Update qutlass cmake for stable abi (#47879)

Signed-off-by: Chris Leonard <chleonar@redhat.com>
This commit is contained in:
Chris Leonard
2026-07-20 18:31:10 -07:00
committed by GitHub
parent 0a684ab0c0
commit 97a98006b0
2 changed files with 11 additions and 9 deletions
+5 -5
View File
@@ -22,7 +22,7 @@ if(QUTLASS_SRC_DIR)
set(qutlass_BINARY_DIR "${CMAKE_BINARY_DIR}/qutlass-binary-dir-unused")
else()
set(_QUTLASS_UPSTREAM_REPO "https://github.com/IST-DASLab/qutlass.git")
set(_QUTLASS_UPSTREAM_TAG "830d2c4537c7396e14a02a46fbddd18b5d107c65")
set(_QUTLASS_UPSTREAM_TAG "e74319e3405ce6d71965732880f5dc1f52371f64")
set(_qutlass_fc_root "${FETCHCONTENT_BASE_DIR}")
if(NOT _qutlass_fc_root)
@@ -125,8 +125,6 @@ if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.8 AND QUTLASS_ARCHS)
CUDA_ARCHS "${QUTLASS_ARCHS}"
)
# QuTLASS uses legacy ATen headers and cannot be built with TORCH_TARGET_VERSION.
# Keep it as its own extension (registers torch.ops._qutlass_C).
define_extension_target(
_qutlass_C
DESTINATION vllm
@@ -139,9 +137,11 @@ if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.8 AND QUTLASS_ARCHS)
WITH_SOABI)
target_compile_definitions(_qutlass_C PRIVATE
QUTLASS_DISABLE_PYBIND=1
QUTLASS_MINIMAL_BUILD=1
TARGET_CUDA_ARCH=${QUTLASS_TARGET_CC}
CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1
TORCH_TARGET_VERSION=0x020B000000000000ULL
USE_CUDA)
set_property(SOURCE ${QUTLASS_SOURCES} APPEND PROPERTY COMPILE_OPTIONS
$<$<COMPILE_LANGUAGE:CUDA>:--expt-relaxed-constexpr --use_fast_math -O3>
+6 -4
View File
@@ -3863,10 +3863,10 @@ def fusedQuantizeMx(
raise ValueError(f"invalid method {method!r}, must be 'quest' or 'abs_max'")
if hasattr(torch.ops._qutlass_C, "fusedQuantizeNv"):
if hasattr(torch.ops._qutlass_C, "fusedQuantizeNvAbsMax"):
@register_fake("_qutlass_C::fusedQuantizeNv")
def _fake_fused_quantize_nv(
@register_fake("_qutlass_C::fusedQuantizeNvAbsMax")
def _fake_fused_quantize_nv_absmax(
a: torch.Tensor,
b: torch.Tensor,
xh_e2m1: torch.Tensor,
@@ -3892,7 +3892,9 @@ def fusedQuantizeNv(
padded_rows, padded_cols, dtype=torch.float8_e4m3fn, device=a.device
)
return torch.ops._qutlass_C.fusedQuantizeNv(a, b, xh_e2m1, xh_e4m3, global_scale)
return torch.ops._qutlass_C.fusedQuantizeNvAbsMax(
a, b, xh_e2m1, xh_e4m3, global_scale
)
def hadacore_transform(x: torch.Tensor, inplace: bool = True) -> torch.Tensor: