Joseph Redmon
2016-05-12 054e2b1954aafb15b0e983180dda309cfd5d831f
src/network.c
@@ -65,6 +65,8 @@
            return net.learning_rate * pow(net.gamma, batch_num);
        case POLY:
            return net.learning_rate * pow(1 - (float)batch_num / net.max_batches, net.power);
        case RANDOM:
            return net.learning_rate * pow(rand_uniform(0,1), net.power);
        case SIG:
            return net.learning_rate * (1./(1.+exp(net.gamma*(batch_num - net.step))));
        default: