def main():
args = parse_args()
if args.bn_sync:
if HAS_BN_SYNC:
dla_up.set_bn(batchnormsync.BatchNormSync)
else:
print('batch normalization synchronization across GPUs '
'is not imported.')
if args.cmd == 'train':
train_seg(args)
elif args.cmd == 'test':
test_seg(args)
def main():
args = parse_args()
if args.bn_sync:
if HAS_BN_SYNC:
dla_up.set_bn(batchnormsync.BatchNormSync)
else:
print('batch normalization synchronization across GPUs '
'is not imported.')
timestamp = datetime.fromtimestamp(time.time()).strftime('%Y%n%d-%H:%M')
writer = SummaryWriter('logs/{}'.format(timestamp))
if args.cmd == 'train':
train_seg(args, writer)
elif args.cmd == 'test':
test_seg(args, writer)
def main():
args = parse_args()
if not exists(args.checkpoint_dir) and args.checkpoint_dir != '':
os.makedirs(args.checkpoint_dir)
if args.bn_sync:
if HAS_BN_SYNC:
dla_up.set_bn(batchnormsync.BatchNormSync)
else:
print('batch normalization synchronization across GPUs '
'is not imported.')
if args.cmd == 'train':
train_seg(args)
elif args.cmd == 'test':
test_seg(args)
