





"""simple docstring"""





from typing import Any, Callable, Dict, List, Optional, Union

import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer

from diffusers import (
    AutoencoderKL,
    DDIMScheduler,
    DiffusionPipeline,
    LMSDiscreteScheduler,
    PNDMScheduler,
    StableDiffusionImgaImgPipeline,
    StableDiffusionInpaintPipelineLegacy,
    StableDiffusionPipeline,
    UNetaDConditionModel,
)
from diffusers.configuration_utils import FrozenDict
from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
from diffusers.utils import deprecate, logging


_lowerCamelCase  					=     logging.get_logger(__name__)  # pylint: disable=invalid-name





class       snake_case		(       SCREAMING_SNAKE_CASE_       ):
      lowerCamelCase__      =			["safety_checker", "feature_extractor"]

      def __init__(      self       :int						,							_lowerCamelCase       :int						,							_lowerCamelCase       :Dict						,							_lowerCamelCase       :Optional[int]						,							_lowerCamelCase       :Tuple						,							_lowerCamelCase       :Optional[int]						,							_lowerCamelCase       :List[str]						,							_lowerCamelCase       :int						,							_lowerCamelCase       :Optional[Any] = True						,							):
       super().__init__()
       if hasattr(scheduler.config						,							'''steps_offset'''						) and scheduler.config.steps_offset != 1:
        __SCREAMING_SNAKE_CASE			:      str 							=	(
            f'''The configuration file of this scheduler: {scheduler} is outdated. `steps_offset`'''
            f''' should be set to 1 instead of {scheduler.config.steps_offset}. Please make sure '''
            '''to update the config accordingly as leaving `steps_offset` might led to incorrect results'''
            ''' in future versions. If you have downloaded this checkpoint from the Hugging Face Hub,'''
            ''' it would be very nice if you could open a Pull request for the `scheduler/scheduler_config.json`'''
            ''' file'''
        )
        deprecate('''steps_offset!=1'''						,							'''1.0.0'''						,							lowercase_						,							standard_warn=lowercase_						)
        __SCREAMING_SNAKE_CASE			:      Union[str, Any] 							=	dict(scheduler.config						)
        __SCREAMING_SNAKE_CASE			:      List[Any] 							=	1
        __SCREAMING_SNAKE_CASE			:      Tuple 							=	FrozenDict(lowercase_						)

       self.register_modules(
           vae=lowercase_						,							text_encoder=lowercase_						,							tokenizer=lowercase_						,							unet=lowercase_						,							scheduler=lowercase_						,							safety_checker=lowercase_						,							feature_extractor=lowercase_						,							)
       self.register_to_config(requires_safety_checker=lowercase_						)

      @property
      def 						SCREAMING_SNAKE_CASE_      (      self       :Tuple						):
       return {k: getattr(self						,							lowercase_						) for k in self.config.keys() if not k.startswith('''_'''						)}

      def 						SCREAMING_SNAKE_CASE_      (      self       :Optional[Any]						,							_lowerCamelCase       :Union[str, Any] = "auto"						):
       if slice_size == "auto":
        # half the attention head size is usually a good trade-off between
        # speed and memory
        __SCREAMING_SNAKE_CASE			:      int 							=	self.unet.config.attention_head_dim // 2
       self.unet.set_attention_slice(lowercase_						)

      def 						SCREAMING_SNAKE_CASE_      (      self       :List[str]						):
       self.enable_attention_slicing(lowercase_						)

      @torch.no_grad()
      def 						SCREAMING_SNAKE_CASE_      (      self       :Optional[Any]						,							_lowerCamelCase       :Any						,							_lowerCamelCase       :str						,							_lowerCamelCase       :Dict						,							_lowerCamelCase       :Any = 0.8						,							_lowerCamelCase       :Dict = 5_0						,							_lowerCamelCase       :Optional[int] = 7.5						,							_lowerCamelCase       :List[Any] = None						,							_lowerCamelCase       :str = 1						,							_lowerCamelCase       :Any = 0.0						,							_lowerCamelCase       :Tuple = None						,							_lowerCamelCase       :List[Any] = "pil"						,							_lowerCamelCase       :Tuple = True						,							_lowerCamelCase       :Optional[int] = None						,							_lowerCamelCase       :Tuple = 1						,							):
       # For more information on how this function works, please see: https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion#diffusers.StableDiffusionImg2ImgPipeline
       return StableDiffusionInpaintPipelineLegacy(**self.components						)(
           prompt=lowercase_						,							image=lowercase_						,							mask_image=lowercase_						,							strength=lowercase_						,							num_inference_steps=lowercase_						,							guidance_scale=lowercase_						,							negative_prompt=lowercase_						,							num_images_per_prompt=lowercase_						,							eta=lowercase_						,							generator=lowercase_						,							output_type=lowercase_						,							return_dict=lowercase_						,							callback=lowercase_						,							)

