src/network.c
@@ -64,6 +64,7 @@ case EXP: return net.learning_rate * pow(net.gamma, batch_num); case POLY: if (batch_num < net.burn_in) return net.learning_rate * pow((float)batch_num / net.burn_in, net.power); 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);