

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







							'''simple docstring'''






							snake_case_          =   size[0] - overlap_pixels * 2
							snake_case_          =   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
							snake_case_          =   np.ones((size_y, size_x)       ,							dtype=np.uinta				) * 255
							snake_case_          =   np.pad(UpperCamelCase__       ,							mode='linear_ramp'       ,							pad_width=UpperCamelCase__       ,							end_values=0				)

							if "l" in remove_borders:
														snake_case_          =   mask[:, overlap_pixels : mask.shape[1]]
							if "r" in remove_borders:
														snake_case_          =   mask[:, 0 : mask.shape[1] - overlap_pixels]
							if "t" in remove_borders:
														snake_case_          =   mask[overlap_pixels : mask.shape[0], :]
							if "b" in remove_borders:
														snake_case_          =   mask[0 : mask.shape[0] - overlap_pixels, :]
							return mask





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							return max(UpperCamelCase__       ,							min(UpperCamelCase__       ,							UpperCamelCase__				)				)





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''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  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   list(UpperCamelCase__				)
							rect[0] -= overlap
							rect[1] -= overlap
							rect[2] += overlap
							rect[3] += overlap
							snake_case_          =   clamp_rect(UpperCamelCase__       ,							[0, 0]       ,							[image_size[0], image_size[1]]				)
							return rect





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   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(UpperCamelCase__       ,							(original_slice, 0)				)
							return result





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   (original_image_slice * 4, 0, tile.size[0], tile.size[1])
							snake_case_          =   tile.crop(UpperCamelCase__				)
							return tile





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   n % d
							return n - divisor







class 			lowercase    (	lowercase_      ):




				def __init__( self				,       snake_case				,       snake_case				,       snake_case				,       snake_case				,       snake_case				,       snake_case				,       snake_case = 350				,       ):
											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    a							( self				,       snake_case				,       snake_case				,       snake_case				,       snake_case				,       snake_case				,       snake_case				,       snake_case				,       **snake_case	):
											torch.manual_seed(0	)
											snake_case_          =   (
											    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	),
											)
											snake_case_          =   add_overlap_rect(snake_case				,       snake_case				,       image.size	)
											snake_case_          =   image.crop(snake_case	)
											snake_case_          =   ((crop_rect[0] + ((crop_rect[2] - crop_rect[0]) / 2)) / image.size[0]) * tile.size[0]
											snake_case_          =   translated_slice_x - (original_image_slice / 2)
											snake_case_          =   max(0				,       snake_case	)
											snake_case_          =   squeeze_tile(snake_case				,       snake_case				,       snake_case				,       snake_case	)
											snake_case_          =   to_input.size
											snake_case_          =   to_input.resize((tile_size, tile_size)				,       Image.BICUBIC	)
											snake_case_          =   super(snake_case				,       self	).__call__(image=snake_case				,       **snake_case	).images[0]
											snake_case_          =   upscaled_tile.resize((orig_input_size[0] * 4, orig_input_size[1] * 4)				,       Image.BICUBIC	)
											snake_case_          =   unsqueeze_tile(snake_case				,       snake_case	)
											snake_case_          =   upscaled_tile.resize((tile.size[0] * 4, tile.size[1] * 4)				,       Image.BICUBIC	)
											snake_case_          =   []
											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'	)
											snake_case_          =   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				,       snake_case				,       snake_case				,       snake_case = 75				,       snake_case = 9.0				,       snake_case = 50				,       snake_case = None				,       snake_case = 1				,       snake_case = 0.0				,       snake_case = None				,       snake_case = None				,       snake_case = None				,       snake_case = 1				,       snake_case = 128				,       snake_case = 32				,       snake_case = 32				,       ):
											snake_case_          =   Image.new('RGB'				,       (image.size[0] * 4, image.size[1] * 4)	)
											snake_case_          =   math.ceil(image.size[0] / tile_size	)
											snake_case_          =   math.ceil(image.size[1] / tile_size	)
											snake_case_          =   tcx * tcy
											snake_case_          =   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  __lowerCamelCase     (			):







							'''simple docstring'''






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

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

							snake_case_          =   pipe(image=UpperCamelCase__       ,							prompt='Black font, white background, vector'       ,							noise_level=40       ,							callback=UpperCamelCase__				)
							final_image.save('diffusers_library.jpg'				)


if __name__ == "__main__":
					main()







# Lint as: python3
import itertools
import os
import re


_UpperCAmelCase		:       str						    =	re.compile(R"""([A-Z]+)([A-Z][a-z])""")
_UpperCAmelCase		:       Dict						    =	re.compile(R"""([a-z\d])([A-Z])""")

_UpperCAmelCase		:       Dict						    =	re.compile(R"""(?<!_)_(?!_)""")
_UpperCAmelCase		:       Tuple						    =	re.compile(R"""(_{2,})""")

_UpperCAmelCase		:       Any						    =	R"""^\w+(\.\w+)*$"""

_UpperCAmelCase		:       List[str]						    =	R"""<>:/\|?*"""





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   _uppercase_uppercase_re.sub(r'\1_\2'       ,							UpperCamelCase__				)
							snake_case_          =   _lowercase_uppercase_re.sub(r'\1_\2'       ,							UpperCamelCase__				)
							return name.lower()





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   _single_underscore_re.split(UpperCamelCase__				)
							snake_case_          =   [_multiple_underscores_re.split(UpperCamelCase__				) for n in name]
							return "".join(n.capitalize() for n in itertools.chain.from_iterable(UpperCamelCase__				) if n != ''				)





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							if os.path.basename(UpperCamelCase__				) != name:
														raise ValueError(F'''Should be a dataset name, not a path: {name}'''				)
							return camelcase_to_snakecase(UpperCamelCase__				)





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__				):







							'''simple docstring'''






							if os.path.basename(UpperCamelCase__				) != name:
														raise ValueError(F'''Should be a dataset name, not a path: {name}'''				)
							if not re.match(_split_re       ,							UpperCamelCase__				):
														raise ValueError(F'''Split name should match \'{_split_re}\'\' but got \'{split}\'.'''				)
							return F'''{filename_prefix_for_name(UpperCamelCase__				)}-{split}'''





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__=None				):







							'''simple docstring'''






							snake_case_          =   filename_prefix_for_split(UpperCamelCase__       ,							UpperCamelCase__				)
							if filetype_suffix:
														prefix += F'''.{filetype_suffix}'''
							snake_case_          =   os.path.join(UpperCamelCase__       ,							UpperCamelCase__				)
							return F'''{filepath}*'''





def  __lowerCamelCase     (			UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__       ,							UpperCamelCase__=None       ,							UpperCamelCase__=None				):







							'''simple docstring'''






							snake_case_          =   filename_prefix_for_split(UpperCamelCase__       ,							UpperCamelCase__				)
							snake_case_          =   os.path.join(UpperCamelCase__       ,							UpperCamelCase__				)

							if shard_lengths:
														snake_case_          =   len(UpperCamelCase__				)
														snake_case_          =   [F'''{prefix}-{shard_id:05d}-of-{num_shards:05d}''' for shard_id in range(UpperCamelCase__				)]
														if filetype_suffix:
																					snake_case_          =   [filename + F'''.{filetype_suffix}''' for filename in filenames]
														return filenames
							else:
														snake_case_          =   prefix
														if filetype_suffix:
																					filename += F'''.{filetype_suffix}'''
														return [filename]