      @torch.no_grad()
      def 						SCREAMING_SNAKE_CASE_      (      self       :str						,							_lowerCamelCase       :List[Any]						,							_lowerCamelCase       :Union[str, Any]						,							_lowerCamelCase       :int = 0.8						,							_lowerCamelCase       :List[str] = 5_0						,							_lowerCamelCase       :Tuple = 7.5						,							_lowerCamelCase       :int = None						,							_lowerCamelCase       :Optional[int] = 1						,							_lowerCamelCase       :Union[str, Any] = 0.0						,							_lowerCamelCase       :List[str] = None						,							_lowerCamelCase       :List[str] = "pil"						,							_lowerCamelCase       :Dict = True						,							_lowerCamelCase       :Dict = None						,							_lowerCamelCase       :Any = 1						,							**_lowerCamelCase       :str						,							):
       # For more information on how this function works, please see: https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion#diffusers.StableDiffusionImg2ImgPipeline
       return StableDiffusionImgaImgPipeline(**self.components						)(
           prompt=lowercase_						,							image=lowercase_						,							strength=lowercase_						,							num_inference_steps=lowercase_						,							guidance_scale=lowercase_						,							negative_prompt=lowercase_						,							num_images_per_prompt=lowercase_						,							eta=lowercase_						,							generator=lowercase_						,							output_type=lowercase_						,							return_dict=lowercase_						,							callback=lowercase_						,							callback_steps=lowercase_						,							)



      @torch.no_grad()
      def 						SCREAMING_SNAKE_CASE_      (      self       :List[str]						,							_lowerCamelCase       :str						,							_lowerCamelCase       :Optional[Any] = 5_1_2						,							_lowerCamelCase       :List[Any] = 5_1_2						,							_lowerCamelCase       :Optional[Any] = 5_0						,							_lowerCamelCase       :Optional[int] = 7.5						,							_lowerCamelCase       :Any = None						,							_lowerCamelCase       :Tuple = 1						,							_lowerCamelCase       :Dict = 0.0						,							_lowerCamelCase       :List[str] = None						,							_lowerCamelCase       :List[Any] = None						,							_lowerCamelCase       :Optional[Any] = "pil"						,							_lowerCamelCase       :Optional[int] = True						,							_lowerCamelCase       :Dict = None						,							_lowerCamelCase       :Any = 1						,							):
       # For more information on how this function https://huggingface.co/docs/diffusers/api/pipelines/stable_diffusion#diffusers.StableDiffusionPipeline
       return StableDiffusionPipeline(**self.components						)(
           prompt=lowercase_						,							height=lowercase_						,							width=lowercase_						,							num_inference_steps=lowercase_						,							guidance_scale=lowercase_						,							negative_prompt=lowercase_						,							num_images_per_prompt=lowercase_						,							eta=lowercase_						,							generator=lowercase_						,							latents=lowercase_						,							output_type=lowercase_						,							return_dict=lowercase_						,							callback=lowercase_						,							callback_steps=lowercase_						,							)








"""simple docstring"""





import math





class       snake_case		:

      def __init__(      self       :Optional[Any]						,							_lowerCamelCase       :Dict						):
       __SCREAMING_SNAKE_CASE			:      str 							=	len(_lowerCamelCase						)
       __SCREAMING_SNAKE_CASE			:      Optional[int] 							=	[0] * (
           4 * self.N
       )  # approximate the overall size of segment tree with array N
       self.build(1						,							0						,							self.N - 1						)

      def 						SCREAMING_SNAKE_CASE_      (      self       :Union[str, Any]						,							_lowerCamelCase       :List[str]						):
       return idx * 2

      def 						SCREAMING_SNAKE_CASE_      (      self       :Tuple						,							_lowerCamelCase       :Optional[Any]						):
       return idx * 2 + 1

