code: def get_input(self, batch, k):
      x = batch[k]
      if len(x.shape) == 3:
          x = x[..., None]
      x = rearrange(x, "b h w c -> b c h w")
      x = x.to(memory_format=torch.contiguous_format).float()
      return x
  
imports: import os
  from copy import deepcopy
  from glob import glob
  import lightning.pytorch
  import torch
  from einops import rearrange
  from ldm.lr_scheduler import LambdaLinearScheduler
  from ldm.models.diffusion.ddpm import LatentDiffusion
  from ldm.modules.diffusionmodules.openaimodel import EncoderUNetModel, UNetModel
  from ldm.util import default, ismap, log_txt_as_img
  from natsort import natsorted
  from omegaconf import OmegaConf
  from torch.nn import functional
  from torch.optim import AdamW
  from torch.optim.lr_scheduler import LambdaLR
label_desc: Use image node_id 7 for calling the NoisyLatentImageClassifier obj's underlying member method code with example usage: obj.get_input(batch, k) and returns: x