509453992838a524f6442d4e0f07a034390ae1f7,layers/eight_mile/tf/layers.py,BiLSTMEncoderAll1,call,#BiLSTMEncoderAll1#Any#,1204

Before Change

            h = tf.concat([fwd_state[i].h, bwd_state[i].h], -1)
            c = tf.concat([fwd_state[i].c, bwd_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

        hs = []
        for rnn in self.rnns:
            outputs, h1, h2 = rnn(inputs, mask=mask)
            h = tf.stack([h1, h2])
            hs.append(h)
            inputs = outputs

        _, B, H = get_shape_as_list(h)
        h = tf.reshape(tf.stack(hs), [-1, B, H * 2])
        return self.output_fn(outputs, h)

    @property

Instances