def test_densenet40_k12(select_data, is_cuda): """ test densenet40_k12 model """ model = net.densenet40_k12() if is_cuda: model = model.cuda() images, _ = select_data output = model(images) utils.print_net_summary('./log_test', model, images)
def test_shufflenetv2_51_s2p0(select_data, device): """ shufflenetv1 - layers = 51 - scaling = 2.0 - channel_split = 0.5 """ model = net.shufflenetv2_51_s2p0().to(device) images, _ = select_data _ = model(images) utils.print_net_summary('./log_shufflenetv2_51_s2p0', model, images)
def test_shufflenetv1_50_s1p0_g8(select_data, device): """ shufflenetv1 - layers = 50 - scaling = 1.0 - groups = 8 """ model = net.shufflenetv1_50_s1p0_g8().to(device) images, _ = select_data _ = model(images) utils.print_net_summary('./log_shufflenetv1_50_s1p0_g8', model, images)
def test_shufflenetv1_50_s0p5_g4(select_data, device): """ shufflenetv1 - layers = 50 - scaling = 0.5 - groups = 4 """ model = net.shufflenetv1_50_s0p5_g4().to(device) images, _ = select_data _ = model(images) utils.print_net_summary('./log_shufflenetv1_50_s0p5_g4', model, images)
def test_mobilenetv1_28_1p25_32(select_data, device): """ test network structure of mobilenetv1 28 layers 1.25/32 """ model = net.mobilenetv1_28_1p25_32().to(device) images, _ = select_data _ = model(images) utils.print_net_summary('./log_test_mobilenetv1_28_1p25_32', model, images)
def test_mnasneta1(select_data, device): """ test mnasneta1 """ model = net.mnasneta1().to(device) images, _ = select_data _ = model(images) utils.print_net_summary('./log_test_mnasneta1', model, images)
def test_mobilenet20_1p0_t4(select_data, device): """ test network layer=20, width_mult=1.0, expansion=4 """ model = net.mobilenet20_1p0_t4().to(device) images, _ = select_data _ = model(images) utils.print_net_summary('./log_test_mobilenet20_1p0_t4', model, images)