code: def __init__(
      self,
      vae: AutoencoderKL,
      text_encoder: AutoModel,
      tokenizer: AutoTokenizer,
      unet: UNet2DConditionModel,
      scheduler: KarrasDiffusionSchedulers,
      safety_checker: StableDiffusionSafetyChecker,
      feature_extractor: CLIPImageProcessor,
      language_adapter: TranslatorNoLN = None,
      tensor_norm: torch.FloatTensor = None,
      requires_safety_checker: bool = True,
  ):
      super().__init__()
  
      self.register_modules(
          vae=vae,
          text_encoder=text_encoder,
          tokenizer=tokenizer,
          unet=unet,
          scheduler=scheduler,
          safety_checker=safety_checker,
          feature_extractor=feature_extractor,
          language_adapter=language_adapter,
          tensor_norm=tensor_norm,
      )
      self.vae_scale_factor = 2 ** (
          len(self.vae.config.block_out_channels) - 1
      )
      self.image_processor = VaeImageProcessor(
          vae_scale_factor=self.vae_scale_factor
      )
      self.register_to_config(
          requires_safety_checker=requires_safety_checker
      )
  
imports: import inspect
  from typing import Any, Dict, List, Optional, Union
  import torch
  import torch.nn
  from transformers import AutoModel, AutoTokenizer, CLIPImageProcessor
  from diffusers import DiffusionPipeline
  from diffusers.image_processor import VaeImageProcessor
  from diffusers.loaders import LoraLoaderMixin
  from diffusers.models import AutoencoderKL, UNet2DConditionModel
  from diffusers.models.lora import adjust_lora_scale_text_encoder
  from diffusers.pipelines.stable_diffusion.pipeline_output import StableDiffusionPipelineOutput
  from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
  from diffusers.schedulers import KarrasDiffusionSchedulers
  from diffusers.utils import USE_PEFT_BACKEND, logging, scale_lora_layers, unscale_lora_layers
  from diffusers.utils.torch_utils import randn_tensor
label_desc: Use image node_id 1 to create a new GlueGenStableDiffusionPipeline object from inherited base classes: DiffusionPipeline, LoraLoaderMixin with example: obj = GlueGenStableDiffusionPipeline(vae, text_encoder, tokenizer, unet, scheduler, safety_checker, feature_extractor, language_adapter, tensor_norm, requires_safety_checker)