





'''simple docstring'''






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    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase							,	lowerCAmelCase=[]  ):





      """simple docstring"""


      _lowerCAmelCase							     =							size[0] - overlap_pixels * 2
      _lowerCAmelCase							     =							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
      _lowerCAmelCase							     =							np.ones((size_y, size_x)							,	dtype=np.uinta  ) * 2_55
      _lowerCAmelCase							     =							np.pad(lowerCAmelCase							,	mode="""linear_ramp"""							,	pad_width=lowerCAmelCase							,	end_values=0  )

      if "l" in remove_borders:
            _lowerCAmelCase							     =							mask[:, overlap_pixels : mask.shape[1]]
      if "r" in remove_borders:
            _lowerCAmelCase							     =							mask[:, 0 : mask.shape[1] - overlap_pixels]
      if "t" in remove_borders:
            _lowerCAmelCase							     =							mask[overlap_pixels : mask.shape[0], :]
      if "b" in remove_borders:
            _lowerCAmelCase							     =							mask[0 : mask.shape[0] - overlap_pixels, :]
      return mask
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      return max(lowerCAmelCase							,	min(lowerCAmelCase							,	lowerCAmelCase  )  )
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase							,	lowerCAmelCase  ):





      """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    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase							     =							list(lowerCAmelCase  )
      rect[0] -= overlap
      rect[1] -= overlap
      rect[2] += overlap
      rect[3] += overlap
      _lowerCAmelCase							     =							clamp_rect(lowerCAmelCase							,	[0, 0]							,	[image_size[0], image_size[1]]  )
      return rect
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase							,	lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase							     =							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(lowerCAmelCase							,	(original_slice, 0)  )
      return result
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase							     =							(original_image_slice * 4, 0, tile.size[0], tile.size[1])
      _lowerCAmelCase							     =							tile.crop(lowerCAmelCase  )
      return tile
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase							     =							n % d
      return n - divisor




class  UpperCAmelCase     (			snake_case_   ):




      def __init__(			self			: List[Any]			,			__snake_case			: AutoencoderKL			,			__snake_case			: CLIPTextModel			,			__snake_case			: CLIPTokenizer			,			__snake_case			: UNetaDConditionModel			,			__snake_case			: DDPMScheduler			,			__snake_case			: Union[DDIMScheduler, PNDMScheduler, LMSDiscreteScheduler]			,			__snake_case			: int = 3_50			,			)				->      int:
            super().__init__(
                vae=__snake_case			,			text_encoder=__snake_case			,			tokenizer=__snake_case			,			unet=__snake_case			,			low_res_scheduler=__snake_case			,			scheduler=__snake_case			,			max_noise_level=__snake_case			,			)




      def 				lowercase__    (			self			: List[Any]			,			__snake_case			: List[Any]			,			__snake_case			: List[Any]			,			__snake_case			: Dict			,			__snake_case			: List[Any]			,			__snake_case			: int			,			__snake_case			: Optional[Any]			,			__snake_case			: Any			,			**__snake_case			: str  )				->      int:
            torch.manual_seed(0  )
            _lowerCAmelCase							     =							(
                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  ),
            )
            _lowerCAmelCase							     =							add_overlap_rect(__snake_case			,			__snake_case			,			image.size  )
            _lowerCAmelCase							     =							image.crop(__snake_case  )
            _lowerCAmelCase							     =							((crop_rect[0] + ((crop_rect[2] - crop_rect[0]) / 2)) / image.size[0]) * tile.size[0]
            _lowerCAmelCase							     =							translated_slice_x - (original_image_slice / 2)
            _lowerCAmelCase							     =							max(0			,			__snake_case  )
            _lowerCAmelCase							     =							squeeze_tile(__snake_case			,			__snake_case			,			__snake_case			,			__snake_case  )
            _lowerCAmelCase							     =							to_input.size
            _lowerCAmelCase							     =							to_input.resize((tile_size, tile_size)			,			Image.BICUBIC  )
            _lowerCAmelCase							     =							super(__snake_case			,			self  ).__call__(image=__snake_case			,			**__snake_case  ).images[0]
            _lowerCAmelCase							     =							upscaled_tile.resize((orig_input_size[0] * 4, orig_input_size[1] * 4)			,			Image.BICUBIC  )
            _lowerCAmelCase							     =							unsqueeze_tile(__snake_case			,			__snake_case  )
            _lowerCAmelCase							     =							upscaled_tile.resize((tile.size[0] * 4, tile.size[1] * 4)			,			Image.BICUBIC  )
            _lowerCAmelCase							     =							[]
            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"""  )
            _lowerCAmelCase							     =							Image.fromarray(
                make_transparency_mask(
                    (upscaled_tile.size[0], upscaled_tile.size[1])			,			tile_border * 4			,			remove_borders=__snake_case  )			,			mode="""L"""			,			)
            final_image.paste(
                __snake_case			,			(crop_rect_with_overlap[0] * 4, crop_rect_with_overlap[1] * 4)			,			__snake_case  )




