


"""simple docstring"""



from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class 					__magic_name__		(			__UpperCAmelCase     ):
							__A			:      UNetaDModel
							__A			:      ScoreSdeVeScheduler






							def __init__(   self  :    Optional[Any]  ,     snake_case__  :    UNetaDModel  ,     snake_case__  :    ScoreSdeVeScheduler				):

														'''simple docstring'''






														super().__init__()
														self.register_modules(unet=snake_case__  ,     scheduler=snake_case__				)







							@torch.no_grad()
							def __call__(   self  :    Tuple  ,     snake_case__  :    int = 1  ,     snake_case__  :    int = 2_0_0_0  ,     snake_case__  :    Optional[Union[torch.Generator, List[torch.Generator]]] = None  ,     snake_case__  :    Optional[str] = "pil"  ,     snake_case__  :    bool = True  ,     **snake_case__  :    Optional[Any]  ,     ):

														'''simple docstring'''






														lowercase		:str       							=				self.unet.config.sample_size
														lowercase		:str       							=				(batch_size, 3, img_size, img_size)

														lowercase		:Any       							=				self.unet

														lowercase		:Dict       							=				randn_tensor(snake_case__  ,     generator=snake_case__				) * self.scheduler.init_noise_sigma
														lowercase		:int       							=				sample.to(self.device				)

														self.scheduler.set_timesteps(snake_case__				)
														self.scheduler.set_sigmas(snake_case__				)

														for i, t in enumerate(self.progress_bar(self.scheduler.timesteps				)				):
																					lowercase		:Optional[int]       							=				self.scheduler.sigmas[i] * torch.ones(shape[0]  ,     device=self.device				)

																					# correction step
																					for _ in range(self.scheduler.config.correct_steps				):
																												lowercase		:str       							=				self.unet(snake_case__  ,     snake_case__				).sample
																												lowercase		:Optional[Any]       							=				self.scheduler.step_correct(snake_case__  ,     snake_case__  ,     generator=snake_case__				).prev_sample

																					# prediction step
																					lowercase		:Optional[Any]       							=				model(snake_case__  ,     snake_case__				).sample
																					lowercase		:Dict       							=				self.scheduler.step_pred(snake_case__  ,     snake_case__  ,     snake_case__  ,     generator=snake_case__				)

																					lowercase		:Tuple       							=				output.prev_sample, output.prev_sample_mean

														lowercase		:str       							=				sample_mean.clamp(0  ,     1				)
														lowercase		:int       							=				sample.cpu().permute(0  ,     2  ,     3  ,     1				).numpy()
														if output_type == "pil":
																					lowercase		:str       							=				self.numpy_to_pil(snake_case__				)

														if not return_dict:
																					return (sample,)

														return ImagePipelineOutput(images=snake_case__				)





"""simple docstring"""



from __future__ import annotations

from decimal import Decimal

from numpy import array






def       lowerCamelCase					(a_						:list[list[float]])     ->							list[list[float]]:
       lowercase		:List[str]       							=				Decimal

       # Check if the provided matrix has 2 rows and 2 columns
       # since this implementation only works for 2x2 matrices
       if len(a_) == 2 and len(matrix[0]) == 2 and len(matrix[1]) == 2:
              # Calculate the determinant of the matrix
              lowercase		:List[str]       							=				float(
                  d(matrix[0][0]) * d(matrix[1][1]) - d(matrix[1][0]) * d(matrix[0][1]))
              if determinant == 0:
                     raise ValueError('''This matrix has no inverse.''')

              # Creates a copy of the matrix with swapped positions of the elements
              lowercase		:Optional[Any]       							=				[[0.0, 0.0], [0.0, 0.0]]
              lowercase							,  lowercase		:List[Any]       							=				matrix[1][1], matrix[0][0]
              lowercase							,  lowercase		:Union[str, Any]       							=				-matrix[1][0], -matrix[0][1]

              # Calculate the inverse of the matrix
              return [
                  [(float(d(a_)) / determinant) or 0.0 for n in row] for row in swapped_matrix
              ]
       elif (
           len(a_) == 3
           and len(matrix[0]) == 3
           and len(matrix[1]) == 3
           and len(matrix[2]) == 3
       ):
              # Calculate the determinant of the matrix using Sarrus rule
              lowercase		:Any       							=				float(
                  (
                      (d(matrix[0][0]) * d(matrix[1][1]) * d(matrix[2][2]))
                      + (d(matrix[0][1]) * d(matrix[1][2]) * d(matrix[2][0]))
                      + (d(matrix[0][2]) * d(matrix[1][0]) * d(matrix[2][1]))
                  )
                  - (
                      (d(matrix[0][2]) * d(matrix[1][1]) * d(matrix[2][0]))
                      + (d(matrix[0][1]) * d(matrix[1][0]) * d(matrix[2][2]))
                      + (d(matrix[0][0]) * d(matrix[1][2]) * d(matrix[2][1]))
                  ))
              if determinant == 0:
                     raise ValueError('''This matrix has no inverse.''')

              # Creating cofactor matrix
              lowercase		:Optional[Any]       							=				[
                  [d(0.0), d(0.0), d(0.0)],
                  [d(0.0), d(0.0), d(0.0)],
                  [d(0.0), d(0.0), d(0.0)],
              ]
              lowercase		:Optional[int]       							=				(d(matrix[1][1]) * d(matrix[2][2])) - (
                  d(matrix[1][2]) * d(matrix[2][1])
              )
              lowercase		:str       							=				-(
                  (d(matrix[1][0]) * d(matrix[2][2])) - (d(matrix[1][2]) * d(matrix[2][0]))
              )
              lowercase		:Union[str, Any]       							=				(d(matrix[1][0]) * d(matrix[2][1])) - (
                  d(matrix[1][1]) * d(matrix[2][0])
              )
              lowercase		:Union[str, Any]       							=				-(
                  (d(matrix[0][1]) * d(matrix[2][2])) - (d(matrix[0][2]) * d(matrix[2][1]))
              )
              lowercase		:Union[str, Any]       							=				(d(matrix[0][0]) * d(matrix[2][2])) - (
                  d(matrix[0][2]) * d(matrix[2][0])
              )
              lowercase		:List[str]       							=				-(
                  (d(matrix[0][0]) * d(matrix[2][1])) - (d(matrix[0][1]) * d(matrix[2][0]))
              )
              lowercase		:Union[str, Any]       							=				(d(matrix[0][1]) * d(matrix[1][2])) - (
                  d(matrix[0][2]) * d(matrix[1][1])
              )
              lowercase		:Union[str, Any]       							=				-(
                  (d(matrix[0][0]) * d(matrix[1][2])) - (d(matrix[0][2]) * d(matrix[1][0]))
              )
              lowercase		:Any       							=				(d(matrix[0][0]) * d(matrix[1][1])) - (
                  d(matrix[0][1]) * d(matrix[1][0])
              )

              # Transpose the cofactor matrix (Adjoint matrix)
              lowercase		:Union[str, Any]       							=				array(a_)
              for i in range(3):
                     for j in range(3):
                            lowercase		:Any       							=				cofactor_matrix[j][i]

        # Inverse of the matrix using the formula (1/determinant) * adjoint matrix
              lowercase		:str       							=				array(a_)
              for i in range(3):
                     for j in range(3):
                            inverse_matrix[i][j] /= d(a_)

        # Calculate the inverse of the matrix
              return [[float(d(a_)) or 0.0 for n in row] for row in inverse_matrix]
       raise ValueError('''Please provide a matrix of size 2x2 or 3x3.''')

