code: def encode(self, x):
      h = self.encoder(x)
      h = self.quant_conv(h)
      quant, emb_loss, info = self.quantize(h)
      return quant, emb_loss, info
  
imports: from contextlib import contextmanager
  import pytorch_lightning
  import torch
  import torch.nn.functional
  from nemo.collections.multimodal.modules.stable_diffusion.diffusionmodules.model import Decoder, Encoder
  from nemo.collections.multimodal.modules.stable_diffusion.distributions.distributions import DiagonalGaussianDistribution
  from nemo.collections.multimodal.parts.stable_diffusion.utils import instantiate_from_config
label_desc: Use image node_id 5 for calling the VQModel obj's underlying member method code with example usage: obj.encode(x) and returns: quant,  emb_loss,  info