






'''simple docstring'''
from typing import List, Optional, Tuple, Union

import torch

from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput


class    _snake_case   (				snake_case					):

					"""simple docstring"""





					def __init__(     self   , UpperCAmelCase__   , UpperCAmelCase__     )      ->	List[Any]:
										super().__init__()
										self.register_modules(unet=UpperCAmelCase__   , scheduler=UpperCAmelCase__     )




					@torch.no_grad()
					def __call__(     self   , UpperCAmelCase__ = 1   , UpperCAmelCase__ = None   , UpperCAmelCase__ = 1000   , UpperCAmelCase__ = "pil"   , UpperCAmelCase__ = True   , )      ->	Union[ImagePipelineOutput, Tuple]:
										# Sample gaussian noise to begin loop
										if isinstance(self.unet.config.sample_size   , UpperCAmelCase__     ):
															a_									=   (
															    batch_size,
															    self.unet.config.in_channels,
															    self.unet.config.sample_size,
															    self.unet.config.sample_size,
															)
										else:
															a_									=   (batch_size, self.unet.config.in_channels, *self.unet.config.sample_size)

										if self.device.type == "mps":
															# randn does not work reproducibly on mps
															a_									=   randn_tensor(UpperCAmelCase__   , generator=UpperCAmelCase__     )
															a_									=   image.to(self.device     )
										else:
															a_									=   randn_tensor(UpperCAmelCase__   , generator=UpperCAmelCase__   , device=self.device     )

										# set step values
										self.scheduler.set_timesteps(UpperCAmelCase__     )

										for t in self.progress_bar(self.scheduler.timesteps     ):
															# 1. predict noise model_output
															a_									=   self.unet(UpperCAmelCase__   , UpperCAmelCase__     ).sample

															# 2. compute previous image: x_t -> x_t-1
															a_									=   self.scheduler.step(UpperCAmelCase__   , UpperCAmelCase__   , UpperCAmelCase__   , generator=UpperCAmelCase__     ).prev_sample

										a_									=   (image / 2 + 0.5).clamp(0   , 1     )
										a_									=   image.cpu().permute(0   , 2   , 3   , 1     ).numpy()
										if output_type == "pil":
															a_									=   self.numpy_to_pil(UpperCAmelCase__     )

										if not return_dict:
															return (image,)

										return ImagePipelineOutput(images=UpperCAmelCase__     )









'''simple docstring'''
def 							a	(   _UpperCAmelCase					,  _UpperCAmelCase					,  _UpperCAmelCase )				->				list[int]:






					"""simple docstring"""







					if hue < 0 or hue > 3_6_0:
										raise Exception('hue should be between 0 and 360' )

					if saturation < 0 or saturation > 1:
										raise Exception('saturation should be between 0 and 1' )

					if value < 0 or value > 1:
										raise Exception('value should be between 0 and 1' )

					a_									=   value * saturation
					a_									=   hue / 6_0
					a_									=   chroma * (1 - abs(hue_section % 2 - 1 ))
					a_									=   value - chroma

					if hue_section >= 0 and hue_section <= 1:
										a_									=   round(2_5_5 * (chroma + match_value) )
										a_									=   round(2_5_5 * (second_largest_component + match_value) )
										a_									=   round(2_5_5 * (match_value) )
					elif hue_section > 1 and hue_section <= 2:
										a_									=   round(2_5_5 * (second_largest_component + match_value) )
										a_									=   round(2_5_5 * (chroma + match_value) )
										a_									=   round(2_5_5 * (match_value) )
					elif hue_section > 2 and hue_section <= 3:
										a_									=   round(2_5_5 * (match_value) )
										a_									=   round(2_5_5 * (chroma + match_value) )
										a_									=   round(2_5_5 * (second_largest_component + match_value) )
					elif hue_section > 3 and hue_section <= 4:
										a_									=   round(2_5_5 * (match_value) )
										a_									=   round(2_5_5 * (second_largest_component + match_value) )
										a_									=   round(2_5_5 * (chroma + match_value) )
					elif hue_section > 4 and hue_section <= 5:
										a_									=   round(2_5_5 * (second_largest_component + match_value) )
										a_									=   round(2_5_5 * (match_value) )
										a_									=   round(2_5_5 * (chroma + match_value) )
					else:
										a_									=   round(2_5_5 * (chroma + match_value) )
										a_									=   round(2_5_5 * (match_value) )
										a_									=   round(2_5_5 * (second_largest_component + match_value) )

					return [red, green, blue]

def 							a	(   _UpperCAmelCase					,  _UpperCAmelCase					,  _UpperCAmelCase )				->				list[float]:






					"""simple docstring"""







					if red < 0 or red > 2_5_5:
										raise Exception('red should be between 0 and 255' )

					if green < 0 or green > 2_5_5:
										raise Exception('green should be between 0 and 255' )

					if blue < 0 or blue > 2_5_5:
										raise Exception('blue should be between 0 and 255' )

					a_									=   red / 2_5_5
					a_									=   green / 2_5_5
					a_									=   blue / 2_5_5
					a_									=   max(_UpperCAmelCase					,  _UpperCAmelCase					,  _UpperCAmelCase )
					a_									=   value - min(_UpperCAmelCase					,  _UpperCAmelCase					,  _UpperCAmelCase )
					a_									=   0 if value == 0 else chroma / value

					if chroma == 0:
										a_									=   0.0
					elif value == float_red:
										a_									=   6_0 * (0 + (float_green - float_blue) / chroma)
					elif value == float_green:
										a_									=   6_0 * (2 + (float_blue - float_red) / chroma)
					else:
										a_									=   6_0 * (4 + (float_red - float_green) / chroma)

					a_									=   (hue + 3_6_0) % 3_6_0

					return [hue, saturation, value]





def 							a	(   _UpperCAmelCase					,  _UpperCAmelCase )				->				bool:






					"""simple docstring"""







					a_									=   abs(hsv_a[0] - hsv_a[0] ) < 0.2
					a_									=   abs(hsv_a[1] - hsv_a[1] ) < 0.0_0_2
					a_									=   abs(hsv_a[2] - hsv_a[2] ) < 0.0_0_2

					return check_hue and check_saturation and check_value

