code: def predict(score: DataFrame):
      pred_rs = score.create_frame()
      pred_rs["score"] = score.apply_row(lambda s: sigmoid(s))
      return pred_rs
  
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 2 for calling the BCELoss obj's underlying member method code with example usage: obj.predict(score) and returns: pred_rs