Function _train_loader_from_config

datasets/build.py:253–280

(cfg, dataset_name, mapper, *, dataset=None, sampler=None)

def _train_loader_from_config(cfg, dataset_name, mapper, *, dataset=None, sampler=None):
    cfg_datasets = cfg['DATASETS']
    cfg_dataloader = cfg['DATALOADER']
    
    if dataset is None:
        dataset = get_detection_dataset_dicts(
            dataset_name,
            filter_empty=cfg_dataloader['FILTER_EMPTY_ANNOTATIONS'],
            proposal_files=cfg_datasets['PROPOSAL_FILES_TRAIN'] if cfg_dataloader['LOAD_PROPOSALS'] else None,
        )

    if mapper is None:
        mapper = DatasetMapper(cfg, True)

    if sampler is None:
        sampler_name = cfg_dataloader['SAMPLER_TRAIN']
        logger = logging.getLogger(__name__)
        logger.info("Using training sampler {}".format(sampler_name))
        sampler = TrainingSampler(len(dataset))

    return {
        "dataset": dataset,
        "sampler": sampler,
        "mapper": mapper,
        "total_batch_size": cfg['TRAIN']['BATCH_SIZE_TOTAL'],
        "aspect_ratio_grouping": cfg_dataloader['ASPECT_RATIO_GROUPING'],
        "num_workers": cfg_dataloader['NUM_WORKERS'],
    }


@configurable(from_config=_train_loader_from_config)