code: def user_forward_fn(
      model: Module, batch: Dict[str, Tensor]
  ) -> Tensor:
      """User forward function used for the computation of model embeddings.
  
      This function might be arbitrarily complicated inside. However, to ensure functionality, it should obey the
      input/output argument structure described below.
  
      Args:
          model: a torch.nn.module that implements a forward pass
          batch: a batch of inputs to pass through the model
  
      Return:
          The model output.
  
      """
      return model(batch["input_ids"])
  
file_path: torchmetrics/examples/bert_score-own_model.py
imports: from pprint import pprint
  from typing import Dict, List, Union
  import torch
  from torch import Tensor, nn
  from torch.nn import Module
  from torchmetrics.text.bert import BERTScore
label_desc: Use image node_id 2 for calling a global function with example usage: user_forward_fn(model, batch) and returns: model