code: 
  
  
  
  
  
  from ..utils import (
      OptionalDependencyNotAvailable,
      is_flax_available,
      is_invisible_watermark_available,
      is_k_diffusion_available,
      is_librosa_available,
      is_note_seq_available,
      is_onnx_available,
      is_torch_available,
      is_transformers_available,
  )
  
  
  try:
  				if not is_torch_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_pt_objects import *  # noqa F403
  else:
  				from .consistency_models import ConsistencyModelPipeline
  				from .dance_diffusion import DanceDiffusionPipeline
  				from .ddim import DDIMPipeline
  				from .ddpm import DDPMPipeline
  				from .dit import DiTPipeline
  				from .latent_diffusion import LDMSuperResolutionPipeline
  				from .latent_diffusion_uncond import LDMPipeline
  				from .pipeline_utils import AudioPipelineOutput, DiffusionPipeline, ImagePipelineOutput
  				from .pndm import PNDMPipeline
  				from .repaint import RePaintPipeline
  				from .score_sde_ve import ScoreSdeVePipeline
  				from .stochastic_karras_ve import KarrasVePipeline
  
  try:
  				if not (is_torch_available() and is_librosa_available()):
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_torch_and_librosa_objects import *  # noqa F403
  else:
  				from .audio_diffusion import AudioDiffusionPipeline, Mel
  
  try:
  				if not (is_torch_available() and is_transformers_available()):
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_torch_and_transformers_objects import *  # noqa F403
  else:
  				from .alt_diffusion import AltDiffusionImgaImgPipeline, AltDiffusionPipeline
  				from .audioldm import AudioLDMPipeline
  				from .controlnet import (
  				    StableDiffusionControlNetImgaImgPipeline,
  				    StableDiffusionControlNetInpaintPipeline,
  				    StableDiffusionControlNetPipeline,
  				)
  				from .deepfloyd_if import (
  				    IFImgaImgPipeline,
  				    IFImgaImgSuperResolutionPipeline,
  				    IFInpaintingPipeline,
  				    IFInpaintingSuperResolutionPipeline,
  				    IFPipeline,
  				    IFSuperResolutionPipeline,
  				)
  				from .kandinsky import (
  				    KandinskyImgaImgPipeline,
  				    KandinskyInpaintPipeline,
  				    KandinskyPipeline,
  				    KandinskyPriorPipeline,
  				)
  				from .kandinskya_a import (
  				    KandinskyVaaControlnetImgaImgPipeline,
  				    KandinskyVaaControlnetPipeline,
  				    KandinskyVaaImgaImgPipeline,
  				    KandinskyVaaInpaintPipeline,
  				    KandinskyVaaPipeline,
  				    KandinskyVaaPriorEmbaEmbPipeline,
  				    KandinskyVaaPriorPipeline,
  				)
  				from .latent_diffusion import LDMTextToImagePipeline
  				from .paint_by_example import PaintByExamplePipeline
  				from .semantic_stable_diffusion import SemanticStableDiffusionPipeline
  				from .shap_e import ShapEImgaImgPipeline, ShapEPipeline
  				from .stable_diffusion import (
  				    CycleDiffusionPipeline,
  				    StableDiffusionAttendAndExcitePipeline,
  				    StableDiffusionDepthaImgPipeline,
  				    StableDiffusionDiffEditPipeline,
  				    StableDiffusionImageVariationPipeline,
  				    StableDiffusionImgaImgPipeline,
  				    StableDiffusionInpaintPipeline,
  				    StableDiffusionInpaintPipelineLegacy,
  				    StableDiffusionInstructPixaPixPipeline,
  				    StableDiffusionLatentUpscalePipeline,
  				    StableDiffusionLDMaDPipeline,
  				    StableDiffusionModelEditingPipeline,
  				    StableDiffusionPanoramaPipeline,
  				    StableDiffusionParadigmsPipeline,
  				    StableDiffusionPipeline,
  				    StableDiffusionPixaPixZeroPipeline,
  				    StableDiffusionSAGPipeline,
  				    StableDiffusionUpscalePipeline,
  				    StableUnCLIPImgaImgPipeline,
  				    StableUnCLIPPipeline,
  				)
  				from .stable_diffusion_safe import StableDiffusionPipelineSafe
  				from .text_to_video_synthesis import TextToVideoSDPipeline, TextToVideoZeroPipeline, VideoToVideoSDPipeline
  				from .unclip import UnCLIPImageVariationPipeline, UnCLIPPipeline
  				from .unidiffuser import ImageTextPipelineOutput, UniDiffuserModel, UniDiffuserPipeline, UniDiffuserTextDecoder
  				from .versatile_diffusion import (
  				    VersatileDiffusionDualGuidedPipeline,
  				    VersatileDiffusionImageVariationPipeline,
  				    VersatileDiffusionPipeline,
  				    VersatileDiffusionTextToImagePipeline,
  				)
  				from .vq_diffusion import VQDiffusionPipeline
  
  
  try:
  				if not (is_torch_available() and is_transformers_available() and is_invisible_watermark_available()):
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_torch_and_transformers_and_invisible_watermark_objects import *  # noqa F403
  else:
  				from .stable_diffusion_xl import StableDiffusionXLImgaImgPipeline, StableDiffusionXLPipeline
  
  try:
  				if not is_onnx_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_onnx_objects import *  # noqa F403
  else:
  				from .onnx_utils import OnnxRuntimeModel
  
