code: def __init__(
      self,
      vae: AutoencoderKL,
      text_encoder: CLIPTextModel,
      tokenizer: CLIPTokenizer,
      unet: UNet2DConditionModel,
      scheduler: "LCMScheduler",
      safety_checker: StableDiffusionSafetyChecker,
      feature_extractor: CLIPImageProcessor,
      requires_safety_checker: bool = True,
  ):
      super().__init__()
  
      scheduler = (
          scheduler
          if scheduler is not None
          else LCMScheduler(
              beta_start=0.00085,
              beta_end=0.0120,
              beta_schedule="scaled_linear",
              prediction_type="epsilon",
          )
      )
  
      self.register_modules(
          vae=vae,
          text_encoder=text_encoder,
          tokenizer=tokenizer,
          unet=unet,
          scheduler=scheduler,
          safety_checker=safety_checker,
          feature_extractor=feature_extractor,
      )
      self.vae_scale_factor = 2 ** (
          len(self.vae.config.block_out_channels) - 1
      )
      self.image_processor = VaeImageProcessor(
          vae_scale_factor=self.vae_scale_factor
      )
  
imports: import math
  from dataclasses import dataclass
  from typing import Any, Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, ConfigMixin, DiffusionPipeline, SchedulerMixin, UNet2DConditionModel, logging
  from diffusers.configuration_utils import register_to_config
  from diffusers.image_processor import VaeImageProcessor
  from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
  from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
  from diffusers.utils import BaseOutput
label_desc: Use image node_id 1 to create a new LatentConsistencyModelPipeline object from inherited base classes: DiffusionPipeline with example: obj = LatentConsistencyModelPipeline(vae, text_encoder, tokenizer, unet, scheduler, safety_checker, feature_extractor, requires_safety_checker)