code: def forward(self, x):
      y_pred = torch.sigmoid(self.linear(x))
      return y_pred
  
file_path: FATE/examples/pipeline/sshe_lr/test_lr_predict_w_torch.py
imports: import argparse
  import torch
  from fate_client.pipeline import FateFlowPipeline
  from fate_client.pipeline.components.fate import Evaluation, Reader
  from fate_client.pipeline.components.fate import SSHELR, PSI
  from fate_client.pipeline.utils import test_utils
label_desc: Use image node_id 2 for calling the LogisticRegression obj's underlying member method code with example usage: obj.forward(x) and returns: y_pred