      @torch.no_grad()
      def __call__(			self			: Union[str, Any]			,			__snake_case			: Union[str, List[str]]			,			__snake_case			: Union[PIL.Image.Image, List[PIL.Image.Image]]			,			__snake_case			: int = 75			,			__snake_case			: float = 9.0			,			__snake_case			: int = 50			,			__snake_case			: Optional[Union[str, List[str]]] = None			,			__snake_case			: Optional[int] = 1			,			__snake_case			: float = 0.0			,			__snake_case			: Optional[torch.Generator] = None			,			__snake_case			: Optional[torch.FloatTensor] = None			,			__snake_case			: Optional[Callable[[int, int, torch.FloatTensor], None]] = None			,			__snake_case			: int = 1			,			__snake_case			: int = 1_28			,			__snake_case			: int = 32			,			__snake_case			: int = 32			,			)				->      str:
            _lowerCAmelCase							     =							Image.new("""RGB"""			,			(image.size[0] * 4, image.size[1] * 4)  )
            _lowerCAmelCase							     =							math.ceil(image.size[0] / tile_size  )
            _lowerCAmelCase							     =							math.ceil(image.size[1] / tile_size  )
            _lowerCAmelCase							     =							tcx * tcy
            _lowerCAmelCase							     =							0
            for y in range(__snake_case  ):
                  for x in range(__snake_case  ):
                        self._process_tile(
                            __snake_case			,			__snake_case			,			__snake_case			,			__snake_case			,			__snake_case			,			__snake_case			,			__snake_case			,			prompt=__snake_case			,			num_inference_steps=__snake_case			,			guidance_scale=__snake_case			,			noise_level=__snake_case			,			negative_prompt=__snake_case			,			num_images_per_prompt=__snake_case			,			eta=__snake_case			,			generator=__snake_case			,			latents=__snake_case			,			)
                        current_count += 1
                        if callback is not None:
                              callback({"""progress""": current_count / total_tile_count, """image""": final_image}  )
            return final_image




def    UpperCamelCase__      (		):





      """simple docstring"""


      _lowerCAmelCase							     =							"""stabilityai/stable-diffusion-x4-upscaler"""
      _lowerCAmelCase							     =							StableDiffusionTiledUpscalePipeline.from_pretrained(lowerCAmelCase							,	revision="""fp16"""							,	torch_dtype=torch.floataa  )
      _lowerCAmelCase							     =							pipe.to("""cuda"""  )
      _lowerCAmelCase							     =							Image.open("""../../docs/source/imgs/diffusers_library.jpg"""  )

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

      _lowerCAmelCase							     =							pipe(image=lowerCAmelCase							,	prompt="""Black font, white background, vector"""							,	noise_level=40							,	callback=lowerCAmelCase  )
      final_image.save("""diffusers_library.jpg"""  )


if __name__ == "__main__":
      main()











'''simple docstring'''






class 							lowercase       :


 """simple docstring"""


 def __init__(							self							)		->   List[str]:
        _UpperCAmelCase  :						int			     = 0
        _UpperCAmelCase  :						Union[str, Any]			     = 0
        _UpperCAmelCase  :						Optional[int]			     = {}







 def _snake_case (							self  ,a_							)		->   Optional[Any]:
        if vertex not in self.adjacency:
               _UpperCAmelCase  :						int			     = {}
               self.num_vertices += 1







 def _snake_case (							self  ,a_  ,a_  ,a_							)		->   int:
        self.add_vertex(a_							)
        self.add_vertex(a_							)

        if head == tail:
               return

        _UpperCAmelCase  :						List[Any]			     = weight
        _UpperCAmelCase  :						Dict			     = weight







 def _snake_case (							self							)		->   Dict:
        _UpperCAmelCase  :						Optional[int]			     = self.get_edges()
        for edge in edges:
               _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						Dict			     = edge
               edges.remove((tail, head, weight)							)
        for i in range(len(a_							)							):
               _UpperCAmelCase  :						str			     = list(edges[i]							)

