docstr: Args:
      obs: An float32 tensor of shape ([B] + observation_space).
           E.g. [B, C, H, W] in atari.
docstr_tok: ["Args",":","obs",":","An","float32","tensor","of","shape","(","[","B","]","+","observation_space",")",".","E.g",".","[","B",",","C",",","H",",","W","]","in","atari","."]
code: def predict(self, obs):
      """
      Args:
          obs: An float32 tensor of shape ([B] + observation_space).
               E.g. [B, C, H, W] in atari.
      """
      logits = self.model.policy(obs)
      probs = layers.softmax(logits)
  
      predict_actions = layers.argmax(probs, 1)
  
      return predict_actions
  
file_path: PARL/parl/algorithms/fluid/a3c.py
imports: import warnings
  import paddle.fluid
  from parl.core.fluid import layers
  from parl.core.fluid.algorithm import Algorithm
  from parl.core.fluid.policy_distribution import CategoricalDistribution
label_desc: Use image node_id 4 for calling the A3C obj's underlying member method code with example usage: obj.predict(obs) and returns: predict_actions