def main_with_asoftmaxloss(model):
"""
train model with vanilla ASoftmaxLoss as supervision
:param model:
:return:
"""
criterion_aloss = AngularLoss()
optimizer = optim.SGD(model.parameters(),
lr=cfg['init_lr'],
momentum=0.9,
weight_decay=cfg['weight_decay'])
cosine_anneal_warmup_lr_scheduler = lr_scheduler.CosineAnnealingWarmRestarts(
optimizer, T_0=10, T_mult=10, eta_min=0, last_epoch=-1)
print('start loading ImageDataset...')
trainloader, valloader, testloader = data_loader.load_imagedataset_data()
dataloaders = {'train': trainloader, 'val': valloader, 'test': testloader}
train_model_with_modified_softmax_loss(
model=model,
dataloaders=dataloaders,
criterion=criterion_aloss,
optimizer=optimizer,
scheduler=cosine_anneal_warmup_lr_scheduler)
def main_with_arcloss(model):
"""
train model
:param model:
:param epoch:
:return:
"""
criterion_xent_loss = nn.CrossEntropyLoss()
arc_metric = ArcLoss(args['dim'], cfg['out_num'])
optimizer = optim.SGD(model.parameters(),
lr=0.01,
momentum=0.9,
weight_decay=1e-4)
exp_lr_scheduler = lr_scheduler.StepLR(optimizer, step_size=60, gamma=0.1)
print('start loading ImageDataset...')
trainloader, valloader, testloader = data_loader.load_imagedataset_data()
dataloaders = {'train': trainloader, 'val': valloader, 'test': testloader}
train_model_for_arcloss(model=model,
dataloaders=dataloaders,
criterion=criterion_xent_loss,
optimizer=optimizer,
metric=arc_metric,
scheduler=exp_lr_scheduler)
def main_with_centerloss(model):
"""
train model
:param model:
:param epoch:
:param data_name:
:return:
"""
criterion_xent = nn.CrossEntropyLoss()
criterion_cent = CenterLoss(num_classes=cfg['out_num'], feat_dim=1024)
optimizer_model = optim.SGD(model.parameters(),
lr=0.01,
momentum=0.9,
weight_decay=1e-4)
optimizer_centloss = optim.SGD(criterion_cent.parameters(), lr=0.5)
cosine_anneal_warmup_lr_scheduler = lr_scheduler.CosineAnnealingWarmRestarts(
optimizer_model, T_0=10, T_mult=10, eta_min=0, last_epoch=-1)
print('start loading ImageDataset...')
trainloader, valloader, testloader = data_loader.load_imagedataset_data()
dataloaders = {'train': trainloader, 'val': valloader, 'test': testloader}
train_model_for_centerloss(model=model,
dataloaders=dataloaders,
criterion_xent=criterion_xent,
criterion_cent=criterion_cent,
optimizer_model=optimizer_model,
optimizer_centloss=optimizer_centloss,
scheduler=cosine_anneal_warmup_lr_scheduler)