


'''simple docstring'''




from __future__ import annotations

from random import random
from typing import Generic, TypeVar

_lowerCAmelCase  :		Tuple		     =	TypeVar('KT')
_lowerCAmelCase  :		Optional[int]		     =	TypeVar('VT')



class  lowerCAmelCase				(				Generic[KT, VT]							):



	def __init__(					self ,					snake_case__ = "root" ,					snake_case__ = None    ):
		lowerCAmelCase					:    Optional[Any]      							= key
		lowerCAmelCase					:    int      							= value
		lowerCAmelCase					:    list[Node[KT, VT]]      							= []



	def __repr__(					self    ):
		return f"Node({self.key}: {self.value})"



	@property
	def 				lowercase     (					self    ):
		return len(self.forward    )



class  lowerCAmelCase				(				Generic[KT, VT]							):



	def __init__(					self ,					snake_case__ = 0.5 ,					snake_case__ = 16    ):
		lowerCAmelCase					:    Node[KT, VT]      							= Node[KT, VT]()
		lowerCAmelCase					:    Tuple      							= 0
		lowerCAmelCase					:    Optional[int]      							= p
		lowerCAmelCase					:    Union[str, Any]      							= max_level



	def __str__(					self    ):
		lowerCAmelCase					:    Optional[Any]      							= list(self    )

		if len(snake_case__    ) == 0:
			return f"SkipList(level={self.level})"

		lowerCAmelCase					:    List[str]      							= max((len(str(snake_case__    )    ) for item in items) ,					default=4    )
		lowerCAmelCase					:    str      							= max(snake_case__ ,					4    ) + 4

		lowerCAmelCase					:    str      							= self.head
		lowerCAmelCase					:    Dict      							= []

		lowerCAmelCase					:    Any      							= node.forward.copy()
		lines.append(f"[{node.key}]".ljust(snake_case__ ,					'-'    ) + '* ' * len(snake_case__    )    )
		lines.append(' ' * label_size + '| ' * len(snake_case__    )    )

		while len(node.forward    ) != 0:
			lowerCAmelCase					:    List[str]      							= node.forward[0]

			lines.append(
			    f"[{node.key}]".ljust(snake_case__ ,					'-'    )
			    + ' '.join(str(n.key    ) if n.key == node.key else '|' for n in forwards    )    )
			lines.append(' ' * label_size + '| ' * len(snake_case__    )    )
			lowerCAmelCase					:    int      							= node.forward

		lines.append('None'.ljust(snake_case__    ) + '* ' * len(snake_case__    )    )
		return f"SkipList(level={self.level})\n" + "\n".join(snake_case__    )



	def __iter__(					self    ):
		lowerCAmelCase					:    Optional[Any]      							= self.head

		while len(node.forward    ) != 0:
			yield node.forward[0].key
			lowerCAmelCase					:    Optional[int]      							= node.forward[0]



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Tuple      							= 1
		while random() < self.p and level < self.max_level:
			level += 1

		return level



	def 				lowercase     (					self ,					snake_case__    ):
		lowerCAmelCase					:    Optional[int]      							= []

		lowerCAmelCase					:    List[str]      							= self.head

		for i in reversed(range(self.level    )    ):
			# i < node.level - When node level is lesser than `i` decrement `i`.
			# node.forward[i].key < key - Jumping to node with key value higher
			#                             or equal to searched key would result
			#                             in skipping searched key.
			while i < node.level and node.forward[i].key < key:
				lowerCAmelCase					:    List[str]      							= node.forward[i]
			# Each leftmost node (relative to searched node) will potentially have to
			# be updated.
			update_vector.append(snake_case__    )

		update_vector.reverse()  # Note that we were inserting values in reverse order.

		# len(node.forward) != 0 - If current node doesn't contain any further
		#                          references then searched key is not present.
		# node.forward[0].key == key - Next node key should be equal to search key
		#                              if key is present.
		if len(node.forward    ) != 0 and node.forward[0].key == key:
			return node.forward[0], update_vector
		else:
			return None, update_vector



	def 				lowercase     (					self ,					snake_case__    ):
		lowerCAmelCase							,   lowerCAmelCase					:    Union[str, Any]      							= self._locate_node(snake_case__    )

