Use github actions for CI (#10)

* chore: Absolute imports

* feat: Add new mesh util

* chore: replace bumpversion

original fork no longer maintained, move config

* ci: remove old configuration files

* ci: update github action

* ci: add python 3.10 test

* chore: update pre-commit hooks

* ci: update supported python versions

supported are 3.7, 3.8 and 3.9.

3.6 had EOL in december 2021.
3.10 has no pytorch distribution yet.

* ci: add windows test

* ci: update action

less windows tests, pre commit

* ci: fix typo

* chore: run precommit for all files

* ci: two step tests

* ci: compatibility waits for style

* fix: init file had missing imports

* ci: add deployment script

* ci: skip complete publish step

* ci: cleanup readme

tests/test_core.py

@@ -404,6 +404,7 @@ def test_glvq_loss_one_hot_unequal():
 
 # Activations
 class TestActivations(unittest.TestCase):
+
     def setUp(self):
         self.flist = ["identity", "sigmoid_beta", "swish_beta"]
         self.x = torch.randn(1024, 1)
@@ -418,6 +419,7 @@ class TestActivations(unittest.TestCase):
             self.assertTrue(iscallable)
 
     def test_callable_deserialization(self):
+
         def dummy(x, **kwargs):
             return x
 
@@ -462,6 +464,7 @@ class TestActivations(unittest.TestCase):
 
 # Competitions
 class TestCompetitions(unittest.TestCase):
+
     def setUp(self):
         pass
 
@@ -515,6 +518,7 @@ class TestCompetitions(unittest.TestCase):
 
 # Pooling
 class TestPooling(unittest.TestCase):
+
     def setUp(self):
         pass
 
@@ -615,6 +619,7 @@ class TestPooling(unittest.TestCase):
 
 # Distances
 class TestDistances(unittest.TestCase):
+
     def setUp(self):
         self.nx, self.mx = 32, 2048
         self.ny, self.my = 8, 2048

tests/test_datasets.py

@@ -12,6 +12,7 @@ from prototorch.datasets.abstract import Dataset, ProtoDataset
 
 
 class TestAbstract(unittest.TestCase):
+
     def setUp(self):
         self.ds = Dataset("./artifacts")
 
@@ -28,6 +29,7 @@ class TestAbstract(unittest.TestCase):
 
 
 class TestProtoDataset(unittest.TestCase):
+
     def test_download(self):
         with self.assertRaises(NotImplementedError):
             _ = ProtoDataset("./artifacts", download=True)
@@ -38,6 +40,7 @@ class TestProtoDataset(unittest.TestCase):
 
 
 class TestNumpyDataset(unittest.TestCase):
+
     def test_list_init(self):
         ds = pt.datasets.NumpyDataset([1], [1])
         self.assertEqual(len(ds), 1)
@@ -50,6 +53,7 @@ class TestNumpyDataset(unittest.TestCase):
 
 
 class TestCSVDataset(unittest.TestCase):
+
     def setUp(self):
         data = np.random.rand(100, 4)
         targets = np.random.randint(2, size=(100, 1))
@@ -67,12 +71,14 @@ class TestCSVDataset(unittest.TestCase):
 
 
 class TestSpiral(unittest.TestCase):
+
     def test_init(self):
         ds = pt.datasets.Spiral(num_samples=10)
         self.assertEqual(len(ds), 10)
 
 
 class TestIris(unittest.TestCase):
+
     def setUp(self):
         self.ds = pt.datasets.Iris()
 
@@ -88,24 +94,28 @@ class TestIris(unittest.TestCase):
 
 
 class TestBlobs(unittest.TestCase):
+
     def test_size(self):
         ds = pt.datasets.Blobs(num_samples=10)
         self.assertEqual(len(ds), 10)
 
 
 class TestRandom(unittest.TestCase):
+
     def test_size(self):
         ds = pt.datasets.Random(num_samples=10)
         self.assertEqual(len(ds), 10)
 
 
 class TestCircles(unittest.TestCase):
+
     def test_size(self):
         ds = pt.datasets.Circles(num_samples=10)
         self.assertEqual(len(ds), 10)
 
 
 class TestMoons(unittest.TestCase):
+
     def test_size(self):
         ds = pt.datasets.Moons(num_samples=10)
         self.assertEqual(len(ds), 10)