class_docstr: All trainable embeddings must inherit from BaseEmbedding.
class_docstr_tok: ["All","trainable","embeddings","must","inherit","from","BaseEmbedding","."]
code: def forward(self, x0: Tensor, x1: Tensor) -> Tensor:
      embedding: Tensor = self.model(x0, x1)
      return embedding
  
imports: import copy
  import os
  from typing import Any, List, Optional, Sequence, Tuple, Union
  import omegaconf
  from omegaconf import DictConfig
  from pytorch_lightning import LightningModule, Trainer
  from pytorch_lightning.callbacks.callback import Callback
  from torch import Tensor
  from torch.nn import Module
  from torch.optim import Optimizer
  from torch.optim.lr_scheduler import _LRScheduler
  from torch.utils.data import DataLoader
  from lightly.data.dataset import LightlyDataset
  from lightly.embedding import callbacks
  from lightly.utils.benchmarking import BenchmarkModule
label_desc: Use image node_id 2 for calling the BaseEmbedding obj's underlying member method code with example usage: obj.forward(x0, x1) and returns: embedding