


from math import cos, sin, sqrt, tau

from audio_filters.iir_filter import IIRFilter







def 							lowerCAmelCase_	(   __lowerCamelCase				,      __lowerCamelCase				,      __lowerCamelCase = 1 / sqrt(2      )      ):
							__snake_case						:     List[Any]									=  tau * frequency / samplerate
							__snake_case						:     Union[str, Any]									=  sin(__lowerCamelCase      )
							__snake_case						:     int									=  cos(__lowerCamelCase      )
							__snake_case						:     Union[str, Any]									=  _sin / (2 * q_factor)

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

							__snake_case						:     Any									=  1 + alpha
							__snake_case						:     List[str]									=  -2 * _cos
							__snake_case						:     List[str]									=  1 - alpha

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







def 							lowerCAmelCase_	(   __lowerCamelCase				,      __lowerCamelCase				,      __lowerCamelCase = 1 / sqrt(2      )      ):
							__snake_case						:     Dict									=  tau * frequency / samplerate
							__snake_case						:     List[str]									=  sin(__lowerCamelCase      )
							__snake_case						:     Dict									=  cos(__lowerCamelCase      )
							__snake_case						:     int									=  _sin / (2 * q_factor)

							__snake_case						:     Tuple									=  (1 + _cos) / 2
							__snake_case						:     Tuple									=  -1 - _cos

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

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







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

							__snake_case						:     Any									=  _sin / 2
							__snake_case						:     Tuple									=  0
							__snake_case						:     Optional[int]									=  -ba

							__snake_case						:     List[str]									=  1 + alpha
							__snake_case						:     Dict									=  -2 * _cos
							__snake_case						:     int									=  1 - alpha

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







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

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

							__snake_case						:     List[Any]									=  IIRFilter(2      )
							filt.set_coefficients([ba, ba, ba]				,      [ba, ba, ba]      )
							return filt







def 							lowerCAmelCase_	(   __lowerCamelCase				,      __lowerCamelCase				,      __lowerCamelCase				,      __lowerCamelCase = 1 / sqrt(2      )				,      ):
							__snake_case						:     Tuple									=  tau * frequency / samplerate
							__snake_case						:     List[str]									=  sin(__lowerCamelCase      )
							__snake_case						:     List[Any]									=  cos(__lowerCamelCase      )
							__snake_case						:     Optional[int]									=  _sin / (2 * q_factor)
							__snake_case						:     Optional[int]									=  1_0 ** (gain_db / 4_0)

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

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







def 							lowerCAmelCase_	(   __lowerCamelCase				,      __lowerCamelCase				,      __lowerCamelCase				,      __lowerCamelCase = 1 / sqrt(2      )				,      ):
							__snake_case						:     Tuple									=  tau * frequency / samplerate
							__snake_case						:     int									=  sin(__lowerCamelCase      )
							__snake_case						:     Union[str, Any]									=  cos(__lowerCamelCase      )
							__snake_case						:     str									=  _sin / (2 * q_factor)
							__snake_case						:     Union[str, Any]									=  1_0 ** (gain_db / 4_0)
							__snake_case						:     Dict									=  (big_a + 1) - (big_a - 1) * _cos
							__snake_case						:     Tuple									=  (big_a + 1) + (big_a - 1) * _cos
							__snake_case						:     int									=  (big_a - 1) - (big_a + 1) * _cos
							__snake_case						:     Tuple									=  (big_a - 1) + (big_a + 1) * _cos
							__snake_case						:     Any									=  2 * sqrt(__lowerCamelCase      ) * alpha

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

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







def 							lowerCAmelCase_	(   __lowerCamelCase				,      __lowerCamelCase				,      __lowerCamelCase				,      __lowerCamelCase = 1 / sqrt(2      )				,      ):
							__snake_case						:     List[Any]									=  tau * frequency / samplerate
							__snake_case						:     Dict									=  sin(__lowerCamelCase      )
							__snake_case						:     List[Any]									=  cos(__lowerCamelCase      )
							__snake_case						:     int									=  _sin / (2 * q_factor)
							__snake_case						:     str									=  1_0 ** (gain_db / 4_0)
							__snake_case						:     Optional[int]									=  (big_a + 1) - (big_a - 1) * _cos
							__snake_case						:     List[str]									=  (big_a + 1) + (big_a - 1) * _cos
							__snake_case						:     Tuple									=  (big_a - 1) - (big_a + 1) * _cos
							__snake_case						:     Any									=  (big_a - 1) + (big_a + 1) * _cos
							__snake_case						:     str									=  2 * sqrt(__lowerCamelCase      ) * alpha

