code: def forward(self, data, oov_dict=None, require_loss=True):
      batch_gd = self.encode_init_node_feature(data)
      if require_loss:
          tgt = data["tgt_tensor"]
      else:
          tgt = None
      (
          prob,
          enc_attn_weights,
          coverage_vectors,
      ) = self.g2s.encoder_decoder(
          batch_gd, oov_dict=oov_dict, tgt_seq=tgt
      )
  
      if require_loss:
          tgt = data["tgt_tensor"]
          min_length = min(prob.shape[1], tgt.shape[1])
          prob = prob[:, :min_length, :]
          tgt = tgt[:, :min_length]
          loss = self.loss_calc(
              prob,
              label=tgt,
              enc_attn_weights=enc_attn_weights,
              coverage_vectors=coverage_vectors,
          )
          return prob, loss * min_length / 2
      else:
          return prob
  
imports: import argparse
  import multiprocessing
  import os
  import platform
  import time
  import numpy
  import torch
  import torch.backends.cudnn
  import torch.multiprocessing
  import torch.nn
  import torch.optim
  from torch.optim.lr_scheduler import ReduceLROnPlateau
  from torch.utils.data import DataLoader
  from graph4nlp.pytorch.datasets.squad import SQuADDataset
  from graph4nlp.pytorch.models.graph2seq import Graph2Seq
  from graph4nlp.pytorch.models.graph2seq_loss import Graph2SeqLoss
  from graph4nlp.pytorch.modules.config import get_basic_args
  from graph4nlp.pytorch.modules.evaluation import BLEU, METEOR, ROUGE
  from graph4nlp.pytorch.modules.graph_embedding_initialization.embedding_construction import WordEmbedding
  from graph4nlp.pytorch.modules.utils import constants
  from graph4nlp.pytorch.modules.utils.config_utils import get_yaml_config, update_values
  from graph4nlp.pytorch.modules.utils.copy_utils import prepare_ext_vocab
  from graph4nlp.pytorch.modules.utils.generic_utils import EarlyStopping, grid, to_cuda
  from graph4nlp.pytorch.modules.utils.logger import Logger
  from .fused_embedding_construction import FusedEmbeddingConstruction
label_desc: Use image node_id 3 for calling the QGModel obj's underlying member method code with example usage: obj.forward(data, oov_dict, require_loss) and returns: prob,  unknown, prob