  try:
  				if not (is_torch_available() and is_transformers_available() and is_onnx_available()):
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_torch_and_transformers_and_onnx_objects import *  # noqa F403
  else:
  				from .stable_diffusion import (
  				    OnnxStableDiffusionImgaImgPipeline,
  				    OnnxStableDiffusionInpaintPipeline,
  				    OnnxStableDiffusionInpaintPipelineLegacy,
  				    OnnxStableDiffusionPipeline,
  				    OnnxStableDiffusionUpscalePipeline,
  				    StableDiffusionOnnxPipeline,
  				)
  
  try:
  				if not (is_torch_available() and is_transformers_available() and is_k_diffusion_available()):
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_torch_and_transformers_and_k_diffusion_objects import *  # noqa F403
  else:
  				from .stable_diffusion import StableDiffusionKDiffusionPipeline
  
  try:
  				if not is_flax_available():
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_flax_objects import *  # noqa F403
  else:
  				from .pipeline_flax_utils import FlaxDiffusionPipeline
  
  
  try:
  				if not (is_flax_available() and is_transformers_available()):
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_flax_and_transformers_objects import *  # noqa F403
  else:
  				from .controlnet import FlaxStableDiffusionControlNetPipeline
  				from .stable_diffusion import (
  				    FlaxStableDiffusionImgaImgPipeline,
  				    FlaxStableDiffusionInpaintPipeline,
  				    FlaxStableDiffusionPipeline,
  				)
  try:
  				if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
  								raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  				from ..utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
  else:
  				from .spectrogram_diffusion import MidiProcessor, SpectrogramDiffusionPipeline
  
  
  
  
style_context: 
  
  
  
  
  
  from dataclasses import dataclass
  
  __lowerCAmelCase     =			"0.1"
  __lowerCAmelCase     =			"Lucia Harcekova"
  
  
  
  
  @dataclass
  class   _UpperCAmelCase	:
  					__A          =   42
  					__A          =   42
  					__A          =   42
  
  
  
  
  					def __repr__(						self       )						->  str:
  							return F"""({self.offset}, {self.length}, {self.indicator})"""
  
  
  
  
  class   _UpperCAmelCase	:
  
  
  
  
  					def __init__(						self    ,      __lowerCAmelCase = 13    ,      __lowerCAmelCase = 6       )						->  None:
  							UpperCamelCase__         =	window_size
  							UpperCamelCase__         =	lookahead_buffer_size
  							UpperCamelCase__         =	self.window_size - self.lookahead_buffer_size
  
  
  
  
  					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  list[Token]:
  							UpperCamelCase__         =	[]
  							UpperCamelCase__         =	""""""
  
  							# while there are still characters in text to compress
  							while text:
  									# find the next encoding phrase
  									# - triplet with offset, length, indicator (the next encoding character)
  									UpperCamelCase__         =	self._find_encoding_token(__lowerCAmelCase    ,      __lowerCAmelCase       )
  
  									# update the search buffer:
  									# - add new characters from text into it
  									# - check if size exceed the max search buffer size, if so, drop the
  									#   oldest elements
  									search_buffer += text[: token.length + 1]
  									if len(__lowerCAmelCase       ) > self.search_buffer_size:
  											UpperCamelCase__         =	search_buffer[-self.search_buffer_size :]
  
  									# update the text
  									UpperCamelCase__         =	text[token.length + 1 :]
  
  									# append the token to output
  									output.append(__lowerCAmelCase       )
  
  							return output
  
  
  
  
  					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  str:
  							UpperCamelCase__         =	""""""
  
  							for token in tokens:
  									for _ in range(token.length       ):
  											output += output[-token.offset]
  									output += token.indicator
  
  							return output
  
  
  
  
  					def 	snake_case_		(						self    ,      __lowerCAmelCase    ,      __lowerCAmelCase       )						->  Token:
  
  							if not text:
  									raise ValueError("""We need some text to work with."""       )
  
  							# Initialise result parameters to default values
  							UpperCamelCase__  ,			UpperCamelCase__         =	0, 0
  
  							if not search_buffer:
  									return Token(__lowerCAmelCase    ,      __lowerCAmelCase    ,      text[length]       )
  
  							for i, character in enumerate(__lowerCAmelCase       ):
  									UpperCamelCase__         =	len(__lowerCAmelCase       ) - i
  									if character == text[0]:
  											UpperCamelCase__         =	self._match_length_from_index(__lowerCAmelCase    ,      __lowerCAmelCase    ,      0    ,      __lowerCAmelCase       )
  											# if the found length is bigger than the current or if it's equal,
  											# which means it's offset is smaller: update offset and length
  											if found_length >= length:
  													UpperCamelCase__  ,			UpperCamelCase__         =	found_offset, found_length
  
  							return Token(__lowerCAmelCase    ,      __lowerCAmelCase    ,      text[length]       )
  
  
  
  
  					def 	snake_case_		(						self    ,      __lowerCAmelCase    ,      __lowerCAmelCase    ,      __lowerCAmelCase    ,      __lowerCAmelCase       )						->  int:
  							if not text or text[text_index] != window[window_index]:
  									return 0
  							return 1 + self._match_length_from_index(
  							    __lowerCAmelCase    ,      window + text[text_index]    ,      text_index + 1    ,      window_index + 1       )
  
  
  if __name__ == "__main__":
  				from doctest import testmod
  
  				testmod()
  				# Initialize compressor class
  				__lowerCAmelCase     =			LZaaCompressor(window_size=13, lookahead_buffer_size=6)
  
  				# Example
  				__lowerCAmelCase     =			"cabracadabrarrarrad"
  				__lowerCAmelCase     =			lzaa_compressor.compress(TEXT)
  				print(lzaa_compressor.compress("ababcbababaa"))
  				__lowerCAmelCase     =			lzaa_compressor.decompress(compressed_text)
  				assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."
  
  
  
  
  
  