
from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class  lowercase__(				UpperCAmelCase							):



	"""simple docstring"""




	a			:UNetaDModel
	a			:KarrasVeScheduler
	def __init__(       self  :			int       ,							SCREAMING_SNAKE_CASE_  :			UNetaDModel       ,							SCREAMING_SNAKE_CASE_  :			KarrasVeScheduler       )       ->     List[str]:
					super().__init__()
					self.register_modules(unet=SCREAMING_SNAKE_CASE_       ,							scheduler=SCREAMING_SNAKE_CASE_       )




	@torch.no_grad()
	def __call__(       self  :			List[str]       ,							SCREAMING_SNAKE_CASE_  :			int = 1       ,							SCREAMING_SNAKE_CASE_  :			int = 5_0       ,							SCREAMING_SNAKE_CASE_  :			Optional[Union[torch.Generator, List[torch.Generator]]] = None       ,							SCREAMING_SNAKE_CASE_  :			Optional[str] = "pil"       ,							SCREAMING_SNAKE_CASE_  :			bool = True       ,							**SCREAMING_SNAKE_CASE_  :			int       ,							)       ->     Union[Tuple, ImagePipelineOutput]:
					lowercase_       =					self.unet.config.sample_size
					lowercase_       =					(batch_size, 3, img_size, img_size)

					lowercase_       =					self.unet

					# sample x_0 ~ N(0, sigma_0^2 * I)
					lowercase_       =					randn_tensor(SCREAMING_SNAKE_CASE_       ,							generator=SCREAMING_SNAKE_CASE_       ,							device=self.device       ) * self.scheduler.init_noise_sigma

					self.scheduler.set_timesteps(SCREAMING_SNAKE_CASE_       )

					for t in self.progress_bar(self.scheduler.timesteps       ):
									# here sigma_t == t_i from the paper
									lowercase_       =					self.scheduler.schedule[t]
									lowercase_       =					self.scheduler.schedule[t - 1] if t > 0 else 0

									# 1. Select temporarily increased noise level sigma_hat
									# 2. Add new noise to move from sample_i to sample_hat
									lowercase_  ,	lowercase_       =					self.scheduler.add_noise_to_input(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							generator=SCREAMING_SNAKE_CASE_       )

									# 3. Predict the noise residual given the noise magnitude `sigma_hat`
									# The model inputs and output are adjusted by following eq. (213) in [1].
									lowercase_       =					(sigma_hat / 2) * model((sample_hat + 1) / 2       ,							sigma_hat / 2       ).sample

									# 4. Evaluate dx/dt at sigma_hat
									# 5. Take Euler step from sigma to sigma_prev
									lowercase_       =					self.scheduler.step(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       )

									if sigma_prev != 0:
													# 6. Apply 2nd order correction
													# The model inputs and output are adjusted by following eq. (213) in [1].
													lowercase_       =					(sigma_prev / 2) * model((step_output.prev_sample + 1) / 2       ,							sigma_prev / 2       ).sample
													lowercase_       =					self.scheduler.step_correct(
													    SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ,							step_output.prev_sample       ,							step_output['''derivative''']       ,							)
									lowercase_       =					step_output.prev_sample

					lowercase_       =					(sample / 2 + 0.5).clamp(0       ,							1       )
					lowercase_       =					sample.cpu().permute(0       ,							2       ,							3       ,							1       ).numpy()
					if output_type == "pil":
									lowercase_       =					self.numpy_to_pil(SCREAMING_SNAKE_CASE_       )

					if not return_dict:
									return (image,)

					return ImagePipelineOutput(images=SCREAMING_SNAKE_CASE_       )






from __future__ import annotations

from collections.abc import MutableSequence
class  lowercase__:



