def start(args):
if args.order == 'train':
train(args)
elif args.order == 'valid':
valid(args)
compute_mAP(args)
draw(args, 'loss')
elif args.order == 'draw':
draw(args)
def train():
if request.method == 'POST':
dt = {'dataset_dir': request.form['dataset_dir']}
else:
dt = {'dataset_dir': request.args.get('dir')}
return operations.train(dt)
def start():
args = set_global_variables()
import operations
if args.order == 'train':
operations.train(args)
print("#------train process is over!------#")
elif args.order == 'valid':
args.draw_option = 'mAP'
operations.valid(args)
operations.compute(args)
operations.draw(args)
print("#------valid process is over!------#")
elif args.order == 'draw':
operations.draw(args)
elif args.order == 'compute':
if args.compute_step is None:
print("The compute_step cannot be None!")
exit()
operations.compute(args)
print(net)
print()
avg_train_loss = 0
avg_train_acc = 0
avg_val_loss = 0
avg_val_acc = 0
loaders = get_strange_symbol_loader_with_validation(
batch_size=args.batch_size, validation_split=args.s)
train_loader, val_loader = loaders
train_stats = train(net,
train_loader,
args.learning_rate,
args.momentum,
epochs=args.epochs,
epslon=args.epslon)
print('[TRAINING] Final loss', train_stats[0])
print('[TRAINING] Final acc', train_stats[1])
avg_val_loss, avg_val_acc = validate(net, val_loader)
print('[VALIDATION] Final loss', avg_val_loss)
print('[VALIDATION] Final acc', avg_val_acc)
print()
predictions = []
labels = []