rda_cell.py 文件源码

def __call__(self, inputs, state, scope=None):
    with _checked_scope(self, scope or "rwa_cell", reuse=self._reuse):
      h, n, d = state

      with vs.variable_scope("u"):
        u = linear(inputs, self._num_units, True, normalize=self._normalize)

      with vs.variable_scope("g"):
        g = linear([inputs, h], self._num_units, True, normalize=self._normalize)

      with vs.variable_scope("a"): # The bias term when factored out of the numerator and denominator cancels and is unnecessary
        a = tf.exp(linear([inputs, h], self._num_units, True, normalize=self._normalize))

      with vs.variable_scope("discount_factor"):
        discount_factor = tf.nn.sigmoid(linear([inputs, h], self._num_units, True, normalize=self._normalize))

      z = tf.multiply(u, tanh(g))

      n = tf.multiply(n, discount_factor) + tf.multiply(z, a)  # Numerically stable update of numerator
      d = tf.multiply(d, discount_factor) + a  # Numerically stable update of denominator
      h_new = self._activation(tf.div(n, d))

      new_state = RDACellTuple(h_new, n, d)

    return h_new, new_state