code: def train_program(
      self,
  ):
      label = F.data(name="label", shape=[None, 112], dtype="int64")
      train_idx = F.data(name="train_idx", shape=[None], dtype="int64")
      prediction = L.gather(self.out_feat, train_idx, overwrite=False)
      label = L.gather(label, train_idx, overwrite=False)
      label = L.cast(label, dtype="float32")
      cost = L.sigmoid_cross_entropy_with_logits(
          x=prediction, label=label
      )
      avg_cost = L.mean(cost)
      self.avg_cost = avg_cost
  
imports: import math
  import paddle.fluid
  import paddle.fluid.layers
  from module.transformer_gat_pgl import transformer_gat_pgl
label_desc: Use image node_id 5 for calling the Proteins_baseline_model obj's underlying member method code with example usage: obj.train_program() without return types