code: def compute_grad(
      gh: DataFrame, label: DataFrame, predict_score: DataFrame
  ):
      gh["g"] = predict_score - label
  
imports: import numpy
  import pandas
  import torch
  from fate.arch.dataframe import DataFrame
  from scipy.special import expit
  from fate.ml.utils.predict_tools import BINARY, MULTI, REGRESSION
label_desc: Use image node_id 4 for calling the BCELoss obj's underlying member method code with example usage: obj.compute_grad(gh, label, predict_score) without return types