code: def forward(self, output, target):
      valid_targets = self.compute_valid_targets(
          target=target, classes=output.shape[1]
      )
      assert (
          valid_targets.shape == output.shape
      ), "LabelSmoothingCrossEntropyLoss requires output and target to be same size"
      smoothed_targets = self.smooth_targets(
          valid_targets=valid_targets, classes=output.shape[1]
      )
      return self.loss_function(output, smoothed_targets)
  
file_path: ClassyVision/classy_vision/losses/label_smoothing_loss.py
imports: from typing import Any, Dict
  import numpy
  from classy_vision.generic.util import convert_to_one_hot
  from classy_vision.losses import ClassyLoss, register_loss
  from classy_vision.losses.soft_target_cross_entropy_loss import SoftTargetCrossEntropyLoss
label_desc: Use image node_id 5 for calling the LabelSmoothingCrossEntropyLoss obj's underlying member method code with example usage: obj.forward(output, target) and returns: self