



'''simple docstring'''


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 					SCREAMING_SNAKE_CASE					(    lowercase__  ,		unittest.TestCase						):






    """simple docstring"""





    pass

@nightly
@require_onnxruntime
@require_torch_gpu
class 					SCREAMING_SNAKE_CASE					(    unittest.TestCase						):






    """simple docstring"""





    @property
    def 					A			(    self :   str					):


       """simple docstring"""







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






    @property
    def 					A			(    self :   Optional[int]					):


       """simple docstring"""







       UpperCamelCase      							=    ort.SessionOptions()
       UpperCamelCase      							=    False
       return options






    def 					A			(    self :   Dict					):


       """simple docstring"""







       UpperCamelCase      							=    load_image(
           'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
           '/in_paint/overture-creations-5sI6fQgYIuo.png'					)
       UpperCamelCase      							=    load_image(
           'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
           '/in_paint/overture-creations-5sI6fQgYIuo_mask.png'					)
       UpperCamelCase      							=    OnnxStableDiffusionInpaintPipeline.from_pretrained(
           'runwayml/stable-diffusion-inpainting'    ,		revision='onnx'    ,		safety_checker=lowercase_    ,		feature_extractor=lowercase_    ,		provider=self.gpu_provider    ,		sess_options=self.gpu_options    ,		)
       pipe.set_progress_bar_config(disable=lowercase_					)

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

       UpperCamelCase      							=    np.random.RandomState(0					)
       UpperCamelCase      							=    pipe(
           prompt=lowercase_    ,		image=lowercase_    ,		mask_image=lowercase_    ,		guidance_scale=7.5    ,		num_inference_steps=1_0    ,		generator=lowercase_    ,		output_type='np'    ,		)
       UpperCamelCase      							=    output.images
       UpperCamelCase      							=    images[0, 2_5_5:2_5_8, 2_5_5:2_5_8, -1]

       assert images.shape == (1, 5_1_2, 5_1_2, 3)
       UpperCamelCase      							=    np.array([0.2_5_1_4, 0.3_0_0_7, 0.3_5_1_7, 0.1_7_9_0, 0.2_3_8_2, 0.3_1_6_7, 0.1_9_4_4, 0.2_2_7_3, 0.2_4_6_4]					)

       assert np.abs(image_slice.flatten() - expected_slice					).max() < 1E-3






    def 					A			(    self :   int					):


       """simple docstring"""







       UpperCamelCase      							=    load_image(
           'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
           '/in_paint/overture-creations-5sI6fQgYIuo.png'					)
       UpperCamelCase      							=    load_image(
           'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
           '/in_paint/overture-creations-5sI6fQgYIuo_mask.png'					)
       UpperCamelCase      							=    LMSDiscreteScheduler.from_pretrained(
           'runwayml/stable-diffusion-inpainting'    ,		subfolder='scheduler'    ,		revision='onnx'					)
       UpperCamelCase      							=    OnnxStableDiffusionInpaintPipeline.from_pretrained(
           'runwayml/stable-diffusion-inpainting'    ,		revision='onnx'    ,		scheduler=lowercase_    ,		safety_checker=lowercase_    ,		feature_extractor=lowercase_    ,		provider=self.gpu_provider    ,		sess_options=self.gpu_options    ,		)
       pipe.set_progress_bar_config(disable=lowercase_					)

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

       UpperCamelCase      							=    np.random.RandomState(0					)
       UpperCamelCase      							=    pipe(
           prompt=lowercase_    ,		image=lowercase_    ,		mask_image=lowercase_    ,		guidance_scale=7.5    ,		num_inference_steps=2_0    ,		generator=lowercase_    ,		output_type='np'    ,		)
       UpperCamelCase      							=    output.images
       UpperCamelCase      							=    images[0, 2_5_5:2_5_8, 2_5_5:2_5_8, -1]

       assert images.shape == (1, 5_1_2, 5_1_2, 3)
       UpperCamelCase      							=    np.array([0.0_0_8_6, 0.0_0_7_7, 0.0_0_8_3, 0.0_0_9_3, 0.0_1_0_7, 0.0_1_3_9, 0.0_0_9_4, 0.0_0_9_7, 0.0_1_2_5]					)

       assert np.abs(image_slice.flatten() - expected_slice					).max() < 1E-3





from manim import *




class       lowercase_					(lowercase__   ):





				def 						__UpperCamelCase    (				self)  -> List[Any]:
											a__      =Rectangle(height=0.5       ,  width=0.5)
											a__      =Rectangle(height=0.46       ,  width=0.46).set_stroke(width=0)

