



"""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       SCREAMING_SNAKE_CASE__  (					unittest.TestCase ):

   @property
   def 	SCREAMING_SNAKE_CASE     (   self						)  ->      Union[str, Any]:





    '''simple docstring'''




    return (
        "CUDAExecutionProvider",
        {
            "gpu_mem_limit": "15000000000",  # 15GB
            "arena_extend_strategy": "kSameAsRequested",
        },
    )

   @property
   def 	SCREAMING_SNAKE_CASE     (   self						)  ->      Optional[int]:





    '''simple docstring'''




    UpperCAmelCase	:					Optional[int]	=	ort.SessionOptions()
    UpperCAmelCase	:					Dict	=	False
    return options




   def 	SCREAMING_SNAKE_CASE     (   self						)  ->      Optional[int]:





    '''simple docstring'''




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

    UpperCAmelCase	:					Union[str, Any]	=	"""A red cat sitting on a park bench"""

    UpperCAmelCase	:					str	=	np.random.RandomState(0						)
    UpperCAmelCase	:					Any	=	pipe(
        prompt=_SCREAMING_SNAKE_CASE      ,     image=_SCREAMING_SNAKE_CASE      ,     mask_image=_SCREAMING_SNAKE_CASE      ,     strength=0.75      ,     guidance_scale=7.5      ,     num_inference_steps=15      ,     generator=_SCREAMING_SNAKE_CASE      ,     output_type="""np"""      ,     )

    UpperCAmelCase	:					Optional[int]	=	output.images[0]

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





"""simple docstring"""
from __future__ import annotations



class       SCREAMING_SNAKE_CASE__  :

   def __init__(   self      ,     _SCREAMING_SNAKE_CASE						)  ->      None:





    '''simple docstring'''




    UpperCAmelCase	:					Any	=	data
    UpperCAmelCase	:					Node | None	=	None
    UpperCAmelCase	:					Node | None	=	None

def       _snake_case						(						UpperCamelCase						:		Node | None						):  # In Order traversal of the tree
 if tree:
  display(tree.left						)
  print(tree.data						)
  display(tree.right						)

def       _snake_case						(						UpperCamelCase						:		Node | None						):
 return 1 + max(depth_of_tree(tree.left						)			,		depth_of_tree(tree.right						)						) if tree else 0

def       _snake_case						(						UpperCamelCase						:		Node						):
 if not tree:
  return True
 if tree.left and tree.right:
  return is_full_binary_tree(tree.left						) and is_full_binary_tree(tree.right						)
 else:
  return not tree.left and not tree.right

def       _snake_case						(						):  # Main function for testing.
 UpperCAmelCase	:					int	=	Node(1						)
 UpperCAmelCase	:					Tuple	=	Node(2						)
 UpperCAmelCase	:					Any	=	Node(3						)
 UpperCAmelCase	:					Optional[int]	=	Node(4						)
 UpperCAmelCase	:					Any	=	Node(5						)
 UpperCAmelCase	:					Optional[int]	=	Node(6						)
 UpperCAmelCase	:					int	=	Node(7						)
 UpperCAmelCase	:					str	=	Node(8						)
 UpperCAmelCase	:					str	=	Node(9						)

 print(is_full_binary_tree(UpperCamelCase						)						)
 print(depth_of_tree(UpperCamelCase						)						)
 print("""Tree is: """						)
 display(UpperCamelCase						)


if __name__ == "__main__":
      main()
