class_docstr: NanoStableDiffusionPipeline.
class_docstr_tok: ["NanoStableDiffusionPipeline","."]
docstr: Init.
docstr_tok: ["Init","."]
code: def __init__(self, *args, **kwargs):
      """Init."""
      super().__init__(*args, **kwargs)
  
imports: import os
  import functools
  import diffusers
  from huggingface_hub import snapshot_download
  from transformers import CLIPFeatureExtractor, CLIPTextModel, CLIPTokenizer
  from diffusers import DiffusionPipeline, StableDiffusionPipeline, StableDiffusionImg2ImgPipeline
  from diffusers import AutoencoderKL, UNet2DConditionModel
  from bigdl.nano.diffusion.utils.paths import *
  from bigdl.nano.pytorch import InferenceOptimizer
  from bigdl.nano.utils.common import invalidInputError
  from bigdl.nano.diffusion.common.optimize import load_optimized_unet, load_optimized_vae_decoder
label_desc: Use image node_id 1 to create a new NanoStableDiffusionPipeline object from inherited base classes: StableDiffusionPipeline with example: obj = NanoStableDiffusionPipeline()