        edges.sort(key=lambda a_							: e[2]							)
        for i in range(len(a_							) - 1							):
               if edges[i][2] >= edges[i + 1][2]:
                      _UpperCAmelCase  :						Optional[Any]			     = edges[i][2] + 1
        for edge in edges:
               _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						Union[str, Any]			     = edge
               _UpperCAmelCase  :						str			     = weight
               _UpperCAmelCase  :						List[str]			     = weight







 def __str__(							self							)		->   Any:
        _UpperCAmelCase  :						List[Any]			     = """"""
        for tail in self.adjacency:
               for head in self.adjacency[tail]:
                      _UpperCAmelCase  :						List[str]			     = self.adjacency[head][tail]
                      string += f'''{head} -> {tail} == {weight}\n'''
        return string.rstrip("""\n"""							)







 def _snake_case (							self							)		->   str:
        _UpperCAmelCase  :						int			     = []
        for tail in self.adjacency:
               for head in self.adjacency[tail]:
                      output.append((tail, head, self.adjacency[head][tail])							)
        return output







 def _snake_case (							self							)		->   Optional[int]:
        return self.adjacency.keys()







 @staticmethod
 def _snake_case (							a_=None  ,a_=None							)		->   Tuple:
        _UpperCAmelCase  :						List[Any]			     = Graph()
        if vertices is None:
               _UpperCAmelCase  :						List[str]			     = []
        if edges is None:
               _UpperCAmelCase  :						Optional[Any]			     = []
        for vertex in vertices:
               g.add_vertex(a_							)
        for edge in edges:
               g.add_edge(*a_							)
        return g



 class 							lowercase       :


  """simple docstring"""


  def __init__(							self							)		->   int:
         _UpperCAmelCase  :						List[str]			     = {}
         _UpperCAmelCase  :						int			     = {}







  def __len__(							self							)		->   Tuple:
         return len(self.parent							)







  def _snake_case (							self  ,a_							)		->   str:
         if item in self.parent:
                return self.find(a_							)

         _UpperCAmelCase  :						Optional[Any]			     = item
         _UpperCAmelCase  :						List[Any]			     = 0
         return item







  def _snake_case (							self  ,a_							)		->   List[str]:
         if item not in self.parent:
                return self.make_set(a_							)
         if item != self.parent[item]:
                _UpperCAmelCase  :						List[Any]			     = self.find(self.parent[item]							)
         return self.parent[item]







  def _snake_case (							self  ,a_  ,a_							)		->   Union[str, Any]:
         _UpperCAmelCase  :						Any			     = self.find(a_							)
         _UpperCAmelCase  :						List[str]			     = self.find(a_							)

         if roota == roota:
                return roota

         if self.rank[roota] > self.rank[roota]:
                _UpperCAmelCase  :						Any			     = roota
                return roota

         if self.rank[roota] < self.rank[roota]:
                _UpperCAmelCase  :						Any			     = roota
                return roota

         if self.rank[roota] == self.rank[roota]:
                self.rank[roota] += 1
                _UpperCAmelCase  :						List[str]			     = roota
                return roota
         return None







 @staticmethod
 def _snake_case (							a_							)		->   List[Any]:
        _UpperCAmelCase  :						int			     = graph.num_vertices

        _UpperCAmelCase  :						int			     = Graph.UnionFind()
        _UpperCAmelCase  :						Optional[int]			     = []
        while num_components > 1:
               _UpperCAmelCase  :						int			     = {}
               for vertex in graph.get_vertices():
                      _UpperCAmelCase  :						Union[str, Any]			     = -1

               _UpperCAmelCase  :						Tuple			     = graph.get_edges()
               for edge in edges:
                      _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						str			     = edge
                      edges.remove((tail, head, weight)							)
               for edge in edges:
                      _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						Optional[Any]			     = edge
                      _UpperCAmelCase  :						Any			     = union_find.find(a_							)
                      _UpperCAmelCase  :						Any			     = union_find.find(a_							)
                      if seta != seta:
                             if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                                    _UpperCAmelCase  :						Tuple			     = [head, tail, weight]

                             if cheap_edge[seta] == -1 or cheap_edge[seta][2] > weight:
                                    _UpperCAmelCase  :						List[str]			     = [head, tail, weight]
               for vertex in cheap_edge:
                      if cheap_edge[vertex] != -1:
                             _UpperCAmelCase     ,_UpperCAmelCase     ,_UpperCAmelCase  :						str			     = cheap_edge[vertex]
                             if union_find.find(a_							) != union_find.find(a_							):
                                    union_find.union(a_  ,a_							)
                                    mst_edges.append(cheap_edge[vertex]							)
                                    _UpperCAmelCase  :						Tuple			     = num_components - 1
        _UpperCAmelCase  :						Optional[int]			     = Graph.build(edges=a_							)
        return mst



