Python data.create_dataset() Examples

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Example #1
Source File: test.py    From CAG_UDA with MIT License 6 votes vote down vote up 
def test(cfg, writer, logger):
    torch.manual_seed(cfg.get('seed', 1337))
    torch.cuda.manual_seed(cfg.get('seed', 1337))
    np.random.seed(cfg.get('seed', 1337))
    random.seed(cfg.get('seed', 1337))
    ## create dataset
    default_gpu = cfg['model']['default_gpu']
    device = torch.device("cuda:{}".format(default_gpu) if torch.cuda.is_available() else 'cpu')
    datasets = create_dataset(cfg, writer, logger)  #source_train\ target_train\ source_valid\ target_valid + _loader

    model = CustomModel(cfg, writer, logger)
    running_metrics_val = runningScore(cfg['data']['target']['n_class'])
    source_running_metrics_val = runningScore(cfg['data']['target']['n_class'])
    val_loss_meter = averageMeter()
    source_val_loss_meter = averageMeter()
    time_meter = averageMeter()
    loss_fn = get_loss_function(cfg)
    path = cfg['test']['path']
    checkpoint = torch.load(path)
    model.adaptive_load_nets(model.BaseNet, checkpoint['DeepLab']['model_state'])

    validation(
                model, logger, writer, datasets, device, running_metrics_val, val_loss_meter, loss_fn,\
                source_val_loss_meter, source_running_metrics_val, iters = model.iter
                )