		if node is not None:
			for i, update_node in enumerate(snake_case__    ):
				# Remove or replace all references to removed node.
				if update_node.level > i and update_node.forward[i].key == key:
					if node.level > i:
						lowerCAmelCase					:    Any      							= node.forward[i]
					else:
						lowerCAmelCase					:    List[str]      							= update_node.forward[:i]



	def 				lowercase     (					self ,					snake_case__ ,					snake_case__    ):
		lowerCAmelCase							,   lowerCAmelCase					:    Union[str, Any]      							= self._locate_node(snake_case__    )
		if node is not None:
			lowerCAmelCase					:    str      							= value
		else:
			lowerCAmelCase					:    Tuple      							= self.random_level()

			if level > self.level:
				# After level increase we have to add additional nodes to head.
				for _ in range(self.level - 1 ,					snake_case__    ):
					update_vector.append(self.head    )
				lowerCAmelCase					:    List[str]      							= level

			lowerCAmelCase					:    Optional[Any]      							= Node(snake_case__ ,					snake_case__    )

			for i, update_node in enumerate(update_vector[:level]    ):
				# Change references to pass through new node.
				if update_node.level > i:
					new_node.forward.append(update_node.forward[i]    )

				if update_node.level < i + 1:
					update_node.forward.append(snake_case__    )
				else:
					lowerCAmelCase					:    Optional[Any]      							= new_node



	def 				lowercase     (					self ,					snake_case__    ):
		lowerCAmelCase							,   lowerCAmelCase					:    Union[str, Any]      							= self._locate_node(snake_case__    )

		if node is not None:
			return node.value

		return None


def 			__UpperCamelCase    (    )    ->      str:




	"""simple docstring"""





	lowerCAmelCase					:    Tuple      							= SkipList()
	skip_list.insert('Key1'					,   3				)
	skip_list.insert('Key2'					,   12				)
	skip_list.insert('Key3'					,   41				)
	skip_list.insert('Key4'					,   -19				)

	lowerCAmelCase					:    List[str]      							= skip_list.head
	lowerCAmelCase					:    List[Any]      							= {}
	while node.level != 0:
		lowerCAmelCase					:    str      							= node.forward[0]
		lowerCAmelCase					:    Tuple      							= node.value

	assert len(_A				) == 4
	assert all_values["Key1"] == 3
	assert all_values["Key2"] == 12
	assert all_values["Key3"] == 41
	assert all_values["Key4"] == -19

def 			__UpperCamelCase    (    )    ->      Optional[int]:




	"""simple docstring"""





	lowerCAmelCase					:    Optional[Any]      							= SkipList()
	skip_list.insert('Key1'					,   10				)
	skip_list.insert('Key1'					,   12				)

	skip_list.insert('Key5'					,   7				)
	skip_list.insert('Key7'					,   10				)
	skip_list.insert('Key10'					,   5				)

	skip_list.insert('Key7'					,   7				)
	skip_list.insert('Key5'					,   5				)
	skip_list.insert('Key10'					,   10				)

	lowerCAmelCase					:    int      							= skip_list.head
	lowerCAmelCase					:    Union[str, Any]      							= {}
	while node.level != 0:
		lowerCAmelCase					:    Dict      							= node.forward[0]
		lowerCAmelCase					:    Optional[int]      							= node.value

	if len(_A				) != 4:
		print()
	assert len(_A				) == 4
	assert all_values["Key1"] == 12
	assert all_values["Key7"] == 7
	assert all_values["Key5"] == 5
	assert all_values["Key10"] == 10

def 			__UpperCamelCase    (    )    ->      Optional[Any]:




	"""simple docstring"""





	lowerCAmelCase					:    Tuple      							= SkipList()
	assert skip_list.find('Some key'				) is None

def 			__UpperCamelCase    (    )    ->      List[str]:




	"""simple docstring"""





	lowerCAmelCase					:    Optional[Any]      							= SkipList()

	skip_list.insert('Key2'					,   20				)
	assert skip_list.find('Key2'				) == 20

	skip_list.insert('Some Key'					,   10				)
	skip_list.insert('Key2'					,   8				)
	skip_list.insert('V'					,   13				)

	assert skip_list.find('Y'				) is None
	assert skip_list.find('Key2'				) == 8
	assert skip_list.find('Some Key'				) == 10
	assert skip_list.find('V'				) == 13

def 			__UpperCamelCase    (    )    ->      Optional[int]:




	"""simple docstring"""





	lowerCAmelCase					:    Optional[Any]      							= SkipList()
	skip_list.delete('Some key'				)

	assert len(skip_list.head.forward				) == 0

def 			__UpperCamelCase    (    )    ->      List[Any]:




