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)