def features_and_labels() -> List[Tuple[Tensor, List[int]]]:
    """
    Returns: list of features and valid labels
    """
    num_batches = 100
    features_dim = 10

    labels_pk = generate_valid_labels(num=num_batches)
    labels_list, _, _ = zip(*labels_pk)

    features = []
    for labels in labels_list:
        features.append(torch.rand(size=(len(labels), features_dim)))

    return list(zip(features, labels_list))

    Returns: list of features and valid labels
    
tests/contrib/data/test_sampler_inbatch.py