											a__      =[mem.copy() for i in range(6)]
											a__      =[mem.copy() for i in range(6)]
											a__      =VGroup(*lowercase_).arrange(lowercase_       ,  buff=0)
											a__      =VGroup(*lowercase_).arrange(lowercase_       ,  buff=0)
											a__      =VGroup(lowercase_       ,  lowercase_).arrange(lowercase_       ,  buff=0)
											a__      =Text('CPU'       ,  font_size=24)
											a__      =Group(lowercase_       ,  lowercase_).arrange(lowercase_       ,  buff=0.5       ,  aligned_edge=lowercase_)
											cpu.move_to([-2.5, -0.5, 0])
											self.add(lowercase_)

											a__      =[mem.copy() for i in range(4)]
											a__      =VGroup(*lowercase_).arrange(lowercase_       ,  buff=0)
											a__      =Text('GPU'       ,  font_size=24)
											a__      =Group(lowercase_       ,  lowercase_).arrange(lowercase_       ,  buff=0.5       ,  aligned_edge=lowercase_)
											gpu.move_to([-1, -1, 0])
											self.add(lowercase_)

											a__      =[mem.copy() for i in range(6)]
											a__      =VGroup(*lowercase_).arrange(lowercase_       ,  buff=0)

											a__      =Text('Model'       ,  font_size=24)
											a__      =Group(lowercase_       ,  lowercase_).arrange(lowercase_       ,  buff=0.5       ,  aligned_edge=lowercase_)
											model.move_to([3, -1.0, 0])
											self.add(lowercase_)

											a__      =[]
											for i, rect in enumerate(lowercase_):
																		rect.set_stroke(lowercase_)
																		# target = fill.copy().set_fill(YELLOW, opacity=0.7)
																		# target.move_to(rect)
																		# self.add(target)

																		a__      =Rectangle(height=0.46 / 4       ,  width=0.46 / 3).set_stroke(width=0.0).set_fill(lowercase_       ,  opacity=0.7)

																		if i == 0:
																									cpu_target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT)       ,  buff=0.02       ,  direction=lowercase_)
																									cpu_target.set_x(cpu_target.get_x() + 0.1)
																		elif i == 3:
																									cpu_target.next_to(cpu_targs[0]       ,  direction=lowercase_       ,  buff=0.0)
																		else:
																									cpu_target.next_to(cpu_targs[i - 1]       ,  direction=lowercase_       ,  buff=0.0)
																		self.add(lowercase_)
																		cpu_targs.append(lowercase_)

											a__      =[mem.copy() for i in range(6)]
											a__      =VGroup(*lowercase_).arrange(lowercase_       ,  buff=0)

											a__      =Text('Loaded Checkpoint'       ,  font_size=24)
											a__      =Group(lowercase_       ,  lowercase_).arrange(lowercase_       ,  aligned_edge=lowercase_       ,  buff=0.4)
											checkpoint.move_to([3, 0.5, 0])

											a__      =Square(side_length=2.2)
											key.move_to([-5, 2, 0])

											a__      =MarkupText(
											    F"""<b>Key:</b>\n\n<span fgcolor='{YELLOW}'>●</span> Empty Model"""       ,  font_size=18       ,  )

											key_text.move_to([-5, 2.4, 0])

											self.add(lowercase_       ,  lowercase_)

											a__      =MarkupText(
											    F"""<span fgcolor='{BLUE}'>●</span> Checkpoint"""       ,  font_size=18       ,  )

											blue_text.next_to(lowercase_       ,  DOWN * 2.4       ,  aligned_edge=key_text.get_left())

											a__      =MarkupText(
											    F"""Next, a <i><span fgcolor=\"{BLUE}\">second</span></i> model is loaded into memory,\nwith the weights of a <span fgcolor=\"{BLUE}\">single shard</span>."""       ,  font_size=24       ,  )
											step_a.move_to([2, 2, 0])
											self.play(Write(lowercase_)       ,  Write(lowercase_))

											self.play(Write(lowercase_       ,  run_time=1)       ,  Create(lowercase_       ,  run_time=1))

											a__      =[]
											a__      =[]
											for i, rect in enumerate(lowercase_):
																		a__      =fill.copy().set_fill(lowercase_       ,  opacity=0.7)
																		target.move_to(lowercase_)
																		first_animations.append(GrowFromCenter(lowercase_       ,  run_time=1))

																		a__      =target.copy()
																		cpu_target.generate_target()
																		if i < 5:
																									cpu_target.target.move_to(cpu_left_col_base[i + 1])
																		else:
																									cpu_target.target.move_to(cpu_right_col_base[i - 5])
																		second_animations.append(MoveToTarget(lowercase_       ,  run_time=1.5))

											self.play(*lowercase_)
											self.play(*lowercase_)
											self.wait()

