def main(): tr_x, tr_y, te_x, te_y = load_cifar10_data() tr_x, te_x = global_mean_std(tr_x, te_x) mean_acc, max_acc, min_acc = eval_net_basic( tr_x, tr_y, te_x, te_y, net_func=cifar10_sequential_cbn6d) print("Mean accuracy: ", mean_acc) print("Max accuracy: ", max_acc) print("Min accuracy: ", min_acc)
def main(): tr_x, tr_y, te_x, te_y = load_cifar10_data() tr_x, te_x = global_mean_std(tr_x, te_x) mean_acc, max_acc, min_acc = eval_net_basic( tr_x, tr_y, te_x, te_y, net_func=cifar10_bn_inception_v1) print("Mean accuracy: ", mean_acc) print("Max accuracy: ", max_acc) print("Min accuracy: ", min_acc)
def main(): tr_x, tr_y, te_x, te_y = load_cifar10_data() tr_x, te_x = global_mean_std(tr_x, te_x) mean_acc, max_acc, min_acc = eval_net_basic( tr_x, tr_y, te_x, te_y, net_func=cifar10_resnet_bottleneck_20) print("Mean accuracy: ", mean_acc) print("Max accuracy: ", max_acc) print("Min accuracy: ", min_acc)
def main(): tr_x, tr_y, te_x, te_y = load_cifar10_data() tr_x, te_x = global_mean_std(tr_x, te_x) mean_acc, max_acc, min_acc = eval_net_basic(tr_x, tr_y, te_x, te_y, net_func=partial( cifar10_se_resnext_29, cardinality=8, group_width=16)) print("Mean accuracy: ", mean_acc) print("Max accuracy: ", max_acc) print("Min accuracy: ", min_acc)