

import math
from typing import Callable, List, Optional, Union

import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer

from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_upscale import StableDiffusionUpscalePipeline
from diffusers.schedulers import DDIMScheduler, DDPMScheduler, LMSDiscreteScheduler, PNDMScheduler

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   List[Any]     ,					SCREAMING_SNAKE_CASE_		:   Any     ,					SCREAMING_SNAKE_CASE_		:   Tuple=[]      ):



     '''simple docstring'''





     lowercase__   :       Union[str, Any]				=	size[0] - overlap_pixels * 2
     lowercase__   :       Optional[int]				=	size[1] - overlap_pixels * 2
     for letter in ["l", "r"]:
          if letter in remove_borders:
               size_x += overlap_pixels
     for letter in ["t", "b"]:
          if letter in remove_borders:
               size_y += overlap_pixels
     lowercase__   :       List[Any]				=	np.ones((size_y, size_x)     ,					dtype=np.uinta      ) * 255
     lowercase__   :       Optional[int]				=	np.pad(SCREAMING_SNAKE_CASE_     ,					mode='linear_ramp'     ,					pad_width=SCREAMING_SNAKE_CASE_     ,					end_values=0      )

     if "l" in remove_borders:
          lowercase__   :       List[Any]				=	mask[:, overlap_pixels : mask.shape[1]]
     if "r" in remove_borders:
          lowercase__   :       List[Any]				=	mask[:, 0 : mask.shape[1] - overlap_pixels]
     if "t" in remove_borders:
          lowercase__   :       List[str]				=	mask[overlap_pixels : mask.shape[0], :]
     if "b" in remove_borders:
          lowercase__   :       Optional[int]				=	mask[0 : mask.shape[0] - overlap_pixels, :]
     return mask

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   Optional[int]     ,					SCREAMING_SNAKE_CASE_		:   str     ,					SCREAMING_SNAKE_CASE_		:   str      ):



     '''simple docstring'''





     return max(SCREAMING_SNAKE_CASE_     ,					min(SCREAMING_SNAKE_CASE_     ,					SCREAMING_SNAKE_CASE_      )      )

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   [int]     ,					SCREAMING_SNAKE_CASE_		:   [int]     ,					SCREAMING_SNAKE_CASE_		:   [int]      ):



     '''simple docstring'''





     return (
         clamp(rect[0]     ,					min[0]     ,					max[0]      ),
         clamp(rect[1]     ,					min[1]     ,					max[1]      ),
         clamp(rect[2]     ,					min[0]     ,					max[0]      ),
         clamp(rect[3]     ,					min[1]     ,					max[1]      ),
     )

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   [int]     ,					SCREAMING_SNAKE_CASE_		:   int     ,					SCREAMING_SNAKE_CASE_		:   [int]      ):



     '''simple docstring'''





     lowercase__   :       Optional[Any]				=	list(SCREAMING_SNAKE_CASE_      )
     rect[0] -= overlap
     rect[1] -= overlap
     rect[2] += overlap
     rect[3] += overlap
     lowercase__   :       List[Any]				=	clamp_rect(SCREAMING_SNAKE_CASE_     ,					[0, 0]     ,					[image_size[0], image_size[1]]      )
     return rect

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   List[str]     ,					SCREAMING_SNAKE_CASE_		:   str     ,					SCREAMING_SNAKE_CASE_		:   Any     ,					SCREAMING_SNAKE_CASE_		:   int      ):



     '''simple docstring'''





     lowercase__   :       Tuple				=	Image.new('RGB'     ,					(tile.size[0] + original_slice, tile.size[1])      )
     result.paste(
         original_image.resize((tile.size[0], tile.size[1])     ,					Image.BICUBIC      ).crop(
             (slice_x, 0, slice_x + original_slice, tile.size[1])      )     ,					(0, 0)     ,					)
     result.paste(SCREAMING_SNAKE_CASE_     ,					(original_slice, 0)      )
     return result

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   str     ,					SCREAMING_SNAKE_CASE_		:   Tuple      ):



     '''simple docstring'''





     lowercase__   :       int				=	(original_image_slice * 4, 0, tile.size[0], tile.size[1])
     lowercase__   :       Optional[int]				=	tile.crop(SCREAMING_SNAKE_CASE_      )
     return tile

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   Tuple     ,					SCREAMING_SNAKE_CASE_		:   Optional[int]      ):



     '''simple docstring'''





     lowercase__   :       Optional[Any]				=	n % d
     return n - divisor


class 				SCREAMING_SNAKE_CASE__ (__snake_case					):





    def __init__(				self						,       a						,       a						,       a						,       a						,       a						,       a						,       a = 350						,       ):
         super().__init__(
             vae=a						,       text_encoder=a						,       tokenizer=a						,       unet=a						,       low_res_scheduler=a						,       scheduler=a						,       max_noise_level=a						,       )





