'''simple docstring'''

import warnings
from typing import List, Optional, Tuple, Union

import numpy as np
import PIL
import torch

from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput


_A			:      List[str]					      =				logging.get_logger(__name__)  # pylint: disable=invalid-name







def      UpperCamelCase_						(					snake_case_       :       Union[List, PIL.Image.Image, torch.Tensor]      )					->     List[str]:






 '''simple docstring'''

 warnings.warn(
     """The preprocess method is deprecated and will be removed in a future version. Please"""
     """ use VaeImageProcessor.preprocess instead"""						,		_lowerCAmelCase						,		)
 if isinstance(_lowerCAmelCase						,		torch.Tensor      ):
  return image
 elif isinstance(_lowerCAmelCase						,		PIL.Image.Image      ):
  __lowerCAmelCase											=						[image]

 if isinstance(image[0]						,		PIL.Image.Image      ):
  __lowerCAmelCase											=						image[0].size
  __lowerCAmelCase											=						(x - x % 8 for x in (w, h))  # resize to integer multiple of 8

  __lowerCAmelCase											=						[np.array(i.resize((w, h)						,		resample=PIL_INTERPOLATION["""lanczos"""]      )      )[None, :] for i in image]
  __lowerCAmelCase											=						np.concatenate(_lowerCAmelCase						,		axis=0      )
  __lowerCAmelCase											=						np.array(_lowerCAmelCase      ).astype(np.floataa      ) / 2_55.0
  __lowerCAmelCase											=						image.transpose(0						,		3						,		1						,		2      )
  __lowerCAmelCase											=						2.0 * image - 1.0
  __lowerCAmelCase											=						torch.from_numpy(_lowerCAmelCase      )
 elif isinstance(image[0]						,		torch.Tensor      ):
  __lowerCAmelCase											=						torch.cat(_lowerCAmelCase						,		dim=0      )
 return image







def      UpperCamelCase_						(					snake_case_       :       Union[List, PIL.Image.Image, torch.Tensor]      )					->     Tuple:






 '''simple docstring'''

 if isinstance(_lowerCAmelCase						,		torch.Tensor      ):
  return mask
 elif isinstance(_lowerCAmelCase						,		PIL.Image.Image      ):
  __lowerCAmelCase											=						[mask]

 if isinstance(mask[0]						,		PIL.Image.Image      ):
  __lowerCAmelCase											=						mask[0].size
  __lowerCAmelCase											=						(x - x % 32 for x in (w, h))  # resize to integer multiple of 32
  __lowerCAmelCase											=						[np.array(m.convert("""L"""      ).resize((w, h)						,		resample=PIL_INTERPOLATION["""nearest"""]      )      )[None, :] for m in mask]
  __lowerCAmelCase											=						np.concatenate(_lowerCAmelCase						,		axis=0      )
  __lowerCAmelCase											=						mask.astype(np.floataa      ) / 2_55.0
  __lowerCAmelCase											=						0
  __lowerCAmelCase											=						1
  __lowerCAmelCase											=						torch.from_numpy(_lowerCAmelCase      )
 elif isinstance(mask[0]						,		torch.Tensor      ):
  __lowerCAmelCase											=						torch.cat(_lowerCAmelCase						,		dim=0      )
 return mask







class 				_lowercase     (				A__			):


 '''simple docstring'''






 _SCREAMING_SNAKE_CASE     :       Dict      	=					42
 _SCREAMING_SNAKE_CASE     :       int      	=					42
 def __init__(      self   :	Tuple      ,       SCREAMING_SNAKE_CASE__   :	Optional[Any]      ,       SCREAMING_SNAKE_CASE__   :	str							)  ->    Union[str, Any]:
  super().__init__()
  self.register_modules(unet=__snake_case      ,       scheduler=__snake_case							)





 @torch.no_grad()
 def __call__(      self   :	Union[str, Any]      ,       SCREAMING_SNAKE_CASE__   :	Union[torch.Tensor, PIL.Image.Image]      ,       SCREAMING_SNAKE_CASE__   :	Union[torch.Tensor, PIL.Image.Image]      ,       SCREAMING_SNAKE_CASE__   :	int = 2_50      ,       SCREAMING_SNAKE_CASE__   :	float = 0.0      ,       SCREAMING_SNAKE_CASE__   :	int = 10      ,       SCREAMING_SNAKE_CASE__   :	int = 10      ,       SCREAMING_SNAKE_CASE__   :	Optional[Union[torch.Generator, List[torch.Generator]]] = None      ,       SCREAMING_SNAKE_CASE__   :	Optional[str] = "pil"      ,       SCREAMING_SNAKE_CASE__   :	bool = True      ,       )  ->    Union[ImagePipelineOutput, Tuple]:
  __lowerCAmelCase											=						image

