Enable unit tests for ROCm 2.3 (#19307)

Summary:
Unit tests that hang on clock64() calls are now fixed.

test_gamma_gpu_sample is now fixed.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/19307

Differential Revision: D14953420

Pulled By: bddppq

fbshipit-source-id: efe807b54e047578415eb1b1e03f8ad44ea27c13

diff --git a/test/test_cuda.py b/test/test_cuda.py
index 4e7ce5a..6774b72 100644 (file)
--- a/test/test_cuda.py
+++ b/test/test_cuda.py
@@ -962,7 +962,6 @@ class TestCuda(TestCase):
         self.assertEqual(y, x)
 
     @unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
-    @skipIfRocm
     def test_copy_streams(self):
         d0 = torch.device('cuda:0')
         x0 = torch.zeros(5, 5, device=d0)
@@ -1497,7 +1496,6 @@ class TestCuda(TestCase):
         torch.cuda.synchronize()
 
     @unittest.skipIf(not TEST_MULTIGPU, "detected only one GPU")
-    @skipIfRocm
     def test_current_stream(self):
         d0 = torch.device('cuda:0')
         d1 = torch.device('cuda:1')
@@ -1526,7 +1524,6 @@ class TestCuda(TestCase):
             torch.cuda.current_stream(torch.device('cpu'))
 
     @unittest.skipIf(not TEST_MULTIGPU, "detected only one GPU")
-    @skipIfRocm
     def test_default_stream(self):
         d0 = torch.device('cuda:0')
         d1 = torch.device('cuda:1')
@@ -1575,7 +1572,6 @@ class TestCuda(TestCase):
         self.assertTrue(default_stream.query())
 
     @unittest.skipIf(not TEST_MULTIGPU, "detected only one GPU")
-    @skipIfRocm
     def test_stream_event_device(self):
         d0 = torch.device('cuda:0')
         d1 = torch.device('cuda:1')
@@ -1638,7 +1634,6 @@ class TestCuda(TestCase):
         self.assertEqual(0, torch.cuda.current_device())
 
     @unittest.skipIf(not TEST_MULTIGPU, "detected only one GPU")
-    @skipIfRocm
     def test_streams_multi_gpu(self):
         default_stream = torch.cuda.current_stream()
         self.assertEqual(default_stream.device, torch.device('cuda:0'))
@@ -1650,7 +1645,6 @@ class TestCuda(TestCase):
             self.assertNotEqual(torch.cuda.current_stream(), default_stream)
 
     @unittest.skipIf(not TEST_MULTIGPU, "detected only one GPU")
-    @skipIfRocm
     def test_streams_multi_gpu_query(self):
         d0 = torch.device('cuda:0')
         d1 = torch.device('cuda:1')
@@ -1741,7 +1735,6 @@ class TestCuda(TestCase):
             self.assertEqual(torch.cuda.FloatTensor(1, device=0).get_device(), 0)
             self.assertEqual(torch.cuda.FloatTensor(1, device=None).get_device(), 1)
 
-    @skipIfRocm
     def test_events(self):
         stream = torch.cuda.current_stream()
         event = torch.cuda.Event(enable_timing=True)
@@ -1859,7 +1852,6 @@ class TestCuda(TestCase):
             self.assertGreater(parent_time + child_time, total_time * 1.4)
 
     @unittest.skipIf(not TEST_MULTIGPU, "detected only one GPU")
-    @skipIfRocm
     def test_events_wait(self):
         d0 = torch.device('cuda:0')
         d1 = torch.device('cuda:1')
@@ -1965,7 +1957,6 @@ class TestCuda(TestCase):
         with torch.cuda.device(d1):
             self.assertGreater(e0.elapsed_time(e2), 0)
 
-    @skipIfRocm
     def test_record_stream(self):
         cycles_per_ms = get_cycles_per_ms()
 
@@ -2003,7 +1994,6 @@ class TestCuda(TestCase):
         x = torch.arange(0, 10).view((2, 5))
         self.assertEqual(x.t(), x.t().pin_memory())
 
-    @skipIfRocm
     def test_caching_pinned_memory(self):
         cycles_per_ms = get_cycles_per_ms()
 
@@ -2024,7 +2014,6 @@ class TestCuda(TestCase):
         self.assertEqual(list(gpu_tensor), [1])
 
     @unittest.skipIf(not TEST_MULTIGPU, "only one GPU detected")
-    @skipIfRocm
     def test_caching_pinned_memory_multi_gpu(self):
         # checks that the events preventing pinned memory from being re-used
         # too early are recorded on the correct GPU

diff --git a/test/test_distributions.py b/test/test_distributions.py
index 92840c0..62be589 100644 (file)
--- a/test/test_distributions.py
+++ b/test/test_distributions.py
@@ -31,7 +31,7 @@ from random import shuffle
 
 import torch
 from torch._six import inf
-from common_utils import TestCase, run_tests, set_rng_seed, TEST_WITH_UBSAN, load_tests, skipIfRocm
+from common_utils import TestCase, run_tests, set_rng_seed, TEST_WITH_UBSAN, load_tests
 from common_cuda import TEST_CUDA
 from torch.autograd import grad, gradcheck
 from torch.distributions import (Bernoulli, Beta, Binomial, Categorical,
@@ -1986,7 +1986,6 @@ class TestDistributions(TestCase):
 
     @unittest.skipIf(not TEST_CUDA, "CUDA not found")
     @unittest.skipIf(not TEST_NUMPY, "Numpy not found")
-    @skipIfRocm
     def test_gamma_gpu_sample(self):
         set_rng_seed(0)
         for alpha, beta in product([0.1, 1.0, 5.0], [0.1, 1.0, 10.0]):