





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        __SCREAMING_SNAKE_CASE					(     _a   ,		_a   ,		unittest.TestCase       ):
							snake_case     :      List[Any]						     =       IFInpaintingSuperResolutionPipeline
							snake_case     :      Dict						     =       TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"""width""", """height"""}
							snake_case     :      str						     =       TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS.union({"""original_image"""}       )
							snake_case     :      Optional[int]						     =       PipelineTesterMixin.required_optional_params - {"""latents"""}






							def 				_lowerCamelCase		(						self  ):
														return self._get_superresolution_dummy_components()






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase=0  ):
														if str(__lowerCAmelCase  ).startswith("""mps"""  ):
																					UpperCamelCase__				     =			torch.manual_seed(__lowerCAmelCase  )
														else:
																					UpperCamelCase__				     =			torch.Generator(device=__lowerCAmelCase  ).manual_seed(__lowerCAmelCase  )

														UpperCamelCase__				     =			floats_tensor((1, 3, 16, 16)  , rng=random.Random(__lowerCAmelCase  )  ).to(__lowerCAmelCase  )
														UpperCamelCase__				     =			floats_tensor((1, 3, 32, 32)  , rng=random.Random(__lowerCAmelCase  )  ).to(__lowerCAmelCase  )
														UpperCamelCase__				     =			floats_tensor((1, 3, 32, 32)  , rng=random.Random(__lowerCAmelCase  )  ).to(__lowerCAmelCase  )

														UpperCamelCase__				     =			{
														    """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 				_lowerCamelCase		(						self  ):
														self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1E-3  )






							def 				_lowerCamelCase		(						self  ):
														self._test_save_load_optional_components()






							@unittest.skipIf(torch_device != """cuda"""  , reason="""float16 requires CUDA"""  )
							def 				_lowerCamelCase		(						self  ):
														# Due to non-determinism in save load of the hf-internal-testing/tiny-random-t5 text encoder
														super().test_save_load_floataa(expected_max_diff=1E-1  )






							def 				_lowerCamelCase		(						self  ):
														self._test_attention_slicing_forward_pass(expected_max_diff=1E-2  )






							def 				_lowerCamelCase		(						self  ):
														self._test_save_load_local()







							def 				_lowerCamelCase		(						self  ):
														self._test_inference_batch_single_identical(
														    expected_max_diff=1E-2  , )











from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any

@dataclass
class        __SCREAMING_SNAKE_CASE					:
							snake_case     :      int
							snake_case     :      Node | None						     =       None
							snake_case     :      Node | None						     =       None






def     _UpperCamelCase     ():






							"""simple docstring"""





							UpperCamelCase__				     =			Node(1       )
							UpperCamelCase__				     =			Node(2       )
							UpperCamelCase__				     =			Node(3       )
							UpperCamelCase__				     =			Node(4       )
							UpperCamelCase__				     =			Node(5       )
							return tree





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							return [root.data, *preorder(root.left       ), *preorder(root.right       )] if root else []





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							return postorder(root.left       ) + postorder(root.right       ) + [root.data] if root else []





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							return [*inorder(root.left       ), root.data, *inorder(root.right       )] if root else []





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							return (max(height(root.left       )   ,			height(root.right       )       ) + 1) if root else 0





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]

							if root is None:
														return output

							UpperCamelCase__				     =			deque([root]       )

							while process_queue:
														UpperCamelCase__				     =			process_queue.popleft()
														output.append(node.data       )

														if node.left:
																					process_queue.append(node.left       )
														if node.right:
																					process_queue.append(node.right       )
							return output





def     _UpperCamelCase     (a__   :Node | None   ,			a__   :int       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]

							def populate_output(a__   :Node | None   ,			a__   :int       ) -> None:
														if not root:
																					return
														if level == 1:
																					output.append(root.data       )
														elif level > 1:
																					populate_output(root.left   ,			level - 1       )
																					populate_output(root.right   ,			level - 1       )

							populate_output(a__   ,			a__       )
							return output





def     _UpperCamelCase     (a__   :Node | None   ,			a__   :int       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]

							def populate_output(a__   :Node | None   ,			a__   :int       ) -> None:
														if root is None:
																					return
														if level == 1:
																					output.append(root.data       )
														elif level > 1:
																					populate_output(root.right   ,			level - 1       )
																					populate_output(root.left   ,			level - 1       )

							populate_output(a__   ,			a__       )
							return output





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							if root is None:
														return []

							UpperCamelCase__				     =			[]

							UpperCamelCase__				     =			0
							UpperCamelCase__				     =			height(a__       )

							for h in range(1   ,			height_tree + 1       ):
														if not flag:
																					output.append(get_nodes_from_left_to_right(a__   ,			a__       )       )
																					UpperCamelCase__				     =			1
														else:
																					output.append(get_nodes_from_right_to_left(a__   ,			a__       )       )
																					UpperCamelCase__				     =			0

							return output





def     _UpperCamelCase     ():  # Main function for testing.






							"""simple docstring"""





							UpperCamelCase__				     =			make_tree()
							print(f"""In-order Traversal: {inorder(a__       )}"""       )
							print(f"""Pre-order Traversal: {preorder(a__       )}"""       )
							print(f"""Post-order Traversal: {postorder(a__       )}"""   ,			"""\n"""       )

							print(f"""Height of Tree: {height(a__       )}"""   ,			"""\n"""       )

							print("""Complete Level Order Traversal: """       )
							print(level_order(a__       )   ,			"""\n"""       )

							print("""Level-wise order Traversal: """       )

							for level in range(1   ,			height(a__       ) + 1       ):
														print(f"""Level {level}:"""   ,			get_nodes_from_left_to_right(a__   ,			level=a__       )       )

							print("""\nZigZag order Traversal: """       )
							print(zigzag(a__       )       )


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					main()




