


from typing import List, Optional, Tuple, Union

import torch

from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput





class   __a			(    __UpperCamelCase      ):
 def __init__(   self				, lowerCAmelCase__				, lowerCAmelCase__ )					->				Optional[int]:




        '''simple docstring'''
        super().__init__()

        # make sure scheduler can always be converted to DDIM
        lowercase__:   Tuple  			=   DDIMScheduler.from_config(scheduler.config )

        self.register_modules(unet=lowerCAmelCase__				, scheduler=lowerCAmelCase__ )
 @torch.no_grad()
 def __call__(   self				, lowerCAmelCase__ = 1				, lowerCAmelCase__ = None				, lowerCAmelCase__ = 0.0				, lowerCAmelCase__ = 50				, lowerCAmelCase__ = None				, lowerCAmelCase__ = "pil"				, lowerCAmelCase__ = True				, )					->				Union[str, Any]:




        '''simple docstring'''


        if isinstance(self.unet.config.sample_size				, lowerCAmelCase__ ):
               lowercase__:   Tuple  			=   (
                   batch_size,
                   self.unet.config.in_channels,
                   self.unet.config.sample_size,
                   self.unet.config.sample_size,
               )
        else:
               lowercase__:   Union[str, Any]  			=   (batch_size, self.unet.config.in_channels, *self.unet.config.sample_size)

        if isinstance(lowerCAmelCase__				, lowerCAmelCase__ ) and len(lowerCAmelCase__ ) != batch_size:
               raise ValueError(
                   F'You have passed a list of generators of length {len(lowerCAmelCase__ )}, but requested an effective batch'
                   F' size of {batch_size}. Make sure the batch size matches the length of the generators.' )

        lowercase__:   Dict  			=   randn_tensor(lowerCAmelCase__				, generator=lowerCAmelCase__				, device=self.device				, dtype=self.unet.dtype )

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

        for t in self.progress_bar(self.scheduler.timesteps ):
               # 1. predict noise model_output
               lowercase__:   Optional[int]  			=   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__:   Dict  			=   self.scheduler.step(
                   lowerCAmelCase__				, lowerCAmelCase__				, lowerCAmelCase__				, eta=lowerCAmelCase__				, use_clipped_model_output=lowerCAmelCase__				, generator=lowerCAmelCase__ ).prev_sample

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

        if not return_dict:
               return (image,)

        return ImagePipelineOutput(images=lowerCAmelCase__ )




_lowerCamelCase       :				int       =			[4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase       :				str       =			[3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase       :				List[str]       =			{
    0: '''Sunday''',
    1: '''Monday''',
    2: '''Tuesday''',
    3: '''Wednesday''',
    4: '''Thursday''',
    5: '''Friday''',
    6: '''Saturday''',
}






def        a_		(       __lowercase   :	int       ,					__lowercase   :	int       ,					__lowercase   :	int ) ->  str:
			assert len(str(__lowercase ) ) > 2, "year should be in YYYY format"
			assert 1 <= month <= 12, "month should be between 1 to 12"
			assert 1 <= day <= 31, "day should be between 1 to 31"

			# Doomsday algorithm:
			_snake_case		=			year // 100
			_snake_case		=			(5 * (century % 4) + 2) % 7
			_snake_case		=			year % 100
			_snake_case		=			centurian % 12
			_snake_case		=			(
			    (centurian // 12) + centurian_m + (centurian_m // 4) + century_anchor
			) % 7
			_snake_case		=			(
			    DOOMSDAY_NOT_LEAP[month - 1]
			    if (year % 4 != 0) or (centurian == 0 and (year % 400) == 0)
			    else DOOMSDAY_LEAP[month - 1]
			)
			_snake_case		=			(dooms_day + day - day_anchor) % 7
			return WEEK_DAY_NAMES[week_day]


if __name__ == "__main__":
			import doctest

			doctest.testmod()