135a56e0935fbb04811f8ce7b9f514f498212f71,niftynet/layer/crf.py,,ftheta,#Any#Any#Any#Any#Any#Any#,148

Before Change

    // Message Passing
    data = tf.reshape(tf.nn.softmax(H1), [batch_size, -1, n_ch])
    Q1 = [None] * len(permutohedrals)
    with tf.device("/cpu:0"):
        for idx, permutohedral in enumerate(permutohedrals):
            Q1[idx] = tf.reshape(
                _permutohedral_gen(permutohedral, data, name + str(idx)),
                U.shape)

    // Weighting Filter Outputs
    Q2 = tf.add_n([Q1 * w for Q1, w in zip(Q1, kernel_weights)])

    // Compatibility Transform
    spatial_dim = infer_spatial_rank(U)

After Change

    // Compatibility Transform, Adding Unary Potentials
    // output logits, not the softmax
    return U - tf.reshape(tf.matmul(Q1, mu), U.shape.as_list())


def permutohedral_prepare(position_vectors):
    

Instances