Integration tests fail on macOS

The parallel dataloader tests still fail on macOS:

$ pytest -m slow
...
self = <tests.samplers.test_single.TestGridGeoSampler object at 0x13524a160>, sampler = <torchgeo.samplers.GridGeoSampler object at 0x13524a2e0>, num_workers = 2

    @pytest.mark.slow
    @pytest.mark.parametrize("num_workers", [0, 1, 2])
    def test_dataloader(self, sampler: GridGeoSampler, num_workers: int) -> None:
        ds = CustomGeoDataset()
        dl = DataLoader(
            ds, sampler=sampler, num_workers=num_workers, collate_fn=stack_samples
        )
>       for _ in dl:

tests/samplers/test_single.py:155: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../.spack/.spack-env/view/lib/python3.8/site-packages/torch/utils/data/dataloader.py:359: in __iter__
    return self._get_iterator()
../.spack/.spack-env/view/lib/python3.8/site-packages/torch/utils/data/dataloader.py:305: in _get_iterator
    return _MultiProcessingDataLoaderIter(self)
../.spack/.spack-env/view/lib/python3.8/site-packages/torch/utils/data/dataloader.py:918: in __init__
    w.start()
../.spack/.spack-env/._view/upu5ollpmvlcwd5wntc5ajlk2y3qkjpg/lib/python3.8/multiprocessing/process.py:121: in start
    self._popen = self._Popen(self)
../.spack/.spack-env/._view/upu5ollpmvlcwd5wntc5ajlk2y3qkjpg/lib/python3.8/multiprocessing/context.py:224: in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
../.spack/.spack-env/._view/upu5ollpmvlcwd5wntc5ajlk2y3qkjpg/lib/python3.8/multiprocessing/context.py:284: in _Popen
    return Popen(process_obj)
../.spack/.spack-env/._view/upu5ollpmvlcwd5wntc5ajlk2y3qkjpg/lib/python3.8/multiprocessing/popen_spawn_posix.py:32: in __init__
    super().__init__(process_obj)
../.spack/.spack-env/._view/upu5ollpmvlcwd5wntc5ajlk2y3qkjpg/lib/python3.8/multiprocessing/popen_fork.py:19: in __init__
    self._launch(process_obj)
../.spack/.spack-env/._view/upu5ollpmvlcwd5wntc5ajlk2y3qkjpg/lib/python3.8/multiprocessing/popen_spawn_posix.py:47: in _launch
    reduction.dump(process_obj, fp)
../.spack/.spack-env/._view/upu5ollpmvlcwd5wntc5ajlk2y3qkjpg/lib/python3.8/multiprocessing/reduction.py:60: in dump
    ForkingPickler(file, protocol).dump(obj)
torchgeo/datasets/geo.py:193: in __getstate__
    objects = self.index.intersection(self.index.bounds, objects=True)
../.spack/.spack-env/view/lib/python3.8/site-packages/rtree/index.py:680: in intersection
    return self._intersection_obj(coordinates, objects)
../.spack/.spack-env/view/lib/python3.8/site-packages/rtree/index.py:722: in _intersection_obj
    p_mins, p_maxs = self.get_coordinate_pointers(coordinates)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = rtree.index.Index(bounds=[1.7976931348623157e+308, -1.7976931348623157e+308, 1.7976931348623157e+308, -1.7976931348623157e+308, 1.7976931348623157e+308, -1.7976931348623157e+308], size=0)
coordinates = [1.7976931348623157e+308, 1.7976931348623157e+308, 1.7976931348623157e+308, -1.7976931348623157e+308, -1.7976931348623157e+308, -1.7976931348623157e+308]

    def get_coordinate_pointers(self, coordinates):
    
        try:
            iter(coordinates)
        except TypeError:
            raise TypeError('Bounds must be a sequence')
        dimension = self.properties.dimension
    
        mins = ctypes.c_double * dimension
        maxs = ctypes.c_double * dimension
    
        if not self.interleaved:
            coordinates = Index.interleave(coordinates)
    
        # it's a point make it into a bbox. [x, y] => [x, y, x, y]
        if len(coordinates) == dimension:
            coordinates += coordinates
    
        if len(coordinates) != dimension * 2:
            raise core.RTreeError(
                "Coordinates must be in the form "
                "(minx, miny, maxx, maxy) or (x, y) for 2D indexes")
    
        # so here all coords are in the form:
        # [xmin, ymin, zmin, xmax, ymax, zmax]
        for i in range(dimension):
            if not coordinates[i] <= coordinates[i + dimension]:
>               raise core.RTreeError(
                    "Coordinates must not have minimums more than maximums")
E               rtree.exceptions.RTreeError: Coordinates must not have minimums more than maximums

../.spack/.spack-env/view/lib/python3.8/site-packages/rtree/index.py:357: RTreeError

This bug was supposed to be fixed by #304, but this appears to be a new manifestation of #184. Also see https://github.com/Toblerity/rtree/issues/87 for details.

We should:

1. Fix this bug
2. Test macOS and Windows on the release branch

[weiji14]

What’s the length of this dataset? Those specific values tend to mean that the dataset is empty (i.e. there is no intersection between those datasets).

Actually you’re right, the size is 0. Doing print(intersection_dataset.index) gives rtree.index.Index(bounds=[1.7976931348623157e+308, -1.7976931348623157e+308, 1.7976931348623157e+308, -1.7976931348623157e+308, 1.7976931348623157e+308, -1.7976931348623157e+308], size=0). Let me double check what’s wrong with my dataset, sorry for the false alarm!

[adamjstewart]

What’s the length of this dataset? Those specific values tend to mean that the dataset is empty (i.e. there is no intersection between those datasets).