							__snake_case						:     Any									=  big_a * (ppmc + aaa)
							__snake_case						:     Tuple									=  -2 * big_a * pmpc
							__snake_case						:     Tuple									=  big_a * (ppmc - aaa)
							__snake_case						:     Dict									=  pmc + aaa
							__snake_case						:     Tuple									=  2 * mpc
							__snake_case						:     List[Any]									=  pmc - aaa

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








import argparse

import intel_extension_for_pytorch as ipex
import torch

from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline


SCREAMING_SNAKE_CASE__							:      List[str]         =    argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False)
parser.add_argument("""--dpm""", action="""store_true""", help="""Enable DPMSolver or not""")
parser.add_argument("""--steps""", default=None, type=int, help="""Num inference steps""")
SCREAMING_SNAKE_CASE__							:      Tuple         =    parser.parse_args()


SCREAMING_SNAKE_CASE__							:      int         =    """cpu"""
SCREAMING_SNAKE_CASE__							:      Optional[Any]         =    """a lovely <dicoo> in red dress and hat, in the snowly and brightly night, with many brighly buildings"""

SCREAMING_SNAKE_CASE__							:      List[Any]         =    """path-to-your-trained-model"""
SCREAMING_SNAKE_CASE__							:      Tuple         =    StableDiffusionPipeline.from_pretrained(model_id)
if args.dpm:
  SCREAMING_SNAKE_CASE__							:      Union[str, Any]         =    DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
SCREAMING_SNAKE_CASE__							:      Optional[int]         =    pipe.to(device)

# to channels last
SCREAMING_SNAKE_CASE__							:      int         =    pipe.unet.to(memory_format=torch.channels_last)
SCREAMING_SNAKE_CASE__							:      List[Any]         =    pipe.vae.to(memory_format=torch.channels_last)
SCREAMING_SNAKE_CASE__							:      Union[str, Any]         =    pipe.text_encoder.to(memory_format=torch.channels_last)
if pipe.requires_safety_checker:
  SCREAMING_SNAKE_CASE__							:      List[str]         =    pipe.safety_checker.to(memory_format=torch.channels_last)

# optimize with ipex
SCREAMING_SNAKE_CASE__							:      Optional[int]         =    torch.randn(2, 4, 6_4, 6_4)
SCREAMING_SNAKE_CASE__							:      Any         =    torch.rand(1) * 9_9_9
SCREAMING_SNAKE_CASE__							:      List[Any]         =    torch.randn(2, 7_7, 7_6_8)
SCREAMING_SNAKE_CASE__							:      Optional[Any]         =    (sample, timestep, encoder_hidden_status)
try:
  SCREAMING_SNAKE_CASE__							:      Any         =    ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True, sample_input=input_example)
except Exception:
  SCREAMING_SNAKE_CASE__							:      Optional[Any]         =    ipex.optimize(pipe.unet.eval(), dtype=torch.bfloataa, inplace=True)
SCREAMING_SNAKE_CASE__							:      str         =    ipex.optimize(pipe.vae.eval(), dtype=torch.bfloataa, inplace=True)
SCREAMING_SNAKE_CASE__							:      Union[str, Any]         =    ipex.optimize(pipe.text_encoder.eval(), dtype=torch.bfloataa, inplace=True)
if pipe.requires_safety_checker:
  SCREAMING_SNAKE_CASE__							:      Union[str, Any]         =    ipex.optimize(pipe.safety_checker.eval(), dtype=torch.bfloataa, inplace=True)

# compute
SCREAMING_SNAKE_CASE__							:      Optional[Any]         =    6_6_6
SCREAMING_SNAKE_CASE__							:      Any         =    torch.Generator(device).manual_seed(seed)
SCREAMING_SNAKE_CASE__							:      int         =    {"""generator""": generator}
if args.steps is not None:
  SCREAMING_SNAKE_CASE__							:      Optional[int]         =    args.steps

with torch.cpu.amp.autocast(enabled=True, dtype=torch.bfloataa):
  SCREAMING_SNAKE_CASE__							:      Dict         =    pipe(prompt, **generate_kwargs).images[0]

# save image
image.save("""generated.png""")

