ops.py 文件源码

def __call__(self, inputs, state, scope=None):
        """Gated recurrent unit (GRU) with nunits cells."""
        with tf.variable_scope(scope or type(self).__name__):  # "GRUCell"
            with tf.variable_scope("Gates"):  # Reset gate and update gate.
                # We start with bias of 1.0 to not reset and not update.
                r, u = array_ops.split(_linear([inputs, state],
                                        2 * self._num_units, True, 1.0), 2, 1)
                r, u = sigmoid(r), sigmoid(u)
            with tf.variable_scope("Candidate"):
                c = self._activation(_linear([inputs, r * state],
                                            self._num_units, True))
            new_h = u * state + (1 - u) * c
        return new_h, new_h