code: def forward_encoder(self, images, batch_size, idx_mask):
      # pass all the tokens to the encoder, both masked and non masked ones
      tokens = self.backbone.images_to_tokens(
          images, prepend_class_token=True
      )
      tokens_masked = utils.mask_at_index(
          tokens, idx_mask, self.mask_token
      )
      return self.backbone.encoder(tokens_masked)
  
file_path: lightly/examples/pytorch_lightning_distributed/simmim.py
imports: import pytorch_lightning
  import torch
  import torchvision
  from torch import nn
  from lightly.models import utils
  from lightly.models.modules import masked_autoencoder
  from lightly.transforms.mae_transform import MAETransform
label_desc: Use image node_id 2 for calling the SimMIM obj's underlying member method code with example usage: obj.forward_encoder(images, batch_size, idx_mask) and returns: self