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replace onlyOnCPUAndCUDA with onlyNativeDeviceTypes (#65201)
Summary: Reference https://github.com/pytorch/pytorch/issues/53849 Replace `onlyOnCPUandCUDA` with `onlyNativeDeviceTypes` which includes `cpu, cuda and meta`. Pull Request resolved: https://github.com/pytorch/pytorch/pull/65201 Reviewed By: mrshenli Differential Revision: D31299718 Pulled By: mruberry fbshipit-source-id: 2d8356450c035d6a314209ab51b2c237583920fd
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@ -12,7 +12,7 @@ from torch.testing import make_tensor
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from torch.testing._internal.common_utils import \
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(TestCase, run_tests, suppress_warnings)
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from torch.testing._internal.common_device_type import \
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(instantiate_device_type_tests, onlyCPU, dtypes, onlyOnCPUAndCUDA)
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(instantiate_device_type_tests, onlyCPU, dtypes, onlyNativeDeviceTypes)
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from torch.testing._internal.common_dtype import (
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get_all_dtypes, get_all_int_dtypes, get_all_fp_dtypes, get_all_complex_dtypes
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)
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@ -125,7 +125,7 @@ class TestViewOps(TestCase):
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s = t.conj()
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self.assertTrue(s is t)
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*get_all_fp_dtypes(include_bfloat16=False), torch.complex64)
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def test_view_dtype(self, device, dtype):
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int_dtype = {
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@ -175,7 +175,7 @@ class TestViewOps(TestCase):
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self.assertFalse(t.view(torch.complex64).requires_grad)
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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def test_view_as_complex(self, device):
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def fn(contiguous_input=True, dim0=0, dim1=1):
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t = torch.randn(3, 2, 2, device=device)
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@ -231,7 +231,7 @@ class TestViewOps(TestCase):
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self.assertTrue(self.is_view_of(x, res))
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self.assertEqual(res.shape, torch.Size([0]))
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*get_all_complex_dtypes(include_complex32=True))
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def test_view_as_real(self, device, dtype):
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def fn(contiguous_input=True):
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@ -269,7 +269,7 @@ class TestViewOps(TestCase):
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self.assertRaises(RuntimeError, lambda: self.is_view_of(x, res))
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self.assertEqual(res.shape, torch.Size([2]))
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*get_all_dtypes())
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def test_view_tensor_split(self, device, dtype):
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a = make_tensor((40, 30), device, dtype, low=-9, high=9)
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@ -280,7 +280,7 @@ class TestViewOps(TestCase):
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for a_split_dim1_tensor in a_split_dim1:
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self.assertTrue(self.is_view_of(a, a_split_dim1_tensor))
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*get_all_dtypes())
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def test_view_tensor_hsplit(self, device, dtype):
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t = make_tensor((4, 4, 4), device, dtype, low=-9, high=9)
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@ -290,7 +290,7 @@ class TestViewOps(TestCase):
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t[2, 2, 2] = 7
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self.assertEqual(t_hsplit[1][2, 0, 2], t[2, 2, 2])
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*get_all_dtypes())
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def test_view_tensor_vsplit(self, device, dtype):
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t = make_tensor((4, 4, 4), device, dtype, low=-9, high=9)
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@ -300,7 +300,7 @@ class TestViewOps(TestCase):
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t[2, 2, 2] = 7
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self.assertEqual(t_vsplit[1][0, 2, 2], t[2, 2, 2])
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*get_all_dtypes())
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def test_view_tensor_dsplit(self, device, dtype):
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t = make_tensor((4, 4, 4), device, dtype, low=-9, high=9)
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@ -310,7 +310,7 @@ class TestViewOps(TestCase):
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t[2, 2, 2] = 7
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self.assertEqual(t_dsplit[1][2, 2, 0], t[2, 2, 2])
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
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def test_real_imag_noncomplex(self, device, dtype):
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t = torch.ones((5, 5), dtype=dtype, device=device)
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@ -321,7 +321,7 @@ class TestViewOps(TestCase):
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with self.assertRaises(RuntimeError):
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torch.imag(t)
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*get_all_complex_dtypes())
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def test_real_imag_view(self, device, dtype):
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def compare_with_numpy(contiguous_input=True):
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@ -352,7 +352,7 @@ class TestViewOps(TestCase):
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self.assertEqual(a[5:].real, a.real[5:])
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self.assertEqual(a[5:].imag, a.imag[5:])
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*get_all_complex_dtypes())
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def test_conj_imag_view(self, device, dtype) -> None:
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t = _make_tensor((4, 5,), dtype, device)
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@ -367,7 +367,7 @@ class TestViewOps(TestCase):
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self.assertEqual(v_imag, t_numpy_conj.imag)
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self.assertTrue(v_imag.is_neg())
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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def test_conj_view_with_shared_memory(self, device) -> None:
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a = _make_tensor((4, 5,), torch.cfloat, device)
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b = a.conj()
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@ -377,7 +377,7 @@ class TestViewOps(TestCase):
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self.assertEqual(torch.add(b, c), torch.add(b, c, out=a))
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self.assertEqual(torch.add(b, c), b.add_(c))
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(*product(get_all_complex_dtypes(), get_all_dtypes()))
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@suppress_warnings
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def test_set_real_imag(self, device, dtypes):
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@ -666,7 +666,7 @@ class TestViewOps(TestCase):
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test_writes_propagate(t, v3)
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self.assertTrue(self.is_view_of_same_base(t, v3))
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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def test_flatten_nonview(self, device):
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def assert_is_nonview(t, nv):
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idx_t = (0,) * t.ndim
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@ -885,7 +885,7 @@ class TestOldViewOps(TestCase):
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self.assertEqual((1, 0, 6, 1, 1), x.view(1, 0, 6, 1, 1).shape)
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# TODO: this should be refactored into the view ops test suite
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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def test_reshape(self, device):
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x = torch.randn(3, 3, device=device)
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self.assertEqual(x.data_ptr(), x.reshape(-1).data_ptr())
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@ -1183,7 +1183,7 @@ class TestOldViewOps(TestCase):
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test_helper((10, 3, 32, 32), 10 * 3 * 32 * 32, torch.channels_last, device)
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test_helper((3, 10, 3, 32, 32), 3 * 10 * 3 * 32 * 32, torch.channels_last_3d, device)
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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@dtypes(torch.int64, torch.float, torch.complex128)
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def test_transpose_invalid(self, device, dtype):
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for fn in (torch.swapdims, torch.swapaxes, torch.transpose):
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@ -1424,7 +1424,7 @@ class TestOldViewOps(TestCase):
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x.set_(x.storage(), 0, x.size(), stride)
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self.assertTrue(x.is_contiguous())
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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# Skip BFloat16 since numpy does not support it
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@dtypes(*get_all_dtypes(include_bfloat16=False))
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def test_tensor_split_sections(self, device, dtype):
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@ -1455,7 +1455,7 @@ class TestOldViewOps(TestCase):
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self.assertEqual(result_n, result1, msg=msg)
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self.assertEqual(result_n, result2, msg=msg)
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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# Skip BFloat16 since numpy does not support it
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@dtypes(*get_all_dtypes(include_bfloat16=False))
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def test_tensor_split_indices(self, device, dtype):
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@ -1500,7 +1500,7 @@ class TestOldViewOps(TestCase):
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self.assertEqual(result_n, result_1, msg=msg)
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self.assertEqual(result_n, result_2, msg=msg)
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@onlyOnCPUAndCUDA
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@onlyNativeDeviceTypes
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def test_tensor_split_errors(self, device):
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S = 10
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test_cases = [
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