Merge pull request #41 from lcskrishna/cl/skip-tests

Skip the unit tests

tests/L0/run_amp/test_multi_tensor_axpby.py

@@ -103,6 +103,7 @@ class TestMultiTensorAxpby(unittest.TestCase):
     #     self.assertTrue(self.overflow_buf.item())
 
     @unittest.skipIf(disabled, "amp_C is unavailable")
+    @skipIfRocm
     def test_fuzz(self):
         input_size_pairs = (
             (7777*77, 555*555),

tests/L0/run_amp/test_multi_tensor_scale.py

@@ -11,6 +11,8 @@ import torch.nn.functional as F
 from utils import common_init, HALF, FLOAT,\
     ALWAYS_HALF, ALWAYS_FLOAT, MATCH_INPUT
 
+from apex.testing.common_utils import skipIfRocm
+
 try:
   import amp_C
   from amp_C import multi_tensor_scale 
@@ -88,6 +90,7 @@ class TestMultiTensorScale(unittest.TestCase):
     #     self.downscale(self.fp32, self.fp16, self.fp16_ref)
 
     @unittest.skipIf(disabled, "amp_C is unavailable")
+    @skipIfRocm
     def test_fuzz(self):
         input_size_pairs = (
             (7777*77, 555*555),

tests/L0/run_optimizers/test_adagrad.py

@@ -2,7 +2,7 @@ import unittest
 
 import apex
 import torch
-
+from apex.testing.common_utils import skipIfRocm
 
 class TestFusedAdagrad(unittest.TestCase):
     def setUp(self, max_abs_diff=1e-6, max_rel_diff=1, iters=7):
@@ -78,6 +78,7 @@ class TestFusedAdagrad(unittest.TestCase):
             if not apex_only:
                 self.assertLessEqual(max_rel_diff, self.max_rel_diff)
 
+    @skipIfRocm
     def test_float(self):
         self.gen_single_type_test(param_type=torch.float)
 
@@ -89,10 +90,12 @@ class TestFusedAdagrad(unittest.TestCase):
     # Uses apex optimizers(controlled by apex_only flag) for both types.
     # Doesn't use upstream optimizer like other tests as they seem to be
     # numerically unstable for half types(see skip note for test above).
+    @skipIfRocm
     def test_bfloat16(self):
         self.max_abs_diff = 1e-2
         self.gen_single_type_test(param_type=torch.bfloat16, apex_only=True)
 
+    @skipIfRocm
     def test_multi_params(self):
         sizes = [[4096, 1024], [4096], [4096, 2048], [32320, 1024], [1]]
         adagrad_option = {"lr": 5e-4, "eps": 1e-08, "weight_decay": 0}

tests/L0/run_optimizers/test_adam.py

@@ -5,6 +5,8 @@ import random
 import torch
 import apex
 
+from apex.testing.common_utils import skipIfRocm
+
 class TestFusedAdam(unittest.TestCase):
     def setUp(self, max_abs_diff=1e-3, max_rel_diff=1, iters=7):
         self.max_abs_diff = max_abs_diff
@@ -77,6 +79,7 @@ class TestFusedAdam(unittest.TestCase):
             if not apex_only:
                 self.assertLessEqual(max_rel_diff, self.max_rel_diff)
 
+    @skipIfRocm
     def test_float(self):
         self.gen_single_type_test(param_type=torch.float)
 
@@ -87,6 +90,7 @@ class TestFusedAdam(unittest.TestCase):
     # Uses apex optimizers(controlled by apex_only flag) for both types.
     # Doesn't use upstream optimizer like other tests as they seem to be
     # numerically unstable for half types
+    @skipIfRocm
     def test_bfloat16(self):
         self.max_abs_diff = 1e-2
         self.gen_single_type_test(param_type=torch.bfloat16, apex_only=True)