






"""simple docstring"""





import torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest






class 					a						( __snake_case		):
    SCREAMING_SNAKE_CASE						:					List[str]						=			(VQDiffusionScheduler,)






    def        UpperCamelCase	(	self					:							Optional[Any]	,						**__SCREAMING_SNAKE_CASE					:							List[str] )					->		List[Any]:
      lowerCamelCase_   					=						{
          'num_vec_classes': 4097,
          'num_train_timesteps': 100,
      }

      config.update(**__SCREAMING_SNAKE_CASE )
      return config






    def        UpperCamelCase	(	self					:							int	,						__SCREAMING_SNAKE_CASE					:							Dict )					->		List[Any]:
      lowerCamelCase_   					=						4
      lowerCamelCase_   					=						8
      lowerCamelCase_   					=						8

      lowerCamelCase_   					=						torch.randint(0	,						__SCREAMING_SNAKE_CASE	,						(batch_size, height * width) )

      return sample






    @property
    def        UpperCamelCase	(	self					:							Union[str, Any] )					->		Any:
      assert False






    def        UpperCamelCase	(	self					:							Union[str, Any]	,						__SCREAMING_SNAKE_CASE					:							Any )					->		List[Any]:
      def model(__SCREAMING_SNAKE_CASE					:							Optional[Any]	,						__SCREAMING_SNAKE_CASE					:							List[Any]	,						*__SCREAMING_SNAKE_CASE					:							Optional[int] ):
        lowerCamelCase_					,     lowerCamelCase_   					=						sample.shape
        lowerCamelCase_   					=						torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels) )
        lowerCamelCase_   					=						F.log_softmax(logits.double()	,						dim=1 ).float()
        return return_value

      return model






    def        UpperCamelCase	(	self					:							Union[str, Any] )					->		str:
      for timesteps in [2, 5, 100, 1000]:
        self.check_over_configs(num_train_timesteps=__SCREAMING_SNAKE_CASE )






    def        UpperCamelCase	(	self					:							Optional[Any] )					->		str:
      for num_vec_classes in [5, 100, 1000, 4000]:
        self.check_over_configs(num_vec_classes=__SCREAMING_SNAKE_CASE )






    def        UpperCamelCase	(	self					:							Optional[int] )					->		int:
      for t in [0, 50, 99]:
        self.check_over_forward(time_step=__SCREAMING_SNAKE_CASE )






    def        UpperCamelCase	(	self					:							str )					->		Optional[int]:
      pass












"""simple docstring"""





def 					lowerCamelCase__	(							_lowerCamelCase	:		int = 1000			)				->    int:
  lowerCamelCase_   					=						0
  lowerCamelCase_   					=						(n - 1) // 3
  total += ((terms) * (6 + (terms - 1) * 3)) // 2  # total of an A.P.
  lowerCamelCase_   					=						(n - 1) // 5
  total += ((terms) * (10 + (terms - 1) * 5)) // 2
  lowerCamelCase_   					=						(n - 1) // 15
  total -= ((terms) * (30 + (terms - 1) * 15)) // 2
  return total


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




