573c3583105fc1f48f485cb606b9d959fec79be2,hypergan/discriminators/pyramid_nostride_discriminator.py,,discriminator,#Any#Any#Any#Any#Any#Any#Any#,30

Before Change

        regs = regularizer(root_config, net, prefix)
        regularizers += regs

    return tf.concat(1, [net]+regularizers)
    return net

After Change

    if batch_norm is not None:
        net = batch_norm(batch_size*2, name=prefix+"_expand_bn_end_"+str(i))(net)
    net = tf.tanh(net)//activation(net)
    net = conv2d(net, int(int(net.get_shape()[3])*depth_increase), name=prefix+"_expaer"+str(i), k_w=1, k_h=1, d_h=1, d_w=1, regularizer=1.)
    net = tf.reshape(net, [batch_size*2, -1])

    //TODO: cross-d feature
    //regularizers = []

Instances