4580d28f9cc8f846ee6fb42dda6909a98797fcd9,nara_wpe/tf_wpe.py,,perform_filter_operation,#Any#Any#Any#Any#,166

Before Change

    // TODO: Second loop can be removed with using segment_axis. No large gain.
    reverb_tail = list()
    for tau_minus_delay in range(0, K):
        reverb_tail.append(tf.einsum(
            "de,dt",
            filter_matrix_conj[tau_minus_delay, :, :],
            Y[:, (K - 1 - tau_minus_delay):(T - delay - tau_minus_delay)]
        ))
    reverb_tail = tf.add_n(reverb_tail)
    return tf.concat(
        [Y[:, :(delay + K - 1)],
         Y[:, (delay + K - 1):] - reverb_tail], axis=-1)

After Change

            filter_matrix_conj[tau_minus_delay, :, :],
            Y[:, (K - 1 - tau_minus_delay):(T - delay - tau_minus_delay)]
        )
    reverb_tail = tf.foldl(
        add_tap, tf.range(0, K),
        initializer=tf.zeros_like(Y[:, (delay + K - 1):])
    )
    return tf.concat(
        [Y[:, :(delay + K - 1)],
         Y[:, (delay + K - 1):] - reverb_tail], axis=-1)

Instances