    def 				snake_case_    (				self						,       a						,       a						,       a						,       a						,       a						,       a						,       a						,       **a):
         torch.manual_seed(0)
         lowercase__   :       Any				=	(
             min(image.size[0] - (tile_size + original_image_slice)						,       x * tile_size),
             min(image.size[1] - (tile_size + original_image_slice)						,       y * tile_size),
             min(image.size[0]						,       (x + 1) * tile_size),
             min(image.size[1]						,       (y + 1) * tile_size),
         )
         lowercase__   :       Optional[int]				=	add_overlap_rect(a						,       a						,       image.size)
         lowercase__   :       Any				=	image.crop(a)
         lowercase__   :       str				=	((crop_rect[0] + ((crop_rect[2] - crop_rect[0]) / 2)) / image.size[0]) * tile.size[0]
         lowercase__   :       Union[str, Any]				=	translated_slice_x - (original_image_slice / 2)
         lowercase__   :       List[str]				=	max(0						,       a)
         lowercase__   :       List[str]				=	squeeze_tile(a						,       a						,       a						,       a)
         lowercase__   :       List[Any]				=	to_input.size
         lowercase__   :       Dict				=	to_input.resize((tile_size, tile_size)						,       Image.BICUBIC)
         lowercase__   :       Union[str, Any]				=	super(a						,       self).__call__(image=a						,       **a).images[0]
         lowercase__   :       str				=	upscaled_tile.resize((orig_input_size[0] * 4, orig_input_size[1] * 4)						,       Image.BICUBIC)
         lowercase__   :       Dict				=	unsqueeze_tile(a						,       a)
         lowercase__   :       Tuple				=	upscaled_tile.resize((tile.size[0] * 4, tile.size[1] * 4)						,       Image.BICUBIC)
         lowercase__   :       Optional[int]				=	[]
         if x == 0:
              remove_borders.append('l')
         elif crop_rect[2] == image.size[0]:
              remove_borders.append('r')
         if y == 0:
              remove_borders.append('t')
         elif crop_rect[3] == image.size[1]:
              remove_borders.append('b')
         lowercase__   :       Any				=	Image.fromarray(
             make_transparency_mask(
                 (upscaled_tile.size[0], upscaled_tile.size[1])						,       tile_border * 4						,       remove_borders=a)						,       mode='L'						,       )
         final_image.paste(
             a						,       (crop_rect_with_overlap[0] * 4, crop_rect_with_overlap[1] * 4)						,       a)





    @torch.no_grad()
    def __call__(				self						,       a						,       a						,       a = 75						,       a = 9.0						,       a = 50						,       a = None						,       a = 1						,       a = 0.0						,       a = None						,       a = None						,       a = None						,       a = 1						,       a = 128						,       a = 32						,       a = 32						,       ):
         lowercase__   :       Optional[int]				=	Image.new('RGB'						,       (image.size[0] * 4, image.size[1] * 4))
         lowercase__   :       Tuple				=	math.ceil(image.size[0] / tile_size)
         lowercase__   :       Optional[Any]				=	math.ceil(image.size[1] / tile_size)
         lowercase__   :       Union[str, Any]				=	tcx * tcy
         lowercase__   :       Union[str, Any]				=	0
         for y in range(a):
              for x in range(a):
                   self._process_tile(
                       a						,       a						,       a						,       a						,       a						,       a						,       a						,       prompt=a						,       num_inference_steps=a						,       guidance_scale=a						,       noise_level=a						,       negative_prompt=a						,       num_images_per_prompt=a						,       eta=a						,       generator=a						,       latents=a						,       )
                   current_count += 1
                   if callback is not None:
                        callback({'progress': current_count / total_tile_count, 'image': final_image})
         return final_image



def      snake_case__      (   ):



     '''simple docstring'''





     lowercase__   :       Tuple				=	'stabilityai/stable-diffusion-x4-upscaler'
     lowercase__   :       Tuple				=	StableDiffusionTiledUpscalePipeline.from_pretrained(SCREAMING_SNAKE_CASE_     ,					revision='fp16'     ,					torch_dtype=torch.floataa      )
     lowercase__   :       Dict				=	pipe.to('cuda'      )
     lowercase__   :       List[str]				=	Image.open('../../docs/source/imgs/diffusers_library.jpg'      )

     def callback(SCREAMING_SNAKE_CASE_		:   Optional[Any]      ):
          print(f"""progress: {obj["progress"]:.4f}"""      )
          obj["image"].save('diffusers_library_progress.jpg'      )

     lowercase__   :       List[str]				=	pipe(image=SCREAMING_SNAKE_CASE_     ,					prompt='Black font, white background, vector'     ,					noise_level=40     ,					callback=SCREAMING_SNAKE_CASE_      )
     final_image.save('diffusers_library.jpg'      )


if __name__ == "__main__":
       main()




def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   int      ):



     '''simple docstring'''





     return 1 if digit in (0, 1) else (digit * factorial(digit - 1      ))

def      snake_case__      (   SCREAMING_SNAKE_CASE_		:   int      ):



     '''simple docstring'''





     lowercase__   :       List[str]				=	0
     lowercase__   :       Optional[int]				=	number
     while duplicate > 0:
          lowercase__				,			lowercase__   :       Tuple				=	divmod(SCREAMING_SNAKE_CASE_     ,					10      )
          fact_sum += factorial(SCREAMING_SNAKE_CASE_      )
     return fact_sum == number


if __name__ == "__main__":
       print('''Program to check whether a number is a Krisnamurthy Number or not.''')
       snake_case_        =			int(input('''Enter number: ''').strip())
       print(
           F'''{number} is {'' if krishnamurthy(number) else 'not '}a Krishnamurthy Number.'''
       )

