code: def training_step(self, batch, batch_index):
      views_and_grids = batch[0]
      views = views_and_grids[: len(views_and_grids) // 2]
      grids = views_and_grids[len(views_and_grids) // 2 :]
      features = [self.forward(view) for view in views]
      loss = self.criterion(
          global_view_features=features[:2],
          global_view_grids=grids[:2],
          local_view_features=features[2:],
          local_view_grids=grids[2:],
      )
      return loss
  
file_path: lightly/examples/pytorch_lightning_distributed/vicregl.py
imports: import pytorch_lightning
  import torch
  import torchvision
  from torch import nn
  from lightly.loss import VICRegLLoss
  from lightly.models.modules import BarlowTwinsProjectionHead
  from lightly.models.modules.heads import VicRegLLocalProjectionHead
  from lightly.transforms.vicregl_transform import VICRegLTransform
label_desc: Use image node_id 3 for calling the VICRegL obj's underlying member method code with example usage: obj.training_step(batch, batch_index) and returns: loss