def test_meta_information():
description = {"author": "testing", "description": "here goes the testing text"}
description_changed = {
"author": "changed author",
"description": "now it's changed",
}
schema = {"text": Text((None,), max_shape=(1000,))}
ds = Dataset(
"./data/test_meta",
shape=(10,),
schema=schema,
meta_information=description,
mode="w",
)
some_text = ["hello world", "hello penguin", "hi penguin"]
for i, text in enumerate(some_text):
ds["text", i] = text
assert type(ds.meta["meta_info"]) == dict
assert ds.meta["meta_info"]["author"] == "testing"
assert ds.meta["meta_info"]["description"] == "here goes the testing text"
ds.close()
def test_dataset_append_and_read():
dt = {"first": "float", "second": "float"}
os.makedirs("./data/test/test_dataset_append_and_read", exist_ok=True)
shutil.rmtree("./data/test/test_dataset_append_and_read")
ds = Dataset(
schema=dt,
shape=(2,),
url="./data/test/test_dataset_append_and_read",
mode="a",
)
ds["first"][0] = 2.3
ds.meta_information["description"] = "This is my description"
assert ds.meta_information["description"] == "This is my description"
assert ds["second"][0].numpy() != 2.3
ds.close()
ds = Dataset(
url="./data/test/test_dataset_append_and_read",
mode="r",
)
assert ds.meta_information["description"] == "This is my description"
ds.meta_information["hello"] = 5
ds.delete()
ds.close()
def test_dataset_bug_3(url="./data/test/dataset", token=None):
my_schema = {
"image": Tensor((100, 100), "uint8"),
}
ds = Dataset(url, token=token, shape=(10000,), mode="w", schema=my_schema)
ds.close()
ds = Dataset(url)
ds["image", 0:1] = [np.zeros((100, 100))]
def test_dataset_wrong_append(url="./data/test/dataset", token=None):
my_schema = {
"image": Tensor((100, 100), "uint8"),
}
ds = Dataset(url, token=token, shape=(10000, ), mode="w", schema=my_schema)
ds.close()
with pytest.raises(TypeError):
ds = Dataset(url, shape=100)
with pytest.raises(SchemaMismatchException):
ds = Dataset(url, schema={"hello": "uint8"})
def test_dataset(url="./data/test/dataset", token=None, public=True):
ds = Dataset(
url, token=token, shape=(10000,), mode="w", schema=my_schema, public=public
)
sds = ds[5]
sds["label/a", 50, 50] = 2
assert sds["label", 50, 50, "a"].numpy() == 2
ds["image", 5, 4, 100:200, 150:300, :] = np.ones((100, 150, 3), "uint8")
assert (
ds["image", 5, 4, 100:200, 150:300, :].numpy()
== np.ones((100, 150, 3), "uint8")
).all()
ds["image", 8, 6, 500:550, 700:730] = np.ones((50, 30, 3))
subds = ds[3:15]
subsubds = subds[4:9]
assert (
subsubds["image", 1, 6, 500:550, 700:730].numpy() == np.ones((50, 30, 3))
).all()
subds = ds[5:7]
ds["image", 6, 3:5, 100:135, 700:720] = 5 * np.ones((2, 35, 20, 3))
assert (
subds["image", 1, 3:5, 100:135, 700:720].numpy() == 5 * np.ones((2, 35, 20, 3))
).all()
ds["label", "c"] = 4 * np.ones((10000, 5, 3), "uint8")
assert (ds["label/c"].numpy() == 4 * np.ones((10000, 5, 3), "uint8")).all()
ds["label", "c", 2, 4] = 6 * np.ones((3))
sds = ds["label", "c"]
ssds = sds[1:3, 4]
sssds = ssds[1]
assert (sssds.numpy() == 6 * np.ones((3))).all()
ds.save()
sds = ds["/label", 5:15, "c"]
sds[2:4, 4, :] = 98 * np.ones((2, 3))
assert (ds[7:9, 4, "label", "/c"].numpy() == 98 * np.ones((2, 3))).all()
labels = ds["label", 1:5]
d = labels["d"]
e = d["e"]
e[:] = 77 * np.ones((4, 5, 3))
assert (e.numpy() == 77 * np.ones((4, 5, 3))).all()
ds.close()
def test_dataset_wrong_append(url="./data/test/dataset", token=None):
my_schema = {
"image": Tensor((100, 100), "uint8"),
}
ds = Dataset(url, token=token, shape=(10000,), mode="w", schema=my_schema)
ds.close()
try:
ds = Dataset(url, shape=100)
except Exception as ex:
assert isinstance(ex, TypeError)
try:
ds = Dataset(url, schema={"hello": "uint8"})
except Exception as ex:
assert isinstance(ex, TypeError)
def test_dataset_append_and_read():
dt = {"first": "float", "second": "float"}
ds = Dataset(
schema=dt,
shape=(2,),
url="./data/test/test_dataset_append_and_read",
mode="a",
)
ds["first"][0] = 2.3
assert ds["second"][0].numpy() != 2.3
ds.close()
ds = Dataset(
url="./data/test/test_dataset_append_and_read",
mode="r",
)
ds.delete()
ds.close()
