code: def validation_step(self, batch, batch_idx):
      inputs = self.get_input(batch, self.image_key)
      reconstructions, posterior = self(inputs)
      aeloss, log_dict_ae = self.loss(
          inputs,
          reconstructions,
          posterior,
          0,
          self.global_step,
          last_layer=self.get_last_layer(),
          split="val",
      )
  
      discloss, log_dict_disc = self.loss(
          inputs,
          reconstructions,
          posterior,
          1,
          self.global_step,
          last_layer=self.get_last_layer(),
          split="val",
      )
  
      self.log("val/rec_loss", log_dict_ae["val/rec_loss"])
      self.log_dict(log_dict_ae)
      self.log_dict(log_dict_disc)
      return self.log_dict
  
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 8 for calling the AutoencoderKL obj's underlying member method code with example usage: obj.validation_step(batch, batch_idx) and returns: self