code: def predict(self, observation):
      processed_obs = self.unitary_feature_processor.process(
          observation
      )
      processed_obs = np.array(processed_obs, dtype=np.float32).reshape(
          1, -1
      )
      predicted_rho = self.fluid_executor.run(
          self.predict_program,
          feed={"obs": processed_obs},
          fetch_list=[self.predicted_rho],
      )[0].reshape(-1)
      return predicted_rho
  
file_path: PARL/examples/NeurIPS2020-Learning-to-Run-a-Power-Network-Challenge/track1/es_agent.py
imports: import parl
  import paddle.fluid
  from parl import layers
  import numpy
  from utils import FeatureProcessor, UnitaryFeatureProcessor
label_desc: Use image node_id 3 for calling the UnitaryESAgent obj's underlying member method code with example usage: obj.predict(observation) and returns: predicted_rho