code: def mixup_target(
      target, num_classes, lam=1.0, smoothing=0.0, device="cuda"
  ):
      off_value = smoothing / num_classes
      on_value = 1.0 - smoothing + off_value
      y1 = one_hot(
          target,
          num_classes,
          on_value=on_value,
          off_value=off_value,
          device=device,
      )
      y2 = one_hot(
          target.flip(0),
          num_classes,
          on_value=on_value,
          off_value=off_value,
          device=device,
      )
      return y1 * lam + y2 * (1.0 - lam)
  
imports: import collections.abc
  from typing import Any, Dict, Optional
  import numpy
  import torch
  from classy_vision.generic.util import convert_to_one_hot
  from torch.distributions.beta import Beta
  from vissl.data.collators import register_collator
  from .moco_collator import moco_collator
  from .simclr_collator import simclr_collator
label_desc: Use image node_id 5 for calling a global function with example usage: mixup_target(target, num_classes, lam, smoothing, device) and returns: unknown