code: def on_train_batch_end(self, *args, **kwargs):
      if self.use_ema:
          self.model_ema(self)
  
imports: import numpy
  import torch
  import pytorch_lightning
  import torch.nn.functional
  from contextlib import contextmanager
  from torch.optim.lr_scheduler import LambdaLR
  from ldm.modules.ema import LitEma
  from vqvae_quantize import VectorQuantizer2
  from ldm.modules.diffusionmodules.model import Encoder, Decoder
  from ldm.util import instantiate_from_config
  import ldm.models.autoencoder
  from packaging import version
label_desc: Use image node_id 4 for calling the VQModel obj's underlying member method code with example usage: obj.on_train_batch_end() without return types