(self)
Allows the network to be called, as in the following code snippet!

        q_network = MelodyRNN(...)
        q_network()

    The q_network() operation can then be placed into a larger graph as a tf op.

    Note that to get actual values from call, must do session.run and feed in
    melody_sequence, lengths, and initial_state in the feed dict.

    Returns:
      Either softmax probabilities over notes, or raw logit scores.
Allows the network to be called, as in the following code snippet!
Allows the network to be called as in the following code snippet!
def __call__(self):
    """Allows the network to be called, as in the following code snippet!

        q_network = MelodyRNN(...)
        q_network()

    The q_network() operation can then be placed into a larger graph as a tf op.

    Note that to get actual values from call, must do session.run and feed in
    melody_sequence, lengths, and initial_state in the feed dict.

    Returns:
      Either softmax probabilities over notes, or raw logit scores.
    """
    with self.graph.as_default():
      with tf.variable_scope(self.scope, reuse=True):
        logits, self.state_tensor = self.run_network_on_melody(
            self.melody_sequence, self.lengths, self.initial_state)
        return logits
def __call__ ( self ) : with self . graph . as_default ( ) : with tf . variable_scope ( self . scope , reuse = True ) : logits , self . state_tensor = self . run_network_on_melody ( self . melody_sequence , self . lengths , self . initial_state ) return logits