Function build_dataset_func

main.py:104–132

(args)

def build_dataset_func(args):
    
    datasets = {
        'train': [], 
        'test': []
    }
    
    for dataset in args.dataset.split(','):
        dataset_module = importlib.import_module(f'datasets.{dataset}')
        datasets['train'].append(
            dataset_module.Dataset(args, split_set="train", augment=args.augment)
        )
        datasets['test'].append(
            dataset_module.Dataset(args, split_set="val", augment=False)
        )
    datasets['train'] = torch.utils.data.ConcatDataset(datasets['train'])
    
    train_sampler, train_loader = build_dataloader_func(args, datasets['train'], split='train')
    dataloaders = {
        'train': train_loader,
        'test': [],
        'train_sampler': train_sampler,
    }
    
    for dataset in datasets['test']:
        _, test_loader = build_dataloader_func(args, dataset, split='test')
        dataloaders['test'].append(test_loader)
    
    return datasets, dataloaders    


def build_model_func(args):