  __lowerCAmelCase											=						_preprocess_image(__snake_case							)
  __lowerCAmelCase											=						original_image.to(device=self.device      ,       dtype=self.unet.dtype							)
  __lowerCAmelCase											=						_preprocess_mask(__snake_case							)
  __lowerCAmelCase											=						mask_image.to(device=self.device      ,       dtype=self.unet.dtype							)

  __lowerCAmelCase											=						original_image.shape[0]

  # sample gaussian noise to begin the loop
  if isinstance(__snake_case      ,       __snake_case							) and len(__snake_case							) != batch_size:
   raise ValueError(
       f"""You have passed a list of generators of length {len(__snake_case							)}, but requested an effective batch"""
       f""" size of {batch_size}. Make sure the batch size matches the length of the generators."""							)

  __lowerCAmelCase											=						original_image.shape
  __lowerCAmelCase											=						randn_tensor(__snake_case      ,       generator=__snake_case      ,       device=self.device      ,       dtype=self.unet.dtype							)

  # set step values
  self.scheduler.set_timesteps(__snake_case      ,       __snake_case      ,       __snake_case      ,       self.device							)
  __lowerCAmelCase											=						eta

  __lowerCAmelCase											=						self.scheduler.timesteps[0] + 1
  __lowerCAmelCase											=						generator[0] if isinstance(__snake_case      ,       __snake_case							) else generator
  for i, t in enumerate(self.progress_bar(self.scheduler.timesteps							)							):
   if t < t_last:
    # predict the noise residual
    __lowerCAmelCase											=						self.unet(__snake_case      ,       __snake_case							).sample
    # compute previous image: x_t -> x_t-1
    __lowerCAmelCase											=						self.scheduler.step(__snake_case      ,       __snake_case      ,       __snake_case      ,       __snake_case      ,       __snake_case      ,       __snake_case							).prev_sample

   else:
    # compute the reverse: x_t-1 -> x_t
    __lowerCAmelCase											=						self.scheduler.undo_step(__snake_case      ,       __snake_case      ,       __snake_case							)
   __lowerCAmelCase											=						t

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

  if not return_dict:
   return (image,)

  return ImagePipelineOutput(images=__snake_case							)











'''simple docstring'''






from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )  )      ->   IIRFilter:
							UpperCAmelCase :       Optional[int] 							=		tau * frequency / samplerate
							UpperCAmelCase :       List[Any] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Optional[Any] 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       int 							=		_sin / (2 * q_factor)

							UpperCAmelCase :       Any 							=		(1 - _cos) / 2
							UpperCAmelCase :       List[Any] 							=		1 - _cos

							UpperCAmelCase :       Union[str, Any] 							=		1 + alpha
							UpperCAmelCase :       Any 							=		-2 * _cos
							UpperCAmelCase :       Dict 							=		1 - alpha

							UpperCAmelCase :       Union[str, Any] 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )  )      ->   IIRFilter:
							UpperCAmelCase :       Any 							=		tau * frequency / samplerate
							UpperCAmelCase :       Tuple 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Tuple 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Dict 							=		_sin / (2 * q_factor)

							UpperCAmelCase :       int 							=		(1 + _cos) / 2
							UpperCAmelCase :       List[Any] 							=		-1 - _cos

							UpperCAmelCase :       Tuple 							=		1 + alpha
							UpperCAmelCase :       List[str] 							=		-2 * _cos
							UpperCAmelCase :       Optional[Any] 							=		1 - alpha

							UpperCAmelCase :       Tuple 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )  )      ->   IIRFilter:
							UpperCAmelCase :       Optional[int] 							=		tau * frequency / samplerate
							UpperCAmelCase :       Optional[int] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Tuple 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Optional[int] 							=		_sin / (2 * q_factor)

							UpperCAmelCase :       Union[str, Any] 							=		_sin / 2
							UpperCAmelCase :       Any 							=		0
							UpperCAmelCase :       int 							=		-ba

							UpperCAmelCase :       Optional[Any] 							=		1 + alpha
							UpperCAmelCase :       List[Any] 							=		-2 * _cos
							UpperCAmelCase :       Optional[Any] 							=		1 - alpha

							UpperCAmelCase :       int 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )  )      ->   IIRFilter:
							UpperCAmelCase :       List[str] 							=		tau * frequency / samplerate
							UpperCAmelCase :       Union[str, Any] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       str 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Optional[Any] 							=		_sin / (2 * q_factor)

