code: def build_lr_model(args):
      """
      Build the LR model to train.
      """
      emb_x = fluid.layers.data(
          name="emb_x", dtype="float32", shape=[args.w2v_emb_size]
      )
      label = fluid.layers.data(
          name="label_y", dtype="int64", shape=[1]
      )
      logits = fluid.layers.fc(
          input=emb_x,
          size=args.num_class,
          act=None,
          name="classification_layer",
      )
      proba = fluid.layers.softmax(logits)
      loss = fluid.layers.softmax_with_cross_entropy(logits, label)
      loss = fluid.layers.mean(loss)
      acc = fluid.layers.accuracy(input=proba, label=label, k=1)
      return loss, acc
  
imports: import numpy
  import paddle
  import paddle.fluid
label_desc: Use image node_id 1 for calling a global function with example usage: build_lr_model(args) and returns: loss,  acc