class_docstr: Sample available actions uniformly.
      
docstr: data: np.ndarray (batch_size, len_distributions)
code: def __init__(self, data):
      """data: np.ndarray (batch_size, len_distributions)"""
      assert len(data.shape) == 2
      self.batch_list = []
      for i in range(data.shape[0]):
          elements = set()
          for j in range(data.shape[1]):
              if np.abs(data[i, j] - 1.0) < 1e-5:
                  # add action idx
                  elements.add(j)
          self.batch_list.append(list(elements))
  
file_path: PARL/examples/QMIX/utils.py
imports: import numpy
label_desc: Use image node_id 1 to create a new AvailableActionsSampler object from inherited base classes: object with example: obj = AvailableActionsSampler(data)