							UpperCAmelCase :       List[str] 							=		1 - alpha
							UpperCAmelCase :       Any 							=		-2 * _cos
							UpperCAmelCase :       Optional[int] 							=		1 + alpha

							UpperCAmelCase :       Union[str, Any] 							=		IIRFilter(2  )
							filt.set_coefficients([ba, ba, ba]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )   ,      )      ->   IIRFilter:
							UpperCAmelCase :       Optional[Any] 							=		tau * frequency / samplerate
							UpperCAmelCase :       Union[str, Any] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Optional[int] 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Dict 							=		_sin / (2 * q_factor)
							UpperCAmelCase :       str 							=		10 ** (gain_db / 40)

							UpperCAmelCase :       int 							=		1 + alpha * big_a
							UpperCAmelCase :       Union[str, Any] 							=		-2 * _cos
							UpperCAmelCase :       Optional[Any] 							=		1 - alpha * big_a
							UpperCAmelCase :       Union[str, Any] 							=		1 + alpha / big_a
							UpperCAmelCase :       Tuple 							=		-2 * _cos
							UpperCAmelCase :       Any 							=		1 - alpha / big_a

							UpperCAmelCase :       Optional[Any] 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt


def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )   ,      )      ->   IIRFilter:
							UpperCAmelCase :       Any 							=		tau * frequency / samplerate
							UpperCAmelCase :       Optional[int] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Union[str, Any] 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       str 							=		_sin / (2 * q_factor)
							UpperCAmelCase :       List[str] 							=		10 ** (gain_db / 40)
							UpperCAmelCase :       Optional[int] 							=		(big_a + 1) - (big_a - 1) * _cos
							UpperCAmelCase :       int 							=		(big_a + 1) + (big_a - 1) * _cos
							UpperCAmelCase :       int 							=		(big_a - 1) - (big_a + 1) * _cos
							UpperCAmelCase :       Optional[int] 							=		(big_a - 1) + (big_a + 1) * _cos
							UpperCAmelCase :       str 							=		2 * sqrt(_lowerCAmelCase  ) * alpha

							UpperCAmelCase :       Dict 							=		big_a * (pmc + aaa)
							UpperCAmelCase :       Any 							=		2 * big_a * mpc
							UpperCAmelCase :       Union[str, Any] 							=		big_a * (pmc - aaa)
							UpperCAmelCase :       Optional[int] 							=		ppmc + aaa
							UpperCAmelCase :       Optional[Any] 							=		-2 * pmpc
							UpperCAmelCase :       Optional[Any] 							=		ppmc - aaa

							UpperCAmelCase :       int 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt




def  snake_case_     (					_lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						int   ,      _lowerCAmelCase  :						float   ,      _lowerCAmelCase  :						float = 1 / sqrt(2  )   ,      )      ->   IIRFilter:
							UpperCAmelCase :       int 							=		tau * frequency / samplerate
							UpperCAmelCase :       Union[str, Any] 							=		sin(_lowerCAmelCase  )
							UpperCAmelCase :       Union[str, Any] 							=		cos(_lowerCAmelCase  )
							UpperCAmelCase :       Any 							=		_sin / (2 * q_factor)
							UpperCAmelCase :       int 							=		10 ** (gain_db / 40)
							UpperCAmelCase :       List[str] 							=		(big_a + 1) - (big_a - 1) * _cos
							UpperCAmelCase :       Union[str, Any] 							=		(big_a + 1) + (big_a - 1) * _cos
							UpperCAmelCase :       Optional[Any] 							=		(big_a - 1) - (big_a + 1) * _cos
							UpperCAmelCase :       Union[str, Any] 							=		(big_a - 1) + (big_a + 1) * _cos
							UpperCAmelCase :       List[str] 							=		2 * sqrt(_lowerCAmelCase  ) * alpha

							UpperCAmelCase :       Any 							=		big_a * (ppmc + aaa)
							UpperCAmelCase :       str 							=		-2 * big_a * pmpc
							UpperCAmelCase :       List[Any] 							=		big_a * (ppmc - aaa)
							UpperCAmelCase :       Optional[Any] 							=		pmc + aaa
							UpperCAmelCase :       Any 							=		2 * mpc
							UpperCAmelCase :       str 							=		pmc - aaa

							UpperCAmelCase :       Union[str, Any] 							=		IIRFilter(2  )
							filt.set_coefficients([aa, aa, aa]   ,      [ba, ba, ba]  )
							return filt





