[Kernel] CUTLASS grouped gemm fp8 MoE kernel (#13972)

Signed-off-by: ElizaWszola <eliza@neuralmagic.com>
Signed-off-by: ElizaWszola <ewszola@redhat.com>
Co-authored-by: Lucas Wilkinson <wilkinson.lucas@gmail.com>

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

@@ -50,6 +50,16 @@ def cutlass_block_fp8_supported() -> bool:
     return ops.cutlass_scaled_mm_supports_block_fp8(capability)
 
 
+def cutlass_group_gemm_supported() -> bool:
+    if not current_platform.is_cuda():
+        return False
+
+    capability_tuple = current_platform.get_device_capability()
+    capability = -1 if capability_tuple is None else capability_tuple.to_int()
+
+    return ops.cutlass_group_gemm_supported(capability)
+
+
 CUTLASS_FP8_SUPPORTED = cutlass_fp8_supported()
 CUTLASS_BLOCK_FP8_SUPPORTED = cutlass_block_fp8_supported()
 

vllm/utils.py

@@ -1568,18 +1568,21 @@ class ClassRegistry(UserDict[Type[T], _V]):
         return any(cls in self.data for cls in key.mro())
 
 
-def weak_ref_tensor(tensor: torch.Tensor) -> torch.Tensor:
+def weak_ref_tensor(tensor: Any) -> Any:
     """
     Create a weak reference to a tensor.
     The new tensor will share the same data as the original tensor,
     but will not keep the original tensor alive.
     """
-    return torch.ops._C.weak_ref_tensor(tensor)
+    if isinstance(tensor, torch.Tensor):
+        return torch.ops._C.weak_ref_tensor(tensor)
+    else:
+        return tensor
 
 
 def weak_ref_tensors(
     tensors: Union[torch.Tensor, list[torch.Tensor], tuple[torch.Tensor]]
-) -> Union[torch.Tensor, list[torch.Tensor], tuple[torch.Tensor]]:
+) -> Union[torch.Tensor, list[Any], tuple[Any], Any]:
     """
     Convenience function to create weak references to tensors,
     for single tensor, list of tensors or tuple of tensors.