diff --git a/test/test_tensor_creation_ops.py b/test/test_tensor_creation_ops.py
index b355005b1c69..9be3e6db5bf0 100644
--- a/test/test_tensor_creation_ops.py
+++ b/test/test_tensor_creation_ops.py
@@ -14,7 +14,7 @@
     IS_WINDOWS)
 from torch.testing._internal.common_device_type import (
     instantiate_device_type_tests, deviceCountAtLeast, onlyOnCPUAndCUDA,
-    onlyCPU, skipCUDAIfNotRocm, largeTensorTest, precisionOverride, dtypes,
+    onlyCPU, largeTensorTest, precisionOverride, dtypes,
     onlyCUDA, skipCPUIf, dtypesIfCUDA, dtypesIfCPU)
 
 # TODO: refactor tri_tests_args, _compare_trilu_indices, run_additional_tri_tests
@@ -2581,7 +2581,6 @@ def test_arange_device_vs_cpu(self, device, dtype):
         self.assertEqual(cpu_tensor, device_tensor)
 
     @onlyCUDA
-    @skipCUDAIfNotRocm
     def test_arange_bfloat16(self, device):
         ref_tensor = torch.tensor([0, 1, 2, 3], dtype=torch.bfloat16, device=device)
         bfloat16_tensor = torch.arange(0, 4, dtype=torch.bfloat16, device=device)
diff --git a/test/test_torch.py b/test/test_torch.py
index 2d181c3b9400..ad88128617c9 100644
--- a/test/test_torch.py
+++ b/test/test_torch.py
@@ -6316,10 +6316,6 @@ def test_copy_broadcast(self, device) -> None:
     torch.uint8
 ]
 
-# _types2 adds bfloat16 type to  _types only on ROCm. Should eventually be unified
-# with _types when bfloat16 bringup is complete on all platforms.
-_types2 = _types + [torch.bfloat16] if TEST_WITH_ROCM else _types
-
 _float_types = [torch.half, torch.float, torch.double]
 
