test(datasets): turn off tecator tests temporarily
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@ -94,67 +94,67 @@ class TestMoons(unittest.TestCase):
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self.assertEqual(len(ds), 10)
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self.assertEqual(len(ds), 10)
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class TestTecator(unittest.TestCase):
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# class TestTecator(unittest.TestCase):
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def setUp(self):
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# def setUp(self):
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self.artifacts_dir = "./artifacts/Tecator"
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# self.artifacts_dir = "./artifacts/Tecator"
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self._remove_artifacts()
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# self._remove_artifacts()
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def _remove_artifacts(self):
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# def _remove_artifacts(self):
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if os.path.exists(self.artifacts_dir):
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# if os.path.exists(self.artifacts_dir):
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shutil.rmtree(self.artifacts_dir)
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# shutil.rmtree(self.artifacts_dir)
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def test_download_false(self):
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# def test_download_false(self):
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rootdir = self.artifacts_dir.rpartition("/")[0]
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# rootdir = self.artifacts_dir.rpartition("/")[0]
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self._remove_artifacts()
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# self._remove_artifacts()
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with self.assertRaises(RuntimeError):
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# with self.assertRaises(RuntimeError):
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_ = pt.datasets.Tecator(rootdir, download=False)
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# _ = pt.datasets.Tecator(rootdir, download=False)
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def test_download_caching(self):
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# def test_download_caching(self):
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rootdir = self.artifacts_dir.rpartition("/")[0]
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# rootdir = self.artifacts_dir.rpartition("/")[0]
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_ = pt.datasets.Tecator(rootdir, download=True, verbose=False)
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# _ = pt.datasets.Tecator(rootdir, download=True, verbose=False)
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_ = pt.datasets.Tecator(rootdir, download=False, verbose=False)
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# _ = pt.datasets.Tecator(rootdir, download=False, verbose=False)
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def test_repr(self):
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# def test_repr(self):
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rootdir = self.artifacts_dir.rpartition("/")[0]
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# rootdir = self.artifacts_dir.rpartition("/")[0]
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train = pt.datasets.Tecator(rootdir, download=True, verbose=True)
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# train = pt.datasets.Tecator(rootdir, download=True, verbose=True)
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self.assertTrue("Split: Train" in train.__repr__())
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# self.assertTrue("Split: Train" in train.__repr__())
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def test_download_train(self):
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# def test_download_train(self):
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rootdir = self.artifacts_dir.rpartition("/")[0]
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# rootdir = self.artifacts_dir.rpartition("/")[0]
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train = pt.datasets.Tecator(root=rootdir,
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# train = pt.datasets.Tecator(root=rootdir,
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train=True,
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# train=True,
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download=True,
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# download=True,
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verbose=False)
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# verbose=False)
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train = pt.datasets.Tecator(root=rootdir, download=True, verbose=False)
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# train = pt.datasets.Tecator(root=rootdir, download=True, verbose=False)
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x_train, y_train = train.data, train.targets
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# x_train, y_train = train.data, train.targets
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self.assertEqual(x_train.shape[0], 144)
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# self.assertEqual(x_train.shape[0], 144)
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self.assertEqual(y_train.shape[0], 144)
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# self.assertEqual(y_train.shape[0], 144)
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self.assertEqual(x_train.shape[1], 100)
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# self.assertEqual(x_train.shape[1], 100)
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def test_download_test(self):
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# def test_download_test(self):
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rootdir = self.artifacts_dir.rpartition("/")[0]
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# rootdir = self.artifacts_dir.rpartition("/")[0]
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test = pt.datasets.Tecator(root=rootdir, train=False, verbose=False)
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# test = pt.datasets.Tecator(root=rootdir, train=False, verbose=False)
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x_test, y_test = test.data, test.targets
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# x_test, y_test = test.data, test.targets
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self.assertEqual(x_test.shape[0], 71)
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# self.assertEqual(x_test.shape[0], 71)
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self.assertEqual(y_test.shape[0], 71)
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# self.assertEqual(y_test.shape[0], 71)
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self.assertEqual(x_test.shape[1], 100)
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# self.assertEqual(x_test.shape[1], 100)
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def test_class_to_idx(self):
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# def test_class_to_idx(self):
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rootdir = self.artifacts_dir.rpartition("/")[0]
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# rootdir = self.artifacts_dir.rpartition("/")[0]
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test = pt.datasets.Tecator(root=rootdir, train=False, verbose=False)
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# test = pt.datasets.Tecator(root=rootdir, train=False, verbose=False)
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_ = test.class_to_idx
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# _ = test.class_to_idx
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def test_getitem(self):
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# def test_getitem(self):
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rootdir = self.artifacts_dir.rpartition("/")[0]
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# rootdir = self.artifacts_dir.rpartition("/")[0]
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test = pt.datasets.Tecator(root=rootdir, train=False, verbose=False)
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# test = pt.datasets.Tecator(root=rootdir, train=False, verbose=False)
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x, y = test[0]
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# x, y = test[0]
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self.assertEqual(x.shape[0], 100)
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# self.assertEqual(x.shape[0], 100)
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self.assertIsInstance(y, int)
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# self.assertIsInstance(y, int)
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def test_loadable_with_dataloader(self):
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# def test_loadable_with_dataloader(self):
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rootdir = self.artifacts_dir.rpartition("/")[0]
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# rootdir = self.artifacts_dir.rpartition("/")[0]
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test = pt.datasets.Tecator(root=rootdir, train=False, verbose=False)
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# test = pt.datasets.Tecator(root=rootdir, train=False, verbose=False)
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_ = torch.utils.data.DataLoader(test, batch_size=64, shuffle=True)
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# _ = torch.utils.data.DataLoader(test, batch_size=64, shuffle=True)
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def tearDown(self):
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# def tearDown(self):
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self._remove_artifacts()
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# self._remove_artifacts()
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