code: def soft_cross_entropy(predicts, targets):
      student_likelihood = torch.nn.functional.log_softmax(
          predicts, dim=-1
      )
      targets_prob = torch.nn.functional.softmax(targets, dim=-1)
      return (-targets_prob * student_likelihood).mean()
  
imports: import torch
  from torch.nn import CrossEntropyLoss, MSELoss
  import datasets
  from datasets import load_dataset, load_metric
  import copy
  import os
  import json
  import transformers
  from transformers import AutoConfig, PretrainedConfig
  import huggingface_transformer
  from huggingface_transformer.modeling_bert import BertForSequenceClassification
  import logging
  import numpy
  import math
label_desc: Use image node_id 5 for calling a global function with example usage: soft_cross_entropy(predicts, targets) and returns: unknown