






"""simple docstring"""
from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter

def 				snake_case      (   A__	,A__	,A__ = 1 / sqrt(2						)						):
			UpperCAmelCase_     : Dict			     =					tau * frequency / samplerate
			UpperCAmelCase_     : int			     =					sin(__snake_case						)
			UpperCAmelCase_     : int			     =					cos(__snake_case						)
			UpperCAmelCase_     : int			     =					_sin / (2 * q_factor)

			UpperCAmelCase_     : Any			     =					(1 - _cos) / 2
			UpperCAmelCase_     : Dict			     =					1 - _cos

			UpperCAmelCase_     : Union[str, Any]			     =					1 + alpha
			UpperCAmelCase_     : Optional[int]			     =					-2 * _cos
			UpperCAmelCase_     : Optional[int]			     =					1 - alpha

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

def 				snake_case      (   A__	,A__	,A__ = 1 / sqrt(2						)						):
			UpperCAmelCase_     : Tuple			     =					tau * frequency / samplerate
			UpperCAmelCase_     : Tuple			     =					sin(__snake_case						)
			UpperCAmelCase_     : Union[str, Any]			     =					cos(__snake_case						)
			UpperCAmelCase_     : Tuple			     =					_sin / (2 * q_factor)

			UpperCAmelCase_     : Dict			     =					(1 + _cos) / 2
			UpperCAmelCase_     : str			     =					-1 - _cos

			UpperCAmelCase_     : Optional[int]			     =					1 + alpha
			UpperCAmelCase_     : Any			     =					-2 * _cos
			UpperCAmelCase_     : int			     =					1 - alpha

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

def 				snake_case      (   A__	,A__	,A__ = 1 / sqrt(2						)						):
			UpperCAmelCase_     : Any			     =					tau * frequency / samplerate
			UpperCAmelCase_     : int			     =					sin(__snake_case						)
			UpperCAmelCase_     : Optional[int]			     =					cos(__snake_case						)
			UpperCAmelCase_     : List[Any]			     =					_sin / (2 * q_factor)

			UpperCAmelCase_     : Any			     =					_sin / 2
			UpperCAmelCase_     : Dict			     =					0
			UpperCAmelCase_     : Optional[int]			     =					-ba

			UpperCAmelCase_     : Any			     =					1 + alpha
			UpperCAmelCase_     : Optional[int]			     =					-2 * _cos
			UpperCAmelCase_     : Optional[Any]			     =					1 - alpha

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

def 				snake_case      (   A__	,A__	,A__ = 1 / sqrt(2						)						):
			UpperCAmelCase_     : Optional[int]			     =					tau * frequency / samplerate
			UpperCAmelCase_     : Any			     =					sin(__snake_case						)
			UpperCAmelCase_     : Optional[Any]			     =					cos(__snake_case						)
			UpperCAmelCase_     : List[Any]			     =					_sin / (2 * q_factor)

			UpperCAmelCase_     : Tuple			     =					1 - alpha
			UpperCAmelCase_     : Optional[int]			     =					-2 * _cos
			UpperCAmelCase_     : List[Any]			     =					1 + alpha

			UpperCAmelCase_     : str			     =					IIRFilter(2						)
			filt.set_coefficients([ba, ba, ba]	,[ba, ba, ba]						)
			return filt

def 				snake_case      (   A__	,A__	,A__	,A__ = 1 / sqrt(2						)	,):
			UpperCAmelCase_     : Union[str, Any]			     =					tau * frequency / samplerate
			UpperCAmelCase_     : List[Any]			     =					sin(__snake_case						)
			UpperCAmelCase_     : List[str]			     =					cos(__snake_case						)
			UpperCAmelCase_     : List[Any]			     =					_sin / (2 * q_factor)
			UpperCAmelCase_     : Optional[Any]			     =					10 ** (gain_db / 40)

