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[ROCm] enable tests test_sampled_addmm_autograd_cuda_*, test_sample… (#117501)

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These tests PASS on ROCM 5.6+ now:

- test_sampled_addmm_autograd_cuda_complex128
- test_sampled_addmm_autograd_cuda_complex64
- test_sampled_addmm_autograd_cuda_float32
- test_sampled_addmm_autograd_cuda_float64
- test_sampled_addmm_cuda_complex128
- test_sampled_addmm_cuda_complex64
- test_sampled_addmm_cuda_float32
- test_sampled_addmm_cuda_float64
- test_autograd_dense_output_addmm_cuda_float64
- test_autograd_dense_output_addmv_cuda_float64
- test_autograd_dense_output_mv_cuda_float64

@pruthvistony @jithunnair-amd

Pull Request resolved: https://github.com/pytorch/pytorch/pull/117501
Approved by: https://github.com/pruthvistony, https://github.com/jeffdaily, https://github.com/malfet
This commit is contained in:
Dmitry Nikolaev
2024-02-22 17:24:23 +00:00
committed by PyTorch MergeBot
parent 1c1028ac49
commit c7328602ed
1 changed files with 3 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files

11
test/test_sparse_csr.py
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@ -46,6 +46,8 @@ def _check_cusparse_spgemm_available():
return not TEST_WITH_ROCM
def _check_cusparse_sddmm_available():
if TEST_WITH_ROCM:
return True
version = _get_torch_cuda_version()
# cusparseSDDMM was added in 11.2.1 but we don't have access to patch version
min_supported_version = (11, 3)
@ -2381,7 +2383,6 @@ class TestSparseCSR(TestCase):
itertools.product([True, False], repeat=4)):
run_test(n, k, upper, unitriangular, transpose, zero)
@skipCUDAIfRocm
@skipCUDAIf(
not _check_cusparse_sddmm_available(),
"cuSparse Generic API SDDMM is not available"
@ -2436,7 +2437,6 @@ class TestSparseCSR(TestCase):
for op_a, op_b in itertools.product([True, False], repeat=2):
run_test(c, a, b, op_a, op_b)
@skipCUDAIfRocm
@skipCUDAIf(
not _check_cusparse_sddmm_available(),
"cuSparse Generic API SDDMM is not available"
@ -2490,7 +2490,7 @@ class TestSparseCSR(TestCase):
@onlyCUDA
@skipCUDAIf(
not (TEST_WITH_ROCM or _check_cusparse_sddmm_available()),
not _check_cusparse_sddmm_available(),
"cuSparse Generic API SDDMM is not available"
)
@dtypes(torch.float32, torch.float64, torch.complex64, torch.complex128)
@ -2772,7 +2772,6 @@ class TestSparseCSR(TestCase):
dense_output.backward(dense_covector)
self.assertEqual(sparse_input.grad, dense_input.grad)
@skipCUDAIfRocm
@skipCUDAIf(
not _check_cusparse_sddmm_available(),
"cuSparse Generic API SDDMM is not available"
@ -2848,7 +2847,6 @@ class TestSparseCSR(TestCase):
else:
self.assertEqual(a.grad, dense_a.grad)
@skipCUDAIfRocm
@skipCPUIfNoMklSparse
@dtypes(torch.float64)
def test_autograd_dense_output_addmv(self, device, dtype):
@ -2883,9 +2881,6 @@ class TestSparseCSR(TestCase):
def test_autograd_dense_output(self, device, dtype, op):
if op.name == "mv" and no_mkl_sparse and self.device_type == 'cpu':
self.skipTest("MKL Sparse is not available")
if op.name == "mv" and TEST_WITH_ROCM and self.device_type == 'cuda':
# mv currently work only on CUDA
self.skipTest("ROCm is not supported")
samples = list(op.sample_inputs(device, dtype, requires_grad=True))