code: def encode_to_prequant(self, x):
      h = self.encoder(x)
      h = self.quant_conv(h)
      return h
  
imports: import torch
  import pytorch_lightning
  import torch.nn.functional
  from contextlib import contextmanager
  from taming.modules.vqvae.quantize import VectorQuantizer2
  from ldm.modules.diffusionmodules.model import Encoder, Decoder
  from ldm.modules.distributions.distributions import DiagonalGaussianDistribution
  from ldm.util import instantiate_from_config
label_desc: Use image node_id 6 for calling the VQModel obj's underlying member method code with example usage: obj.encode_to_prequant(x) and returns: h