


from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import PNDMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput





class    _a				(							__A):
	_a    :    Optional[int]        =				42
	_a    :    Dict        =				42




	def __init__(   self		:						Dict						,   _SCREAMING_SNAKE_CASE		:						str						,   _SCREAMING_SNAKE_CASE		:						Optional[int]						)->			int:
			super().__init__()

			lowerCAmelCase__  :     Optional[Any]       	=   PNDMScheduler.from_config(scheduler.config						)

			self.register_modules(unet=A_						,   scheduler=A_						)




	@torch.no_grad()
	def __call__(   self		:						Tuple						,   _SCREAMING_SNAKE_CASE		:						Any = 1						,   _SCREAMING_SNAKE_CASE		:						Optional[Any] = 50						,   _SCREAMING_SNAKE_CASE		:						Union[str, Any] = None						,   _SCREAMING_SNAKE_CASE		:						Optional[int] = "pil"						,   _SCREAMING_SNAKE_CASE		:						int = True						,   **_SCREAMING_SNAKE_CASE		:						int						,   )->			Dict:
			lowerCAmelCase__  :     List[Any]       	=   randn_tensor(
			    (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)						,   generator=A_						,   device=self.device						,   )

			self.scheduler.set_timesteps(A_						)
			for t in self.progress_bar(self.scheduler.timesteps						):
					lowerCAmelCase__  :     List[Any]       	=   self.unet(A_						,   A_						).sample

					lowerCAmelCase__  :     Optional[int]       	=   self.scheduler.step(A_						,   A_						,   A_						).prev_sample

			lowerCAmelCase__  :     Union[str, Any]       	=   (image / 2 + 0.5).clamp(0						,   1						)
			lowerCAmelCase__  :     List[str]       	=   image.cpu().permute(0						,   2						,   3						,   1						).numpy()
			if output_type == "pil":
					lowerCAmelCase__  :     Optional[int]       	=   self.numpy_to_pil(A_						)

			if not return_dict:
					return (image,)

			return ImagePipelineOutput(images=A_						)









"""simple docstring"""






from math import gcd


def 							A__ (     UpperCamelCase__ = 12_000    ):


  '''simple docstring'''


  _SCREAMING_SNAKE_CASE        =			0
  for d in range(max_d + 1    ):
    for n in range(d // 3 + 1       ,							(d + 1) // 2    ):
      if gcd(UpperCamelCase__       ,							UpperCamelCase__    ) == 1:
        fractions_number += 1
  return fractions_number


if __name__ == "__main__":
    print(F'''{solution() = }''')