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

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

def 				snake_case      (   A__	,A__	,A__	,A__ = 1 / sqrt(2						)	,):
			UpperCAmelCase_     : int			     =					tau * frequency / samplerate
			UpperCAmelCase_     : Tuple			     =					sin(__snake_case						)
			UpperCAmelCase_     : List[Any]			     =					cos(__snake_case						)
			UpperCAmelCase_     : List[Any]			     =					_sin / (2 * q_factor)
			UpperCAmelCase_     : List[Any]			     =					10 ** (gain_db / 40)
			UpperCAmelCase_     : int			     =					(big_a + 1) - (big_a - 1) * _cos
			UpperCAmelCase_     : Optional[int]			     =					(big_a + 1) + (big_a - 1) * _cos
			UpperCAmelCase_     : Dict			     =					(big_a - 1) - (big_a + 1) * _cos
			UpperCAmelCase_     : Union[str, Any]			     =					(big_a - 1) + (big_a + 1) * _cos
			UpperCAmelCase_     : Union[str, Any]			     =					2 * sqrt(__snake_case						) * alpha

			UpperCAmelCase_     : Tuple			     =					big_a * (pmc + aaa)
			UpperCAmelCase_     : Union[str, Any]			     =					2 * big_a * mpc
			UpperCAmelCase_     : Optional[int]			     =					big_a * (pmc - aaa)
			UpperCAmelCase_     : Dict			     =					ppmc + aaa
			UpperCAmelCase_     : 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      (   A__	,A__	,A__	,A__ = 1 / sqrt(2						)	,):
			UpperCAmelCase_     : List[Any]			     =					tau * frequency / samplerate
			UpperCAmelCase_     : Dict			     =					sin(__snake_case						)
			UpperCAmelCase_     : Tuple			     =					cos(__snake_case						)
			UpperCAmelCase_     : Any			     =					_sin / (2 * q_factor)
			UpperCAmelCase_     : Dict			     =					10 ** (gain_db / 40)
			UpperCAmelCase_     : str			     =					(big_a + 1) - (big_a - 1) * _cos
			UpperCAmelCase_     : Union[str, Any]			     =					(big_a + 1) + (big_a - 1) * _cos
			UpperCAmelCase_     : Union[str, Any]			     =					(big_a - 1) - (big_a + 1) * _cos
			UpperCAmelCase_     : Optional[int]			     =					(big_a - 1) + (big_a + 1) * _cos
			UpperCAmelCase_     : Tuple			     =					2 * sqrt(__snake_case						) * alpha

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

			UpperCAmelCase_     : List[str]			     =					IIRFilter(2						)
			filt.set_coefficients([aa, aa, aa]	,[ba, ba, ba]						)
			return filt











"""simple docstring"""



# limitations under the License.


from typing import Optional, Tuple, Union

import torch

from diffusers import DiffusionPipeline, ImagePipelineOutput

class        a     (   a_	):







    def __init__(			self							,		_lowerCamelCase							,		_lowerCamelCase       ):
      super().__init__()
      self.register_modules(unet=_lowerCamelCase							,		scheduler=_lowerCamelCase       )







    @torch.no_grad()
    def __call__(			self							,		_lowerCamelCase = 1							,		_lowerCamelCase = None							,		_lowerCamelCase = 5_0							,		_lowerCamelCase = "pil"							,		_lowerCamelCase = True							,		**_lowerCamelCase							,		):
      lowercase							    =       torch.randn(
          (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)							,		generator=_lowerCamelCase							,		)
      lowercase							    =       image.to(self.device       )

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

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

        # 2. predict previous mean of image x_t-1 and add variance depending on eta
        # eta corresponds to η in paper and should be between [0, 1]
        # do x_t -> x_t-1
        lowercase							    =       self.scheduler.step(_lowerCamelCase							,		_lowerCamelCase							,		_lowerCamelCase       ).prev_sample

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

      if not return_dict:
        return (image,), "This is a local test"

      return ImagePipelineOutput(images=_lowerCamelCase       ), "This is a local test"