      def 						SCREAMING_SNAKE_CASE_      (      self       :int						,							_lowerCamelCase       :Optional[Any]						,							_lowerCamelCase       :Union[str, Any]						,							_lowerCamelCase       :str						):  # noqa: E741
       if l == r:
        __SCREAMING_SNAKE_CASE			:      Union[str, Any] 							=	A[l]
       else:
        __SCREAMING_SNAKE_CASE			:      Dict 							=	(l + r) // 2
        self.build(self.left(_lowerCamelCase						)						,							_lowerCamelCase						,							_lowerCamelCase						)
        self.build(self.right(_lowerCamelCase						)						,							mid + 1						,							_lowerCamelCase						)
        __SCREAMING_SNAKE_CASE			:      List[Any] 							=	max(self.st[self.left(_lowerCamelCase						)]						,							self.st[self.right(_lowerCamelCase						)]						)

      def 						SCREAMING_SNAKE_CASE_      (      self       :Tuple						,							_lowerCamelCase       :Optional[Any]						,							_lowerCamelCase       :Optional[Any]						,							_lowerCamelCase       :Union[str, Any]						):
       return self.update_recursive(1						,							0						,							self.N - 1						,							a - 1						,							b - 1						,							_lowerCamelCase						)

      def 						SCREAMING_SNAKE_CASE_      (      self       :Optional[int]						,							_lowerCamelCase       :Optional[Any]						,							_lowerCamelCase       :Any						,							_lowerCamelCase       :Union[str, Any]						,							_lowerCamelCase       :Optional[Any]						,							_lowerCamelCase       :str						,							_lowerCamelCase       :Optional[Any]						):  # noqa: E741
       if r < a or l > b:
        return True
       if l == r:
        __SCREAMING_SNAKE_CASE			:      Union[str, Any] 							=	val
        return True
       __SCREAMING_SNAKE_CASE			:      List[Any] 							=	(l + r) // 2
       self.update_recursive(self.left(_lowerCamelCase						)						,							_lowerCamelCase						,							_lowerCamelCase						,							_lowerCamelCase						,							_lowerCamelCase						,							_lowerCamelCase						)
       self.update_recursive(self.right(_lowerCamelCase						)						,							mid + 1						,							_lowerCamelCase						,							_lowerCamelCase						,							_lowerCamelCase						,							_lowerCamelCase						)
       __SCREAMING_SNAKE_CASE			:      Union[str, Any] 							=	max(self.st[self.left(_lowerCamelCase						)]						,							self.st[self.right(_lowerCamelCase						)]						)
       return True

      def 						SCREAMING_SNAKE_CASE_      (      self       :Tuple						,							_lowerCamelCase       :str						,							_lowerCamelCase       :Any						):
       return self.query_recursive(1						,							0						,							self.N - 1						,							a - 1						,							b - 1						)

      def 						SCREAMING_SNAKE_CASE_      (      self       :str						,							_lowerCamelCase       :Dict						,							_lowerCamelCase       :str						,							_lowerCamelCase       :Union[str, Any]						,							_lowerCamelCase       :Optional[Any]						,							_lowerCamelCase       :Any						):  # noqa: E741
       if r < a or l > b:
        return -math.inf
       if l >= a and r <= b:
        return self.st[idx]
       __SCREAMING_SNAKE_CASE			:      List[str] 							=	(l + r) // 2
       __SCREAMING_SNAKE_CASE			:      Any 							=	self.query_recursive(self.left(_lowerCamelCase						)						,							_lowerCamelCase						,							_lowerCamelCase						,							_lowerCamelCase						,							_lowerCamelCase						)
       __SCREAMING_SNAKE_CASE			:      Optional[int] 							=	self.query_recursive(self.right(_lowerCamelCase						)						,							mid + 1						,							_lowerCamelCase						,							_lowerCamelCase						,							_lowerCamelCase						)
       return max(_lowerCamelCase						,							_lowerCamelCase						)



      def 						SCREAMING_SNAKE_CASE_      (      self       :Dict						):
       __SCREAMING_SNAKE_CASE			:      str 							=	[]
       for i in range(1						,							N + 1						):
        show_list += [self.query(_lowerCamelCase						,							_lowerCamelCase						)]
       print(_lowerCamelCase						)


if __name__ == "__main__":
    _lowerCamelCase  					=     [1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
    _lowerCamelCase  					=     15
    _lowerCamelCase  					=     SegmentTree(A)
    print(segt.query(4, 6))
    print(segt.query(7, 11))
    print(segt.query(7, 12))
    segt.update(1, 3, 1_11)
    print(segt.query(1, 15))
    segt.update(7, 8, 2_35)
    segt.show_data()

