def test_ssd300():
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
model = Model(ssd300_mobilenetv2())
model.compile()
loc, score = model.predict(ts.ones((1, 3, 300, 300)))
print(loc.asnumpy(), score.asnumpy())
device_target=args_opt.device_target)
# download voc dataset
if not args_opt.dataset_path:
args_opt.dataset_path = download_dataset('voc')
epoch_size = args_opt.epoch_size
batch_size = args_opt.batch_size
voc_path = args_opt.dataset_path
dataset_sink_mode = not args_opt.device_target == "CPU"
if not args_opt.do_eval: # as for train, users could use model.train
ds_train = create_dataset(voc_path, batch_size=batch_size)
dataset_size = ds_train.get_dataset_size()
# build the SSD300 network
net = ssd300_mobilenetv2(class_num=args_opt.num_classes)
# define the loss function
if args_opt.device_target == "GPU":
net.to_float(ts.float16)
net = net_with_loss(net)
init_net_param(net)
# define the optimizer
lr = ssd300_lr(global_step=args_opt.pre_trained_epoch_size *
dataset_size,
lr_init=0.001,
lr_end=0.001 * args_opt.lr,
lr_max=args_opt.lr,
warmup_epochs=2,
total_epochs=args_opt.epoch_size,
steps_per_epoch=dataset_size)
loss_scale = 1.0 if args_opt.device_target == "CPU" else float(
device_target=args_opt.device_target)
# download voc dataset
if not args_opt.dataset_path:
args_opt.dataset_path = download_dataset('voc')
epoch_size = args_opt.epoch_size
batch_size = args_opt.batch_size
voc_path = args_opt.dataset_path
dataset_sink_mode = not args_opt.device_target == "CPU"
if not args_opt.do_eval: # as for train, users could use model.train
ds_train = create_dataset(voc_path, batch_size=batch_size)
dataset_size = ds_train.get_dataset_size()
# build the SSD300 network
net = ssd300_mobilenetv2(class_num=args_opt.num_classes)
# define the loss function
if args_opt.device_target == "GPU":
net.to_float(ts.float16)
net = net_with_loss(net)
init_net_param(net)
# define the optimizer
lr = ssd300_lr(global_step=args_opt.pre_trained_epoch_size *
dataset_size,
lr_init=0.001,
lr_end=0.001 * args_opt.lr,
lr_max=args_opt.lr,
warmup_epochs=2,
total_epochs=args_opt.epoch_size,
steps_per_epoch=dataset_size)
loss_scale = 1.0 if args_opt.device_target == "CPU" else float(