def run_nsfw(model, epoch):
"""
run NSFW
:param model:
:param epoch:
:return:
"""
criterion = nn.CrossEntropyLoss()
optimizer_ft = optim.SGD(model.parameters(),
lr=cfg['init_lr'],
momentum=0.9,
weight_decay=cfg['weight_decay'])
exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft,
step_size=cfg['lr_decay_step'],
gamma=0.1)
print('start loading NSFWDataset...')
trainloader, valloader, testloader = data_loader.load_nsfw_data()
dataloaders = {
'train': trainloader,
'val': valloader,
'test': testloader,
}
train_model(model=model,
dataloaders=dataloaders,
criterion=criterion,
optimizer=optimizer_ft,
scheduler=exp_lr_scheduler,
num_epochs=epoch,
inference=False)
def finetune_nsfw_classification(model, epoch):
"""
finetune NSFW classification
:param model:
:param epoch:
:return:
"""
criterion = nn.CrossEntropyLoss()
optimizer_ft = optim.SGD(model.parameters(), lr=args['learning_rate'], momentum=0.9,
weight_decay=args['weight_decay'])
exp_lr_scheduler = lr_scheduler.StepLR(optimizer_ft, step_size=args['step'], gamma=0.1)
print('start loading NSFW Dataset...')
trainloader, valloader, testloader = data_loader.load_nsfw_data()
dataloaders = {
'train': trainloader,
'val': valloader,
'test': testloader,
}
finetune_model(model=model, dataloaders=dataloaders, criterion=criterion, optimizer=optimizer_ft,
scheduler=exp_lr_scheduler, num_epochs=epoch, inference=args['inference'])