code: def forward(self, input, return_pred_indices=False):
      quant, diff, (_, _, ind) = self.encode(input)
      dec = self.decode(quant)
      if return_pred_indices:
          return dec, diff, ind
      return dec, diff
  
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 9 for calling the VQModel obj's underlying member method code with example usage: obj.forward(input, return_pred_indices) and returns: dec,  diff, dec,  diff,  ind