




from __future__ import annotations

from collections.abc import Callable
from typing import Generic, TypeVar

_A     =			TypeVar('''T''')
_A     =			TypeVar('''U''')


class  A		(  Generic[T, U]     ):



		def __init__(     self,	UpperCamelCase__,	UpperCamelCase__   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  key
								lowerCAmelCase_      			=  val
								lowerCAmelCase_      			=  None
								lowerCAmelCase_      			=  None







		def __repr__(     self   ):







								"""simple docstring"""



								return (
								    f"Node: key: {self.key}, val: {self.val}, "
								    f"has next: {bool(self.next   )}, has prev: {bool(self.prev   )}"
								)







class  A		(  Generic[T, U]     ):



		def __init__(     self   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  DoubleLinkedListNode(UpperCamelCase__,	UpperCamelCase__   )
								lowerCAmelCase_      			=  DoubleLinkedListNode(UpperCamelCase__,	UpperCamelCase__   )
								lowerCAmelCase_			,					lowerCAmelCase_      			=  self.rear, self.head



		def __repr__(     self   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  ['''DoubleLinkedList''']
								lowerCAmelCase_      			=  self.head
								while node.next is not None:
														rep.append(str(UpperCamelCase__   )   )
														lowerCAmelCase_      			=  node.next
								rep.append(str(self.rear   )   )
								return ",\n    ".join(UpperCamelCase__   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  self.rear.prev

								# All nodes other than self.head are guaranteed to have non-None previous
								assert previous is not None

								lowerCAmelCase_      			=  node
								lowerCAmelCase_      			=  previous
								lowerCAmelCase_      			=  node
								lowerCAmelCase_      			=  self.rear







		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								if node.prev is None or node.next is None:
														return None

								lowerCAmelCase_      			=  node.next
								lowerCAmelCase_      			=  node.prev
								lowerCAmelCase_      			=  None
								lowerCAmelCase_      			=  None
								return node







class  A		(  Generic[T, U]     ):
		__snake_case									=   {}



		def __init__(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  DoubleLinkedList()
								lowerCAmelCase_      			=  capacity
								lowerCAmelCase_      			=  0
								lowerCAmelCase_      			=  0
								lowerCAmelCase_      			=  0
								lowerCAmelCase_      			=  {}



		def __repr__(     self   ):







								"""simple docstring"""



								return (
								    f"CacheInfo(hits={self.hits}, misses={self.miss}, "
								    f"capacity={self.capacity}, current size={self.num_keys})"
								)



		def __contains__(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								return key in self.cache



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								if key in self.cache:
														self.hits += 1
														lowerCAmelCase_      			=  self.cache[key]
														lowerCAmelCase_      			=  self.list.remove(self.cache[key]   )
														assert node == value_node

														# node is guaranteed not None because it is in self.cache
														assert node is not None
														self.list.add(UpperCamelCase__   )
														return node.val
								self.miss += 1
								return None



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__   ):







								"""simple docstring"""



								if key not in self.cache:
														if self.num_keys >= self.capacity:
																				# delete first node (oldest) when over capacity
																				lowerCAmelCase_      			=  self.list.head.next

																				# guaranteed to have a non-None first node when num_keys > 0
																				# explain to type checker via assertions
																				assert first_node is not None
																				assert first_node.key is not None
																				assert (
																				    self.list.remove(UpperCamelCase__   ) is not None
																				)  # node guaranteed to be in list assert node.key is not None

																				del self.cache[first_node.key]
																				self.num_keys -= 1
														lowerCAmelCase_      			=  DoubleLinkedListNode(UpperCamelCase__,	UpperCamelCase__   )
														self.list.add(self.cache[key]   )
														self.num_keys += 1

								else:
														# bump node to the end of the list, update value
														lowerCAmelCase_      			=  self.list.remove(self.cache[key]   )
														assert node is not None  # node guaranteed to be in list
														lowerCAmelCase_      			=  value
														self.list.add(UpperCamelCase__   )







		@classmethod
		def        SCREAMING_SNAKE_CASE__			(     cls,	UpperCamelCase__ = 128   ):