	"""simple docstring"""




	def __init__(       self  :			Optional[Any]       ,							SCREAMING_SNAKE_CASE_  :			int       ,							SCREAMING_SNAKE_CASE_  :			MutableSequence[float]       )       ->     None:
					if len(SCREAMING_SNAKE_CASE_       ) != degree + 1:
									raise ValueError(
									    '''The number of coefficients should be equal to the degree + 1.'''       )

					lowercase_       =					list(SCREAMING_SNAKE_CASE_       )
					lowercase_       =					degree
	def __add__(       self  :			Any       ,							SCREAMING_SNAKE_CASE_  :			Polynomial       )       ->     Polynomial:

					if self.degree > polynomial_a.degree:
									lowercase_       =					self.coefficients[:]
									for i in range(polynomial_a.degree + 1       ):
													coefficients[i] += polynomial_a.coefficients[i]
									return Polynomial(self.degree       ,							SCREAMING_SNAKE_CASE_       )
					else:
									lowercase_       =					polynomial_a.coefficients[:]
									for i in range(self.degree + 1       ):
													coefficients[i] += self.coefficients[i]
									return Polynomial(polynomial_a.degree       ,							SCREAMING_SNAKE_CASE_       )
	def __sub__(       self  :			str       ,							SCREAMING_SNAKE_CASE_  :			Polynomial       )       ->     Polynomial:
					return self + polynomial_a * Polynomial(0       ,							[-1]       )
	def __neg__(       self  :			int       )       ->     Polynomial:
					return Polynomial(self.degree       ,							[-c for c in self.coefficients]       )
	def __mul__(       self  :			Any       ,							SCREAMING_SNAKE_CASE_  :			Polynomial       )       ->     Polynomial:
					lowercase_       =					[0] * (self.degree + polynomial_a.degree + 1)
					for i in range(self.degree + 1       ):
									for j in range(polynomial_a.degree + 1       ):
													coefficients[i + j] += (
													    self.coefficients[i] * polynomial_a.coefficients[j]
													)

					return Polynomial(self.degree + polynomial_a.degree       ,							SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			Dict       ,							SCREAMING_SNAKE_CASE_  :			int | float       )       ->     int | float:
					lowercase_       =					0
					for i in range(self.degree + 1       ):
									result += self.coefficients[i] * (substitution**i)
					return result
	def __str__(       self  :			Tuple       )       ->     str:
					lowercase_       =					''''''
					for i in range(self.degree       ,							-1       ,							-1       ):
									if self.coefficients[i] == 0:
													continue
									elif self.coefficients[i] > 0:
													if polynomial:
																	polynomial += " + "
									else:
													polynomial += " - "

									if i == 0:
													polynomial += str(abs(self.coefficients[i]       )       )
									elif i == 1:
													polynomial += str(abs(self.coefficients[i]       )       ) + "x"
									else:
													polynomial += str(abs(self.coefficients[i]       )       ) + "x^" + str(SCREAMING_SNAKE_CASE_       )

					return polynomial
	def __repr__(       self  :			Optional[Any]       )       ->     str:
					return self.__str__()
	def 						_lowercase  (       self  :			int       )       ->     Polynomial:
					lowercase_       =					[0] * self.degree
					for i in range(self.degree       ):
									lowercase_       =					self.coefficients[i + 1] * (i + 1)
					return Polynomial(self.degree - 1       ,							SCREAMING_SNAKE_CASE_       )
	def 						_lowercase  (       self  :			List[str]       ,							SCREAMING_SNAKE_CASE_  :			int | float = 0       )       ->     Polynomial:
					lowercase_       =					[0] * (self.degree + 2)
					lowercase_       =					constant
					for i in range(self.degree + 1       ):
									lowercase_       =					self.coefficients[i] / (i + 1)
					return Polynomial(self.degree + 1       ,							SCREAMING_SNAKE_CASE_       )
	def __eq__(       self  :			str       ,							SCREAMING_SNAKE_CASE_  :			object       )       ->     bool:
					if not isinstance(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_       ):
									return False

					if self.degree != polynomial_a.degree:
									return False

					for i in range(self.degree + 1       ):
									if self.coefficients[i] != polynomial_a.coefficients[i]:
													return False

					return True




	def __ne__(       self  :			List[str]       ,							SCREAMING_SNAKE_CASE_  :			object       )       ->     bool:
					return not self.__eq__(SCREAMING_SNAKE_CASE_       )




