def test_errors():
schema = SchemaDict(
{
"a": Tensor((None, None), dtype=int, max_shape=(20, 20)),
"b": Sequence(
dtype=SchemaDict(
{"e": Tensor((None,), max_shape=(10,), dtype=BBox(dtype=float))}
)
),
"c": Sequence(
dtype=SchemaDict({"d": Sequence((), dtype=Tensor((5, 5), dtype=float))})
),
}
)
ds = hub.Dataset("./nested_seq", shape=(5,), mode="w", schema=schema)
# Invalid schema
with pytest.raises(ValueError):
ds["b", 0, "e", 1]
# Too many indices
with pytest.raises(IndexError):
ds["c", 0, "d", 1, 1, 0, 0, 0]
with pytest.raises(IndexError):
ds["c", :2, "d"][0, 1, 1, 0, 0, 0]
ob = ds["c", :2, "d"][0, 2:5, 1, 0, 0]
assert str(ob[1]) == "ObjectView(subpath='/c/d', indexes=0, slice=[3, 1, 0, 0])"
with pytest.raises(IndexError):
ob[1, 0]
# Key Errors
# wrong key
with pytest.raises(KeyError):
ds["b", "c"]
# too many keys
with pytest.raises(KeyError):
ds["c", "d", "e"]
with pytest.raises(KeyError):
ds["c", "d"]["e"]
def test_objectview():
schema = SchemaDict({
"a":
Tensor((20, 20), dtype=int, max_shape=(20, 20)),
"b":
Sequence(dtype=BBox(dtype=float)),
"c":
Sequence(dtype=SchemaDict(
{"d": Sequence((), dtype=Tensor((5, 5), dtype=float))})),
"e":
Sequence(dtype={
"f": {
"g": Tensor(5, dtype=int),
"h": Tensor((), dtype=int)
}
}),
})
ds = hub.Dataset("./nested_seq", shape=(5, ), mode="w", schema=schema)
# dataset view to objectview
dv = ds[3:5]
dv["c", 0] = {"d": 5 * np.ones((2, 2, 5, 5))}
assert (dv[0, "c", 0, "d", 0].compute() == 5 * np.ones((5, 5))).all()
# dataset view unsqueezed
with pytest.raises(IndexError):
dv["c", "d"].compute()
# dataset unsqueezed
with pytest.raises(IndexError):
ds["c", "d"].compute()
# tensorview to object view
# sequence of tensor
ds["b", 0] = 0.5 * np.ones((5, 4))
tv = ds["b", 0]
tv[0] = 0.3 * np.ones((4, ))
assert (tv[0].compute() == 0.3 * np.ones((4, ))).all()
# ds to object view
assert (ds[3, "c", "d"].compute() == 5 * np.ones((2, 2, 5, 5))).all()
# Sequence of schemadicts
ds[0, "e"] = {"f": {"g": np.ones((3, 5)), "h": np.array([42, 25, 15])}}
with pytest.raises(KeyError):
ds[0, "e", 1].compute()
assert (ds[0, "e", "f", "h"].compute() == np.array([42, 25, 15])).all()
# With dataset view
dv[0, "e"] = {"f": {"g": np.ones((3, 5)), "h": np.array([1, 25, 1])}}
# dv[0, "e", 1]["f", "h"] = 25
assert (dv[0, "e", "f", "h"].compute() == np.array([1, 25, 1])).all()
# If not lazy mode all slices should be stable
ds.lazy = False
assert ds[0, "e", 0, "f", "h"] == 42
with pytest.raises(KeyError):
ds[0, "e", 1]["f", "h"] == 25
ds.lazy = True
# make an objectview
ov = ds["c", "d"]
with pytest.raises(IndexError):
ov.compute()
assert (ov[3].compute() == 5 * np.ones((2, 2, 5, 5))).all()
# ov[3, 1] = 2 * np.ones((2, 5, 5))
assert (ov[3][0, 0].compute() == 5 * np.ones((5, 5))).all()
assert (ov[3][1].compute() == 5 * np.ones((2, 5, 5))).all()