docstr: x: (batch_size, max_length) LongTensor
  length: (batch_size,) LongTensor
code: def forward(self, x, length):
      """
      x: (batch_size, max_length) LongTensor
      length: (batch_size,) LongTensor
      """
      x = self.emb(x).sum(1) / length.unsqueeze(1).float()
      return self.proj(x)
  
imports: import argparse
  import pickle
  import time
  import dgl
  import dgl.function
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.data import DataLoader, IterableDataset
  from ..None import utils
label_desc: Use image node_id 2 for calling the BagOfWordsPretrained obj's underlying member method code with example usage: obj.forward(x, length) and returns: self