diff --git a/test/test_tensorboard.py b/test/test_tensorboard.py index 8ff6913887c..376e24023a5 100644 --- a/test/test_tensorboard.py +++ b/test/test_tensorboard.py @@ -40,9 +40,9 @@ skipIfNoMatplotlib = unittest.skipIf(not TEST_MATPLOTLIB, "no matplotlib") import torch from torch.testing._internal.common_utils import ( instantiate_parametrized_tests, + parametrize, IS_MACOS, IS_WINDOWS, - parametrize, run_tests, skipIfTorchDynamo, TEST_WITH_CROSSREF, @@ -487,38 +487,23 @@ class TestTensorBoardSummary(BaseTestCase): summary.video("dummy", np.random.rand(16, 48, 1, 28, 28)) summary.video("dummy", np.random.rand(20, 7, 1, 8, 8)) - @unittest.skipIf( - IS_MACOS, "Skipping on mac, see https://github.com/pytorch/pytorch/pull/109349 " - ) @xfailIfS390X def test_audio(self): self.assertProto(summary.audio("dummy", tensor_N(shape=(42,)))) - @unittest.skipIf( - IS_MACOS, "Skipping on mac, see https://github.com/pytorch/pytorch/pull/109349 " - ) def test_text(self): self.assertProto(summary.text("dummy", "text 123")) - @unittest.skipIf( - IS_MACOS, "Skipping on mac, see https://github.com/pytorch/pytorch/pull/109349 " - ) def test_histogram_auto(self): self.assertProto( summary.histogram("dummy", tensor_N(shape=(1024,)), bins="auto", max_bins=5) ) - @unittest.skipIf( - IS_MACOS, "Skipping on mac, see https://github.com/pytorch/pytorch/pull/109349 " - ) def test_histogram_fd(self): self.assertProto( summary.histogram("dummy", tensor_N(shape=(1024,)), bins="fd", max_bins=5) ) - @unittest.skipIf( - IS_MACOS, "Skipping on mac, see https://github.com/pytorch/pytorch/pull/109349 " - ) def test_histogram_doane(self): self.assertProto( summary.histogram( @@ -538,9 +523,6 @@ class TestTensorBoardSummary(BaseTestCase): layout ) # only smoke test. Because protobuf in python2/3 serialize dictionary differently. - @unittest.skipIf( - IS_MACOS, "Skipping on mac, see https://github.com/pytorch/pytorch/pull/109349 " - ) def test_mesh(self): v = np.array([[[1, 1, 1], [-1, -1, 1], [1, -1, -1], [-1, 1, -1]]], dtype=float) c = np.array( @@ -550,9 +532,6 @@ class TestTensorBoardSummary(BaseTestCase): mesh = summary.mesh("my_mesh", vertices=v, colors=c, faces=f, config_dict=None) self.assertProto(mesh) - @unittest.skipIf( - IS_MACOS, "Skipping on mac, see https://github.com/pytorch/pytorch/pull/109349 " - ) def test_scalar_new_style(self): scalar = summary.scalar("test_scalar", 1.0, new_style=True) self.assertProto(scalar) @@ -799,11 +778,15 @@ class TestTensorBoardFigure(BaseTestCase): figures.append(figure) writer.add_figure("add_figure/figure_list", figures, 0, close=False) - self.assertTrue(all(plt.fignum_exists(figure.number) is True for figure in figures)) # noqa: F812 + self.assertTrue( + all(plt.fignum_exists(figure.number) is True for figure in figures) + ) # noqa: F812 writer.add_figure("add_figure/figure_list", figures, 1) if matplotlib.__version__ != "3.3.0": - self.assertTrue(all(plt.fignum_exists(figure.number) is False for figure in figures)) # noqa: F812 + self.assertTrue( + all(plt.fignum_exists(figure.number) is False for figure in figures) + ) # noqa: F812 else: print( "Skipping fignum_exists, see https://github.com/matplotlib/matplotlib/issues/18163" @@ -813,13 +796,6 @@ class TestTensorBoardFigure(BaseTestCase): class TestTensorBoardNumpy(BaseTestCase): - @unittest.skipIf( - IS_WINDOWS, - "Skipping on windows, see https://github.com/pytorch/pytorch/pull/109349 ", - ) - @unittest.skipIf( - IS_MACOS, "Skipping on mac, see https://github.com/pytorch/pytorch/pull/109349 " - ) def test_scalar(self): res = make_np(1.1) self.assertIsInstance(res, np.ndarray) and self.assertEqual(res.shape, (1,)) @@ -827,8 +803,9 @@ class TestTensorBoardNumpy(BaseTestCase): self.assertIsInstance(res, np.ndarray) and self.assertEqual(res.shape, (1,)) res = make_np(np.float16(1.00000087)) self.assertIsInstance(res, np.ndarray) and self.assertEqual(res.shape, (1,)) - res = make_np(np.float128(1.00008 + 9)) - self.assertIsInstance(res, np.ndarray) and self.assertEqual(res.shape, (1,)) + if not IS_MACOS and not IS_WINDOWS: + res = make_np(np.float128(1.00008 + 9)) + self.assertIsInstance(res, np.ndarray) and self.assertEqual(res.shape, (1,)) res = make_np(np.int64(100000000000)) self.assertIsInstance(res, np.ndarray) and self.assertEqual(res.shape, (1,))