code: def _get_latent(self, path=None, img=None):
      if not (path or img):
          raise ValueError("Input either path or tensor")
      if img is not None:
          raise NotImplementedError
      x = preprocess(Image.open(path), target_image_size=256).to(
          self.device
      )
      x_processed = preprocess_vqgan(x)
      z, *_ = self.vqgan.encode(x_processed)
      return z
  
imports: import os
  from glob import glob
  import imageio
  import torch
  import torchvision
  import wandb
  from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
  from loaders import load_vqgan
  from PIL import Image
  from torch import nn
  from transformers import CLIPModel, CLIPTokenizerFast
  from utils import get_device, get_timestamp, show_pil
label_desc: Use image node_id 3 for calling the VQGAN_CLIP obj's underlying member method code with example usage: obj._get_latent(path, img) and returns: z