	"""simple docstring"""





	lowerCAmelCase					:    List[Any]      							= SkipList()

	skip_list.insert('Key1'					,   12				)
	skip_list.insert('V'					,   13				)
	skip_list.insert('X'					,   14				)
	skip_list.insert('Key2'					,   15				)

	skip_list.delete('V'				)
	skip_list.delete('Key2'				)

	assert skip_list.find('V'				) is None
	assert skip_list.find('Key2'				) is None

def 			__UpperCamelCase    (    )    ->      Dict:




	"""simple docstring"""





	lowerCAmelCase					:    Tuple      							= SkipList()

	skip_list.insert('Key1'					,   12				)
	skip_list.insert('V'					,   13				)
	skip_list.insert('X'					,   14				)
	skip_list.insert('Key2'					,   15				)

	skip_list.delete('V'				)
	assert skip_list.find('V'				) is None
	assert skip_list.find('X'				) == 14
	assert skip_list.find('Key1'				) == 12
	assert skip_list.find('Key2'				) == 15

	skip_list.delete('X'				)
	assert skip_list.find('V'				) is None
	assert skip_list.find('X'				) is None
	assert skip_list.find('Key1'				) == 12
	assert skip_list.find('Key2'				) == 15

	skip_list.delete('Key1'				)
	assert skip_list.find('V'				) is None
	assert skip_list.find('X'				) is None
	assert skip_list.find('Key1'				) is None
	assert skip_list.find('Key2'				) == 15

	skip_list.delete('Key2'				)
	assert skip_list.find('V'				) is None
	assert skip_list.find('X'				) is None
	assert skip_list.find('Key1'				) is None
	assert skip_list.find('Key2'				) is None

def 			__UpperCamelCase    (    )    ->      Union[str, Any]:




	"""simple docstring"""





	lowerCAmelCase					:    Union[str, Any]      							= SkipList()

	skip_list.insert('Key1'					,   12				)
	skip_list.insert('V'					,   13				)
	skip_list.insert('X'					,   1_42				)
	skip_list.insert('Key2'					,   15				)

	skip_list.delete('X'				)

	def traverse_keys(_A    :				Dict				):
		yield node.key
		for forward_node in node.forward:
			yield from traverse_keys(_A				)

	assert len(set(traverse_keys(skip_list.head				)				)				) == 4

def 			__UpperCamelCase    (    )    ->      Tuple:




	"""simple docstring"""





	def is_sorted(_A    :				Union[str, Any]				):
		return all(next_item >= item for item, next_item in zip(_A					,   lst[1:]				)				)

	lowerCAmelCase					:    List[Any]      							= SkipList()
	for i in range(10				):
		skip_list.insert(_A					,   _A				)
	assert is_sorted(list(_A				)				)
	skip_list.delete(5				)
	skip_list.delete(8				)
	skip_list.delete(2				)
	assert is_sorted(list(_A				)				)
	skip_list.insert(-12					,   -12				)
	skip_list.insert(77					,   77				)
	assert is_sorted(list(_A				)				)

def 			__UpperCamelCase    (    )    ->      Optional[int]:




	"""simple docstring"""





	for _ in range(1_00				):
		# Repeat test 100 times due to the probabilistic nature of skip list
		# random values == random bugs
		test_insert()
		test_insert_overrides_existing_value()

		test_searching_empty_list_returns_none()
		test_search()

		test_deleting_item_from_empty_list_do_nothing()
		test_deleted_items_are_not_founded_by_find_method()
		test_delete_removes_only_given_key()
		test_delete_doesnt_leave_dead_nodes()

		test_iter_always_yields_sorted_values()

def 			__UpperCamelCase    (    )    ->      List[str]:




	"""simple docstring"""





	lowerCAmelCase					:    List[Any]      							= SkipList()
	skip_list.insert(2					,   '2'				)
	skip_list.insert(4					,   '4'				)
	skip_list.insert(6					,   '4'				)
	skip_list.insert(4					,   '5'				)
	skip_list.insert(8					,   '4'				)
	skip_list.insert(9					,   '4'				)

	skip_list.delete(4				)

	print(_A				)


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()