								"""simple docstring"""



								def cache_decorator_inner(UpperCamelCase__   ) -> Callable[..., U]:
														def cache_decorator_wrapper(*UpperCamelCase__   ) -> U:
																				if func not in cls.decorator_function_to_instance_map:
																										lowerCAmelCase_      			=  LRUCache(UpperCamelCase__   )

																				lowerCAmelCase_      			=  cls.decorator_function_to_instance_map[func].get(args[0]   )
																				if result is None:
																										lowerCAmelCase_      			=  func(*UpperCamelCase__   )
																										cls.decorator_function_to_instance_map[func].put(args[0],	UpperCamelCase__   )
																				return result

														def cache_info() -> LRUCache[T, U]:
																				return cls.decorator_function_to_instance_map[func]

														setattr(UpperCamelCase__,	'''cache_info''',	UpperCamelCase__   )  # noqa: B010

														return cache_decorator_wrapper

								return cache_decorator_inner


if __name__ == "__main__":
						import doctest

						doctest.testmod()










import unittest

import numpy as np
import torch

from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device


enable_full_determinism()


class  A		(  unittest.TestCase     ):



		@property
		def        SCREAMING_SNAKE_CASE__			(     self   ):







								"""simple docstring"""



								torch.manual_seed(0   )
								lowerCAmelCase_      			=  UNetaDModel(
								    block_out_channels=(32, 64),	layers_per_block=2,	sample_size=32,	in_channels=3,	out_channels=3,	down_block_types=('''DownBlock2D''', '''AttnDownBlock2D'''),	up_block_types=('''AttnUpBlock2D''', '''UpBlock2D'''),	)
								return model







		def        SCREAMING_SNAKE_CASE__			(     self   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  self.dummy_uncond_unet
								lowerCAmelCase_      			=  KarrasVeScheduler()

								lowerCAmelCase_      			=  KarrasVePipeline(unet=UpperCamelCase__,	scheduler=UpperCamelCase__   )
								pipe.to(UpperCamelCase__   )
								pipe.set_progress_bar_config(disable=UpperCamelCase__   )

								lowerCAmelCase_      			=  torch.manual_seed(0   )
								lowerCAmelCase_      			=  pipe(num_inference_steps=2,	generator=UpperCamelCase__,	output_type='''numpy'''   ).images

								lowerCAmelCase_      			=  torch.manual_seed(0   )
								lowerCAmelCase_      			=  pipe(num_inference_steps=2,	generator=UpperCamelCase__,	output_type='''numpy''',	return_dict=UpperCamelCase__   )[0]

								lowerCAmelCase_      			=  image[0, -3:, -3:, -1]
								lowerCAmelCase_      			=  image_from_tuple[0, -3:, -3:, -1]

								assert image.shape == (1, 32, 32, 3)
								lowerCAmelCase_      			=  np.array([0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0]   )

								assert np.abs(image_slice.flatten() - expected_slice   ).max() < 1E-2
								assert np.abs(image_from_tuple_slice.flatten() - expected_slice   ).max() < 1E-2







@slow
@require_torch
class  A		(  unittest.TestCase     ):



		def        SCREAMING_SNAKE_CASE__			(     self   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  '''google/ncsnpp-celebahq-256'''
								lowerCAmelCase_      			=  UNetaDModel.from_pretrained(UpperCamelCase__   )
								lowerCAmelCase_      			=  KarrasVeScheduler()

								lowerCAmelCase_      			=  KarrasVePipeline(unet=UpperCamelCase__,	scheduler=UpperCamelCase__   )
								pipe.to(UpperCamelCase__   )
								pipe.set_progress_bar_config(disable=UpperCamelCase__   )

								lowerCAmelCase_      			=  torch.manual_seed(0   )
								lowerCAmelCase_      			=  pipe(num_inference_steps=20,	generator=UpperCamelCase__,	output_type='''numpy'''   ).images

								lowerCAmelCase_      			=  image[0, -3:, -3:, -1]
								assert image.shape == (1, 256, 256, 3)
								lowerCAmelCase_      			=  np.array([0.578, 0.5_811, 0.5_924, 0.5_809, 0.587, 0.5_886, 0.5_861, 0.5_802, 0.586]   )

								assert np.abs(image_slice.flatten() - expected_slice   ).max() < 1E-2




