code: def get_lprobs_and_target(self, model, net_output, sample):
      lprobs = model.get_normalized_probs(net_output, log_probs=True)
      target = model.get_targets(sample, net_output)
      if self.ignore_prefix_size > 0:
          # lprobs: B x T x C
          lprobs = lprobs[:, self.ignore_prefix_size :, :].contiguous()
          target = target[:, self.ignore_prefix_size :].contiguous()
      return lprobs.view(-1, lprobs.size(-1)), target.view(-1)
  
imports: import math
  from dataclasses import dataclass, field
  import torch
  from fairseq import utils
  from fairseq.logging import metrics
  from fairseq.criterions import FairseqCriterion, register_criterion
  from fairseq.dataclass import FairseqDataclass
  from omegaconf import II
label_desc: Use image node_id 3 for calling the LabelSmoothedCrossEntropyCriterion obj's underlying member method code with example usage: obj.get_lprobs_and_target(model, net_output, sample) and returns: lprobs,  target