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)