def test_download_train(self):
rootdir = self.artifacts_dir.rpartition('/')[0]
train = tecator.Tecator(root=rootdir,
train=True,
download=True,
verbose=False)
train = tecator.Tecator(root=rootdir, download=True, verbose=False)
x_train, y_train = train.data, train.targets
self.assertEqual(x_train.shape[0], 144)
self.assertEqual(y_train.shape[0], 144)
self.assertEqual(x_train.shape[1], 100)
def test_download_test(self):
rootdir = self.artifacts_dir.rpartition('/')[0]
test = tecator.Tecator(root=rootdir, train=False, verbose=False)
x_test, y_test = test.data, test.targets
self.assertEqual(x_test.shape[0], 71)
self.assertEqual(y_test.shape[0], 71)
self.assertEqual(x_test.shape[1], 100)
def test_loadable_with_dataloader(self):
rootdir = self.artifacts_dir.rpartition('/')[0]
test = tecator.Tecator(root=rootdir, train=False, verbose=False)
_ = torch.utils.data.DataLoader(test, batch_size=64, shuffle=True)
def test_getitem(self):
rootdir = self.artifacts_dir.rpartition('/')[0]
test = tecator.Tecator(root=rootdir, train=False, verbose=False)
x, y = test[0]
self.assertEqual(x.shape[0], 100)
self.assertIsInstance(y, int)
def test_class_to_idx(self):
rootdir = self.artifacts_dir.rpartition('/')[0]
test = tecator.Tecator(root=rootdir, train=False, verbose=False)
_ = test.class_to_idx
def test_repr(self):
rootdir = self.artifacts_dir.rpartition('/')[0]
train = tecator.Tecator(rootdir, download=True, verbose=True)
self.assertTrue('Split: Train' in train.__repr__())
def test_download_caching(self):
rootdir = self.artifacts_dir.rpartition('/')[0]
_ = tecator.Tecator(rootdir, download=True, verbose=False)
_ = tecator.Tecator(rootdir, download=False, verbose=False)
def test_download_false(self):
rootdir = self.artifacts_dir.rpartition('/')[0]
self._remove_artifacts()
with self.assertRaises(RuntimeError):
_ = tecator.Tecator(rootdir, download=False)