ba675a4894fbf3df2257c3815bc591c770c7470c,deeppavlov/core/layers/tf_layers.py,,cudnn_gru,#Any#Any#Any#Any#Any#Any#Any#Any#,498

Before Change

            indices = tf.stack([tf.range(tf.shape(h)[0]), seq_lengths], axis=1)
            h_last = tf.gather_nd(h, indices)
        else:
            h_last = tf.squeeze(h_last, 0)
        return h, h_last


def cudnn_lstm(units, n_hidden, n_layers=1, trainable_initial_states=None, seq_lengths=None, initial_h=None, initial_c=None,

After Change

        h, h_last = gru(tf.transpose(units, (1, 0, 2)), (initial_h, ))
        h = tf.transpose(h, (1, 0, 2))
        h_last = tf.reshape(h_last, shape=(-1, n_hidden))

        // Extract last states if they are provided
        if seq_lengths is not None:
            indices = tf.stack([tf.range(tf.shape(h)[0]), seq_lengths], axis=1)

Instances