code: 
  """simple docstring"""
  
  
  
  
  
  from typing import List, Optional, Tuple, Union
  
  import torch
  
  from ...models import UNetaDModel
  from ...schedulers import PNDMScheduler
  from ...utils import randn_tensor
  from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
  
  
  class A_			(lowercase__   ):
  
  
  
  
    '''simple docstring'''
    SCREAMING_SNAKE_CASE__    :		UNetaDModel
    SCREAMING_SNAKE_CASE__    :		PNDMScheduler
  
  
  
  
  
  
  
    def __init__(	self       ,     lowercase_       ,     lowercase_						):
  
       """simple docstring"""
       super().__init__()
  
       UpperCAmelCase_      :      Tuple      =					PNDMScheduler.from_config(scheduler.config						)
  
       self.register_modules(unet=lowercase_       ,     scheduler=lowercase_						)
  
  
  
  
  
  
  
    @torch.no_grad()
    def __call__(	self       ,     lowercase_ = 1       ,     lowercase_ = 50       ,     lowercase_ = None       ,     lowercase_ = "pil"       ,     lowercase_ = True       ,     **lowercase_       ,     ):
  
       """simple docstring"""
       UpperCAmelCase_      :      Optional[int]      =					randn_tensor(
           (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)       ,     generator=lowercase_       ,     device=self.device       ,     )
  
       self.scheduler.set_timesteps(lowercase_						)
       for t in self.progress_bar(self.scheduler.timesteps						):
          UpperCAmelCase_      :      Optional[int]      =					self.unet(lowercase_       ,     lowercase_						).sample
  
          UpperCAmelCase_      :      Union[str, Any]      =					self.scheduler.step(lowercase_       ,     lowercase_       ,     lowercase_						).prev_sample
  
       UpperCAmelCase_      :      Optional[int]      =					(image / 2 + 0.5).clamp(0       ,     1						)
       UpperCAmelCase_      :      List[Any]      =					image.cpu().permute(0       ,     2       ,     3       ,     1						).numpy()
       if output_type == "pil":
          UpperCAmelCase_      :      Union[str, Any]      =					self.numpy_to_pil(lowercase_						)
  
       if not return_dict:
          return (image,)
  
       return ImagePipelineOutput(images=lowercase_						)
  
  
  
style_context: 
  """simple docstring"""
  
  
  
  
  
  from __future__ import annotations
  
  from typing import Any
  
  
  class A_			:
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    def __init__(	self       ,     lowercase_       ,     lowercase_						):  # noqa: A002
  
       """simple docstring"""
       UpperCAmelCase_      :      Optional[Any]      =					item
       UpperCAmelCase_      :      Optional[Any]      =					next
  
  
  
  
  class A_			:
  
  
  
  
    '''simple docstring'''
  
  
  
  
  
  
  
    def __init__(	self						):
  
       """simple docstring"""
       UpperCAmelCase_      :      Node | None      =					None
       UpperCAmelCase_      :      Optional[int]      =					0
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self       ,     lowercase_						):
  
       """simple docstring"""
       UpperCAmelCase_      :      int      =					Node(lowercase_       ,     self.head						)
       self.size += 1
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       # Switched 'self.is_empty()' to 'self.head is None'
       # because mypy was considering the possibility that 'self.head'
       # can be None in below else part and giving error
       if self.head is None:
          return None
       else:
          UpperCAmelCase_      :      int      =					self.head.item
          UpperCAmelCase_      :      str      =					self.head.next
          self.size -= 1
          return item
  
  
  
  
  
  
  
    def  UpperCamelCase__      (	self						):
  
       """simple docstring"""
       return self.head is None
  
  
  
  
  
  
  
    def __str__(	self						):
  
       """simple docstring"""
       if self.is_empty():
          return ""
       else:
          UpperCAmelCase_      :      str      =					self.head
          UpperCAmelCase_      :      str      =					""
          UpperCAmelCase_      :      list[str]      =					[]
          while iterate:
             item_list.append(str(iterate.item						)						)
             UpperCAmelCase_      :      Tuple      =					iterate.next
  
          UpperCAmelCase_      :      Optional[Any]      =					" --> ".join(lowercase_						)
  
          return item_str
  
  
  
  
  
  
  
    def __len__(	self						):
  
       """simple docstring"""
       return self.size
  
  
  