Function data_loader

tests/python/common.py:57–78

(
    nchannel=3,
    max_label=5,
    is_classification=True,
    seed=-1,
    batch_size=2,
    dtype=torch.float32,
)

def data_loader(
    nchannel=3,
    max_label=5,
    is_classification=True,
    seed=-1,
    batch_size=2,
    dtype=torch.float32,
):
    if seed >= 0:
        torch.manual_seed(seed)

    data = ["   X   ", "  X X  ", " XXXXX "]

    # Generate coordinates
    coords = [get_coords(data) for i in range(batch_size)]
    coords = ME.utils.batched_coordinates(coords)

    # features and labels
    N = len(coords)
    feats = torch.arange(N * nchannel).view(N, nchannel).to(dtype)
    label = (torch.rand(batch_size if is_classification else N) * max_label).long()
    return coords, feats, label