'''simple docstring'''




import gc
import unittest

import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer

from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
    enable_full_determinism,
    load_numpy,
    nightly,
    require_torch_gpu,
    slow,
    torch_device,
)

from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_PARAMS
from ..test_pipelines_common import PipelineTesterMixin


enable_full_determinism()



class  lowerCAmelCase				(				a      ,				unittest.TestCase							):
	_lowerCamelCase   :					List[Any]			      = LDMTextToImagePipeline
	_lowerCamelCase   :					Optional[Any]			      = TEXT_TO_IMAGE_PARAMS - {
	    """negative_prompt""",
	    """negative_prompt_embeds""",
	    """cross_attention_kwargs""",
	    """prompt_embeds""",
	}
	_lowerCamelCase   :					List[str]			      = PipelineTesterMixin.required_optional_params - {
	    """num_images_per_prompt""",
	    """callback""",
	    """callback_steps""",
	}
	_lowerCamelCase   :					Union[str, Any]			      = TEXT_TO_IMAGE_BATCH_PARAMS
	_lowerCamelCase   :					Optional[int]			      = False



	def 				lowercase     (					self    ):
		torch.manual_seed(0    )
		lowerCAmelCase					:    Dict      							= UNetaDConditionModel(
		    block_out_channels=(32, 64) ,					layers_per_block=2 ,					sample_size=32 ,					in_channels=4 ,					out_channels=4 ,					down_block_types=('DownBlock2D', 'CrossAttnDownBlock2D') ,					up_block_types=('CrossAttnUpBlock2D', 'UpBlock2D') ,					cross_attention_dim=32 ,					)
		lowerCAmelCase					:    int      							= DDIMScheduler(
		    beta_start=0.0_0_0_8_5 ,					beta_end=0.0_1_2 ,					beta_schedule='scaled_linear' ,					clip_sample=snake_case__ ,					set_alpha_to_one=snake_case__ ,					)
		torch.manual_seed(0    )
		lowerCAmelCase					:    str      							= AutoencoderKL(
		    block_out_channels=(32, 64) ,					in_channels=3 ,					out_channels=3 ,					down_block_types=('DownEncoderBlock2D', 'DownEncoderBlock2D') ,					up_block_types=('UpDecoderBlock2D', 'UpDecoderBlock2D') ,					latent_channels=4 ,					)
		torch.manual_seed(0    )
		lowerCAmelCase					:    Any      							= CLIPTextConfig(
		    bos_token_id=0 ,					eos_token_id=2 ,					hidden_size=32 ,					intermediate_size=37 ,					layer_norm_eps=1e-0_5 ,					num_attention_heads=4 ,					num_hidden_layers=5 ,					pad_token_id=1 ,					vocab_size=1000 ,					)
		lowerCAmelCase					:    str      							= CLIPTextModel(snake_case__    )
		lowerCAmelCase					:    str      							= CLIPTokenizer.from_pretrained('hf-internal-testing/tiny-random-clip'    )

		lowerCAmelCase					:    List[Any]      							= {
		    'unet': unet,
		    'scheduler': scheduler,
		    'vqvae': vae,
		    'bert': text_encoder,
		    'tokenizer': tokenizer,
		}
		return components



	def 				lowercase     (					self ,					snake_case__ ,					snake_case__=0    ):
		if str(snake_case__    ).startswith('mps'    ):
			lowerCAmelCase					:    Optional[int]      							= torch.manual_seed(snake_case__    )
		else:
			lowerCAmelCase					:    str      							= torch.Generator(device=snake_case__    ).manual_seed(snake_case__    )
		lowerCAmelCase					:    Tuple      							= {
		    'prompt': 'A painting of a squirrel eating a burger',
		    'generator': generator,
		    'num_inference_steps': 2,
		    'guidance_scale': 6.0,
		    'output_type': 'numpy',
		}
		return inputs



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    List[str]      							= 'cpu'  # ensure determinism for the device-dependent torch.Generator

		lowerCAmelCase					:    Optional[Any]      							= self.get_dummy_components()
		lowerCAmelCase					:    Optional[Any]      							= LDMTextToImagePipeline(**snake_case__    )
		pipe.to(snake_case__    )
		pipe.set_progress_bar_config(disable=snake_case__    )

		lowerCAmelCase					:    Tuple      							= self.get_dummy_inputs(snake_case__    )
		lowerCAmelCase					:    Union[str, Any]      							= pipe(**snake_case__    ).images
		lowerCAmelCase					:    str      							= image[0, -3:, -3:, -1]

