class_docstr: CLIP guided stable diffusion based on the amazing repo by @crowsonkb and @Jack000
  - https://github.com/Jack000/glid-3-xl
  - https://github.dev/crowsonkb/k-diffusion
class_docstr_tok: ["CLIP","guided","stable","diffusion","based","on","the","amazing","repo","by","@","crowsonkb","and","@","Jack000","-","https",":","\/\/github.com\/Jack000\/glid-3-xl","-","https",":","\/\/github.dev\/crowsonkb\/k-diffusion"]
code: def disable_attention_slicing(self):
      self.enable_attention_slicing(None)
  
imports: import inspect
  from typing import List, Optional, Union
  import torch
  from torch import nn
  from torch.nn import functional
  from torchvision import transforms
  from transformers import CLIPImageProcessor, CLIPModel, CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, DDIMScheduler, DiffusionPipeline, DPMSolverMultistepScheduler, LMSDiscreteScheduler, PNDMScheduler, UNet2DConditionModel
  from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion import StableDiffusionPipelineOutput
label_desc: Use image node_id 3 for calling the CLIPGuidedStableDiffusion obj's underlying member method code with example usage: obj.disable_attention_slicing() without return types