code: def build_program(self):
      self.pred_program = fluid.Program()
      self.learn_program = fluid.Program()
      self.next_q_program = fluid.Program()
      self.next_a_program = fluid.Program()
  
      with fluid.program_guard(self.pred_program):
          obs = layers.data(
              name="obs",
              shape=[self.obs_dim_n[self.agent_index]],
              dtype="float32",
          )
          self.pred_act = self.alg.predict(obs)
  
      with fluid.program_guard(self.learn_program):
          obs_n = [
              layers.data(
                  name="obs" + str(i),
                  shape=[self.obs_dim_n[i]],
                  dtype="float32",
              )
              for i in range(self.n)
          ]
          act_n = [
              layers.data(
                  name="act" + str(i),
                  shape=[self.act_dim_n[i]],
                  dtype="float32",
              )
              for i in range(self.n)
          ]
          target_q = layers.data(
              name="target_q", shape=[], dtype="float32"
          )
          self.critic_cost = self.alg.learn(obs_n, act_n, target_q)
  
      with fluid.program_guard(self.next_q_program):
          obs_n = [
              layers.data(
                  name="obs" + str(i),
                  shape=[self.obs_dim_n[i]],
                  dtype="float32",
              )
              for i in range(self.n)
          ]
          act_n = [
              layers.data(
                  name="act" + str(i),
                  shape=[self.act_dim_n[i]],
                  dtype="float32",
              )
              for i in range(self.n)
          ]
          self.next_Q = self.alg.Q_next(obs_n, act_n)
  
      with fluid.program_guard(self.next_a_program):
          obs = layers.data(
              name="obs",
              shape=[self.obs_dim_n[self.agent_index]],
              dtype="float32",
          )
          self.next_action = self.alg.predict_next(obs)
  
      if self.speedup:
          self.pred_program = parl.compile(self.pred_program)
          self.learn_program = parl.compile(
              self.learn_program, self.critic_cost
          )
          self.next_q_program = parl.compile(self.next_q_program)
          self.next_a_program = parl.compile(self.next_a_program)
  
file_path: PARL/benchmark/fluid/MADDPG/simple_agent.py
imports: import numpy
  import parl
  from parl import layers
  from paddle import fluid
  from parl.utils import ReplayMemory
  from parl.utils import machine_info, get_gpu_count
label_desc: Use image node_id 2 for calling the MAAgent obj's underlying member method code with example usage: obj.build_program() without return types