		assert image.shape == (1, 16, 16, 3)
		lowerCAmelCase					:    List[Any]      							= np.array([0.6_1_0_1, 0.6_1_5_6, 0.5_6_2_2, 0.4_8_9_5, 0.6_6_6_1, 0.3_8_0_4, 0.5_7_4_8, 0.6_1_3_6, 0.5_0_1_4]    )

		assert np.abs(image_slice.flatten() - expected_slice    ).max() < 1e-3



@slow
@require_torch_gpu
class  lowerCAmelCase				(				unittest.TestCase							):



	def 				lowercase     (					self    ):
		super().tearDown()
		gc.collect()
		torch.cuda.empty_cache()



	def 				lowercase     (					self ,					snake_case__ ,					snake_case__=torch.floataa ,					snake_case__=0    ):
		lowerCAmelCase					:    List[str]      							= torch.manual_seed(snake_case__    )
		lowerCAmelCase					:    int      							= np.random.RandomState(snake_case__    ).standard_normal((1, 4, 32, 32)    )
		lowerCAmelCase					:    Optional[Any]      							= torch.from_numpy(snake_case__    ).to(device=snake_case__ ,					dtype=snake_case__    )
		lowerCAmelCase					:    List[str]      							= {
		    'prompt': 'A painting of a squirrel eating a burger',
		    'latents': latents,
		    'generator': generator,
		    'num_inference_steps': 3,
		    'guidance_scale': 6.0,
		    'output_type': 'numpy',
		}
		return inputs



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Tuple      							= LDMTextToImagePipeline.from_pretrained('CompVis/ldm-text2im-large-256'    ).to(snake_case__    )
		pipe.set_progress_bar_config(disable=snake_case__    )

		lowerCAmelCase					:    Optional[Any]      							= self.get_inputs(snake_case__    )
		lowerCAmelCase					:    List[Any]      							= pipe(**snake_case__    ).images
		lowerCAmelCase					:    str      							= image[0, -3:, -3:, -1].flatten()

		assert image.shape == (1, 256, 256, 3)
		lowerCAmelCase					:    Tuple      							= np.array([0.5_1_8_2_5, 0.5_2_8_5_0, 0.5_2_5_4_3, 0.5_4_2_5_8, 0.5_2_3_0_4, 0.5_2_5_6_9, 0.5_4_3_6_3, 0.5_5_2_7_6, 0.5_6_8_7_8]    )
		lowerCAmelCase					:    int      							= np.abs(expected_slice - image_slice    ).max()
		assert max_diff < 1e-3



@nightly
@require_torch_gpu
class  lowerCAmelCase				(				unittest.TestCase							):



	def 				lowercase     (					self    ):
		super().tearDown()
		gc.collect()
		torch.cuda.empty_cache()



	def 				lowercase     (					self ,					snake_case__ ,					snake_case__=torch.floataa ,					snake_case__=0    ):
		lowerCAmelCase					:    List[str]      							= torch.manual_seed(snake_case__    )
		lowerCAmelCase					:    Any      							= np.random.RandomState(snake_case__    ).standard_normal((1, 4, 32, 32)    )
		lowerCAmelCase					:    List[Any]      							= torch.from_numpy(snake_case__    ).to(device=snake_case__ ,					dtype=snake_case__    )
		lowerCAmelCase					:    List[str]      							= {
		    'prompt': 'A painting of a squirrel eating a burger',
		    'latents': latents,
		    'generator': generator,
		    'num_inference_steps': 50,
		    'guidance_scale': 6.0,
		    'output_type': 'numpy',
		}
		return inputs



	def 				lowercase     (					self    ):
		lowerCAmelCase					:    Optional[int]      							= LDMTextToImagePipeline.from_pretrained('CompVis/ldm-text2im-large-256'    ).to(snake_case__    )
		pipe.set_progress_bar_config(disable=snake_case__    )

		lowerCAmelCase					:    int      							= self.get_inputs(snake_case__    )
		lowerCAmelCase					:    Optional[int]      							= pipe(**snake_case__    ).images[0]

		lowerCAmelCase					:    Optional[int]      							= load_numpy(
		    'https://huggingface.co/datasets/diffusers/test-arrays/resolve/main/ldm_text2img/ldm_large_256_ddim.npy'    )
		lowerCAmelCase					:    List[str]      							= np.abs(expected_image - image    ).max()
		assert max_diff < 1e-3
