class_docstr: Agent.
  Args:
      algorithm (`parl.Algorithm`): algorithm to be used in this agent.
class_docstr_tok: ["Agent",".","Args",":","algorithm","(","`","parl.Algorithm","`",")",":","algorithm","to","be","used","in","this","agent","."]
docstr: Predict the critic value
  Args:
      state (np.array): representation of current state 
  Return:
      value (np.array): state value
docstr_tok: ["Predict","the","critic","value","Args",":","state","(","np.array",")",":","representation","of","current","state","Return",":","value","(","np.array",")",":","state","value"]
code: def value(self, state):
      """Predict the critic value
      Args:
          state (np.array): representation of current state
      Return:
          value (np.array): state value
      """
  
      state_tensor = paddle.to_tensor(state, dtype=paddle.float32)
  
      with paddle.no_grad():
          value = self.alg.value(state_tensor).cpu().numpy()
  
      return value
  
file_path: PARL/examples/Baselines/Halite_competition/paddle/rl_trainer/agent.py
imports: import os
  import parl
  import paddle
label_desc: Use image node_id 5 for calling the Agent obj's underlying member method code with example usage: obj.value(state) and returns: value