class_docstr: Sample available actions uniformly.
      
code: def sample(self):
      results = []
      for i in range(len(self.batch_list)):
          candidates = self.batch_list[i]
          results.append(np.random.choice(candidates))
      return np.array(results, dtype="long")
  
file_path: PARL/benchmark/fluid/QMIX/utils.py
imports: import numpy
label_desc: Use image node_id 2 for calling the AvailableActionsSampler obj's underlying member method code with example usage: obj.sample() and returns: np