skip tests

Signed-off-by: Tyler Michael Smith <[email protected]>

tests/kernels/test_semi_structured.py

@@ -8,6 +8,8 @@
 import torch
 
 from vllm import _custom_ops as ops
+from vllm.model_executor.layers.quantization.utils.w8a8_utils import (
+    sparse_cutlass_supported)
 from vllm.platforms import current_platform
 
 CUDA_DEVICES = [
@@ -102,10 +104,11 @@ def baseline_scaled_mm(a: torch.Tensor,
     return output
 
 
-@pytest.mark.skipif(not current_platform.has_device_capability(90),
+@pytest.mark.skipif(not sparse_cutlass_supported(),
                     reason="Sparse FP8 is not yet supported on this GPU type.")
 # Test working with a subset of A and B for sparse matmul
 def test_cutlass_sparse_subset():
+
     big_m = 1024
     m, n, k = 512, 512, 512
 

tests/quantization/test_compressed_tensors.py

@@ -14,6 +14,8 @@
     CompressedTensorsW4A16Sparse24, CompressedTensorsW8A8Fp8,
     CompressedTensorsW8A8Int8, CompressedTensorsW8A16Fp8,
     CompressedTensorsWNA16)
+from vllm.model_executor.layers.quantization.utils.w8a8_utils import (
+    sparse_cutlass_supported)
 from vllm.platforms import current_platform
 
 
@@ -212,7 +214,7 @@ def test_compressed_tensors_kv_cache(vllm_runner):
         assert output
 
 
-@pytest.mark.skipif(not current_platform.has_device_capability(90),
+@pytest.mark.skipif(not sparse_cutlass_supported(),
                     reason="Sparse FP8 is not yet supported on this GPU type.")
 def _test_2of4_quant_models(qkv_proj, weight_strategy, input_strategy):
     assert isinstance(qkv_proj.quant_method, CompressedTensorsLinearMethod)
@@ -254,7 +256,7 @@ def test_compressed_tensors_2of4_quant_fp8(vllm_runner, args_2of4):
         assert output
 
 
-@pytest.mark.skipif(not current_platform.has_device_capability(90),
+@pytest.mark.skipif(not sparse_cutlass_supported(),
                     reason="Sparse FP8 is not yet supported on this GPU type.")
 @pytest.mark.parametrize("args_2of4", [
     ("nm-testing/TinyLlama-1.1B-Chat-v1.0-INT8-Dynamic-IA-Per-Channel-Weight-testing",
@@ -279,7 +281,7 @@ def test_compressed_tensors_2of4_quant_int8(vllm_runner, args_2of4):
         assert output
 
 
-@pytest.mark.skipif(not current_platform.has_device_capability(90),
+@pytest.mark.skipif(not sparse_cutlass_supported(),
                     reason="Sparse FP8 is not yet supported on this GPU type.")
 @pytest.mark.parametrize(
     "args_2of4",

vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_24.py

@@ -9,27 +9,15 @@
 from vllm.model_executor.layers.quantization.compressed_tensors.schemes import (
     CompressedTensorsScheme)
 from vllm.model_executor.layers.quantization.utils.w8a8_utils import (
-    convert_to_channelwise)
+    convert_to_channelwise, sparse_cutlass_supported)
 from vllm.model_executor.parameter import (BasevLLMParameter,
                                            ChannelQuantScaleParameter,
                                            ModelWeightParameter,
                                            PerTensorScaleParameter)
-from vllm.platforms import current_platform
 
 __all__ = ["CompressedTensors24"]
 
 
-def sparse_cutlass_supported() -> bool:
-    # sparse cutlass is not supported on Rocm
-    if current_platform.is_rocm():
-        return False
-
-    capability_tuple = current_platform.get_device_capability()
-    capability = -1 if capability_tuple is None else capability_tuple.to_int()
-
-    return ops.cutlass_sparse_scaled_mm_supported(capability)
-
-
 class CompressedTensors24(CompressedTensorsScheme):
 
     def __init__(self,

vllm/model_executor/layers/quantization/utils/w8a8_utils.py

@@ -10,6 +10,17 @@
 TORCH_DEVICE_IDENTITY = torch.ones(1, dtype=torch.float32)
 
 
+def sparse_cutlass_supported() -> bool:
+    # sparse cutlass is not supported on Rocm
+    if current_platform.is_rocm():
+        return False
+
+    capability_tuple = current_platform.get_device_capability()
+    capability = -1 if capability_tuple is None else capability_tuple.to_int()
+
+    return ops.cutlass_sparse_scaled_mm_supported(capability)
+
+
 def cutlass_fp8_supported() -> bool:
     # cutlass is not supported on Rocm
     if current_platform.is_rocm():