowercase				:		Any												=				floats_tensor((1, 3, 3_2, 3_2)    ,   rng=random.Random(UpperCamelCase__						)						).to(UpperCamelCase__						)

						__lowercase				:		str												=				{
						    "prompt": "A painting of a squirrel eating a burger",
						    "image": image,
						    "original_image": original_image,
						    "mask_image": mask_image,
						    "generator": generator,
						    "num_inference_steps": 2,
						    "output_type": "numpy",
						}

						return inputs



				@unittest.skipIf(
				    torch_device != "cuda" or not is_xformers_available()    ,   reason="XFormers attention is only available with CUDA and `xformers` installed"    ,   )
				def       snake_case    (     self					:	int						):
						self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3						)



				def       snake_case    (     self					:	Any						):
						self._test_save_load_optional_components()



				@unittest.skipIf(torch_device != "cuda"    ,   reason="float16 requires CUDA"						)
				def       snake_case    (     self					:	Optional[Any]						):
						super().test_save_load_floataa(expected_max_diff=1e-1						)



				def       snake_case    (     self					:	Optional[Any]						):
						self._test_attention_slicing_forward_pass(expected_max_diff=1e-2						)



				def       snake_case    (     self					:	Union[str, Any]						):
						self._test_save_load_local()



				def       snake_case    (     self					:	str						):
						self._test_inference_batch_single_identical(
						    expected_max_diff=1e-2    ,   )










"""simple docstring"""







class       lowerCAmelCase__       :


				"""simple docstring"""





				def __init__(     self					:	int    ,   lowercase__					:	List[Any]						):
						__lowercase				:		Tuple												=				val
						__lowercase				:		Optional[Any]												=				None
						__lowercase				:		Tuple												=				None



				def       snake_case    (     self					:	Optional[Any]    ,   lowercase__					:	List[str]						):
						if self.val:
								if val < self.val:
										if self.left is None:
												__lowercase				:		Tuple												=				Node(lowercase__						)
										else:
												self.left.insert(lowercase__						)
								elif val > self.val:
										if self.right is None:
												__lowercase				:		Any												=				Node(lowercase__						)
										else:
												self.right.insert(lowercase__						)
						else:
								__lowercase				:		Optional[Any]												=				val





def 						snake_case__       (					_lowerCamelCase,  _lowerCamelCase				)			->Any:






		"""simple docstring"""


		if root:
				inorder(root.left,  _lowerCamelCase				)
				res.append(root.val				)
				inorder(root.right,  _lowerCamelCase				)

def 						snake_case__       (					_lowerCamelCase				)			->Optional[Any]:






		"""simple docstring"""


		if len(_lowerCamelCase				) == 0:
				return arr
		__lowercase				:		int												=				Node(arr[0]				)
		for i in range(1,  len(_lowerCamelCase				)				):
				root.insert(arr[i]				)
		# Traverse BST in order.
		__lowercase				:		Tuple												=				[]
		inorder(_lowerCamelCase,  _lowerCamelCase				)
		return res


if __name__ == "__main__":
						print(tree_sort([1_0, 1, 3, 2, 9, 1_4, 1_3]))