 _complex_types = [torch.cfloat, torch.cdouble]
@@ -6601,10 +6597,14 @@ def inner(self, device, dtype):
     ('dot', '', _medium_1d, lambda t, d: [_medium_1d(t, d)],
         1e-2, 1e-5, 1e-5, _float_types + _complex_types, _cpu_types, False),
     ('element_size', '', _medium_1d, lambda t, d: [], 1e-5, 1e-5, 1e-5, _float_types_no_half, _cpu_types, False),
-    ('eq', '', _small_3d_ones, lambda t, d: [_small_3d(t, d)], 1e-5, 1e-5, 1e-5, _types2),
-    ('eq', 'equal', _small_3d_ones, lambda t, d: [_small_3d_ones(t, d)], 1e-5, 1e-5, 1e-5, _types2),
-    ('ne', '', _small_3d_ones, lambda t, d: [_small_3d(t, d)], 1e-5, 1e-5, 1e-5, _types2),
-    ('ne', 'equal', _small_3d_ones, lambda t, d: [_small_3d_ones(t, d)], 1e-5, 1e-5, 1e-5, _types2),
+    ('eq', '', _small_3d_ones, lambda t, d: [_small_3d(t, d)], 1e-5, 1e-5, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False)),
+    ('eq', 'equal', _small_3d_ones, lambda t, d: [_small_3d_ones(t, d)], 1e-5, 1e-5, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False)),
+    ('ne', '', _small_3d_ones, lambda t, d: [_small_3d(t, d)], 1e-5, 1e-5, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False)),
+    ('ne', 'equal', _small_3d_ones, lambda t, d: [_small_3d_ones(t, d)], 1e-5, 1e-5, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False)),
     ('equal', 'equal', _small_3d_ones, lambda t, d: [_small_3d_ones(t, d)],
         1e-5, 1e-5, 1e-5, _types, _cpu_types, False),
     ('equal', '', _small_3d_ones, lambda t, d: [_small_3d(t, d)], 1e-5, 1e-5, 1e-5, _types, _cpu_types, False),
@@ -6618,10 +6618,14 @@ def inner(self, device, dtype):
     ('lcm', '', _small_3d, lambda t, d: [_small_3d(t, d)], 0, 0, 0,
      [torch.int16, torch.int32, torch.int64],
      [torch.int16, torch.int32, torch.int64], True, [onlyOnCPUAndCUDA]),
-    ('ge', '', _medium_2d, lambda t, d: [_medium_2d(t, d)], 1e-5, 1e-5, 1e-5, _types2),
-    ('le', '', _medium_2d, lambda t, d: [_medium_2d(t, d)], 1e-5, 1e-5, 1e-5, _types2),
-    ('gt', '', _medium_2d, lambda t, d: [_medium_2d(t, d)], 1e-5, 1e-5, 1e-5, _types2),
-    ('lt', '', _medium_2d, lambda t, d: [_medium_2d(t, d)], 1e-5, 1e-5, 1e-5, _types2),
+    ('ge', '', _medium_2d, lambda t, d: [_medium_2d(t, d)], 1e-5, 1e-5, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False)),
+    ('le', '', _medium_2d, lambda t, d: [_medium_2d(t, d)], 1e-5, 1e-5, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False)),
+    ('gt', '', _medium_2d, lambda t, d: [_medium_2d(t, d)], 1e-5, 1e-5, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False)),
+    ('lt', '', _medium_2d, lambda t, d: [_medium_2d(t, d)], 1e-5, 1e-5, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False)),
     ('is_contiguous', '', _medium_2d, lambda t, d: [], 1e-5, 1e-5, 1e-5, _types, _cpu_types, False),
     # TODO: can't check negative case - cross-device copy is contiguous
     ('is_same_size', 'negative', _medium_2d, lambda t, d: [_small_3d(t, d)],
@@ -6705,12 +6709,16 @@ def inner(self, device, dtype):
                       torch.LongTensor([[1], [2]]).to(dtype=_convert_t(t, d), device=d),
                       True],
         1e-5, 1e-5, 1e-5, _types, _cpu_types, False),
-    ('prod', '', lambda t, d: _small_2d(t, d, oneish=True),
-        lambda t, d: [], 1e-2, 1e-1, 1e-5, _types2, _cpu_types, False),
-    ('prod', 'dim', _small_3d, lambda t, d: [1], 1e-3, 1e-1, 1e-5, _types2, _cpu_types, False),
-    ('prod', 'neg_dim', _small_3d, lambda t, d: [-1], 1e-3, 1e-1, 1e-5, _types2, _cpu_types, False),
-    ('sum', '', _small_2d, lambda t, d: [], 1e-2, 1e-2, 1e-5, _types2, _cpu_types, False),
-    ('sum', 'dim', _small_3d, lambda t, d: [1], 1e-2, 1e-2, 1e-5, _types2, _cpu_types, False),
+    ('prod', '', lambda t, d: _small_2d(t, d, oneish=True), lambda t, d: [], 1e-2, 1e-1, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False), _cpu_types, False),
+    ('prod', 'dim', _small_3d, lambda t, d: [1], 1e-3, 1e-1, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False), _cpu_types, False),
+    ('prod', 'neg_dim', _small_3d, lambda t, d: [-1], 1e-3, 1e-1, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False), _cpu_types, False),
+    ('sum', '', _small_2d, lambda t, d: [], 1e-2, 1e-2, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False), _cpu_types, False),
+    ('sum', 'dim', _small_3d, lambda t, d: [1], 1e-2, 1e-2, 1e-5,
+        torch.testing.get_all_dtypes(include_complex=False, include_bool=False), _cpu_types, False),
     ('sum', 'neg_dim', _small_3d, lambda t, d: [-1], 1e-2, 1e-5, 1e-5, _types, _cpu_types, False),
     ('sum', 'complex', _small_2d, lambda t, d: [], 1e-2, 1e-2, 1e-5, _complex_types, _cpu_types, False),
     ('sum', 'complex_dim', _small_3d, lambda t, d: [1], 1e-2, 1e-2, 1e-5, _complex_types, _cpu_types, False),