Skip failing tests for rowwise-scaled (#2022)

stack-info: PR: #2022, branch: drisspg/stack/46

Author: drisspg

test/test_ops_rowwise_scaled_linear_cutlass.py

@@ -16,6 +16,7 @@
     _int4_symm_cutlass_quant,
     _int8_symm_cutlass_quant,
 )
+from torchao.testing.utils import get_compute_capability
 
 DTYPES = [torch.float16, torch.bfloat16]
 BATCH_SIZE = [1, 4, 8, 16, 32, 64]
@@ -87,6 +88,7 @@ def run_test_for_op(op, dtype, batch_size, size_mnk, use_bias):
 
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA not available")
+@pytest.mark.skipif(get_compute_capability() != 8.0, reason="Only supported on A100")
 @pytest.mark.parametrize("dtype, batch_size, size_mnk, use_bias", TEST_PARAMS)
 def test_rowwise_scaled_linear_cutlass_s4s4(dtype, batch_size, size_mnk, use_bias):
     run_test_for_op(
@@ -99,6 +101,7 @@ def test_rowwise_scaled_linear_cutlass_s4s4(dtype, batch_size, size_mnk, use_bia
 
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA not available")
+@pytest.mark.skipif(get_compute_capability() != 8.0, reason="Only supported on A100")
 @pytest.mark.parametrize("dtype, batch_size, size_mnk, use_bias", TEST_PARAMS)
 def test_rowwise_scaled_linear_cutlass_s8s4(dtype, batch_size, size_mnk, use_bias):
     run_test_for_op(