class_docstr: Discrete filtered Q-network.
  
  This produces filtered Q values according to the method used in the discrete
  BCQ algorithm (https://arxiv.org/pdf/1910.01708.pdf - section 4).
class_docstr_tok: ["Discrete","filtered","Q-network",".","This","produces","filtered","Q","values","according","to","the","method","used","in","the","discrete","BCQ","algorithm","(","https",":","\/\/arxiv.org\/pdf\/1910.01708.pdf","-","section","4",")","."]
code: def __init__(
      self,
      g_network: snt.Module,
      q_network: snt.Module,
      threshold: float,
  ):
      super().__init__(name="discrete_filtered_qnet")
      assert threshold >= 0 and threshold <= 1
      self.g_network = g_network
      self.q_network = q_network
      self._threshold = threshold
  
imports: import sonnet
  import tensorflow
label_desc: Use image node_id 1 to create a new DiscreteFilteredQNetwork object from inherited base classes: snt with example: obj = DiscreteFilteredQNetwork(g_network, q_network, threshold)