code: def forward(self, features):
      token_embeddings = self.emb_layer(features["input_ids"])
      cls_tokens = None
      features.update(
          {
              "token_embeddings": token_embeddings,
              "cls_token_embeddings": cls_tokens,
              "attention_mask": features["attention_mask"],
          }
      )
      return features
  
imports: import torch
  from torch import nn
  from typing import List
  import logging
  import gzip
  from tqdm import tqdm
  import numpy
  import os
  import json
  from ..util import import_from_string, fullname, http_get
  from .tokenizer import WordTokenizer, WhitespaceTokenizer
label_desc: Use image node_id 2 for calling the WordEmbeddings obj's underlying member method code with example usage: obj.forward(features) and returns: features