code: def encode(self, x):
      h = self.encoder(x)
      moments = self.quant_conv(h)
      posterior = DiagonalGaussianDistribution(moments)
      return posterior
  
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 3 for calling the AutoencoderKL obj's underlying member method code with example usage: obj.encode(x) and returns: posterior