code: def predict(self, obs):
      real_obs = layers.slice(
          obs,
          axes=[1],
          starts=[0],
          ends=[self.obs_dim - self.vel_obs_dim],
      )
      vel_obs = layers.slice(
          obs, axes=[1], starts=[-self.vel_obs_dim], ends=[self.obs_dim]
      )
      hid0 = self.fc0(real_obs)
      hid1 = self.fc1(hid0)
      vel_hid0 = self.vel_fc0(vel_obs)
      vel_hid1 = self.vel_fc1(vel_hid0)
      concat = layers.concat([hid1, vel_hid1], axis=1)
      hid2 = self.fc2(concat)
      means = self.fc3(hid2)
      return means
  
file_path: PARL/examples/NeurIPS2019-Learn-to-Move-Challenge/final_submit/mlp_model.py
imports: import numpy
  import parl
  from parl import layers
  from paddle import fluid
  from paddle.fluid.param_attr import ParamAttr
label_desc: Use image node_id 2 for calling the ActorModel obj's underlying member method code with example usage: obj.predict(obs) and returns: means