19d2bbc7d6e70836f34b83ac7702a0477e4b97b0,python/eight_mile/tf/layers.py,BiLSTMEncoder1,call,#BiLSTMEncoder1#Any#,835

Before Change

            c = tf.concat([fw_state[i].c, bw_state[i].c], -1)
            encoder_state.append(tf.contrib.rnn.LSTMStateTuple(h=h, c=c))
        encoder_state = tuple(encoder_state)
        return self.output_fn(rnnout, encoder_state)

    def output_fn(self, out, state):
        return out, state

After Change

        with tf.name_scope(self.name), tf.variable_scope(self.name):
            rnnout, (fwd_state, backward_state) = tf.nn.bidirectional_dynamic_rnn(self.fwd_rnn, self.bwd_rnn, inputs, sequence_length=lengths, dtype=tf.float32)
        rnnout = tf.concat(axis=2, values=rnnout)
        return self.output_fn(rnnout, ((fwd_state[-1].h, fwd_state[-1].c), (backward_state[-1].h, backward_state[-1].c)))

    @property
    def requires_length(self):

Instances