code: def get_noise_pred_single(self, latents, t, context):
      noise_pred = self.unet(latents, t, encoder_hidden_states=context)[
          "sample"
      ]
      return noise_pred
  
imports: import inspect
  import os
  import numpy
  import torch
  import torch.nn.functional
  from PIL import Image
  from torch.optim.adam import Adam
  from tqdm import tqdm
  from diffusers import StableDiffusionPipeline
  from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
label_desc: Use image node_id 2 for calling the NullTextPipeline obj's underlying member method code with example usage: obj.get_noise_pred_single(latents, t, context) and returns: noise_pred