4acd61442955baa2509fdc2961284c9d2a986f34,tflearn/layers/recurrent.py,GRUCell,__call__,#GRUCell#Any#Any#Any#,697

Before Change

        // We start with bias of 1.0 to not reset and not update.
        self.W[0], self.b[0], r_u = _linear([inputs, state],
                                            2 * self._num_units,
                                            self.bias, self.W[0],
                                            self.b[0], self.W_init, 1.0,
                                            trainable=self.trainable,
                                            restore=self.restore,

After Change

            with tf.variable_scope("Linear/Gates", reuse=True):
                self.W.append(tf.get_variable("Matrix"))
                self.b.append(tf.get_variable("Bias"))
            with tf.variable_scope("Linear/Candidate", reuse=True):
                self.W.append(tf.get_variable("Matrix"))
                self.b.append(tf.get_variable("Bias"))

        return new_h, new_h


// --------------------

Instances