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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 11, 22:30 UTC

[CI/Build][AMD][Quantization] Fix test_int8_kernel.py by updating int8_utils to use hip.libdevice.round (#30151)

Signed-off-by: Randall Smith <ransmith@amd.com> Co-authored-by: Randall Smith <ransmith@amd.com>

rasmith committed Dec 5, 2025 at 22:52 UTC dc839ad03d31104c8ebcb0b8f5a75021f1796760
1 file changed +2 -17
vllm/model_executor/layers/quantization/utils/int8_utils.py
+2 -17
@@ -83,26 +83,11 @@ def block_dequant(
83
84
85 if current_platform.is_rocm():
86 - from triton.language import core
87 -
88 - # NOTE: This can be removed when hip.libdevice.round() is available.
89 - @core.extern
90 - def round_f32(arg0, _builder=None):
91 - return core.extern_elementwise(
92 - "",
93 - "",
94 - [arg0],
95 - {
96 - (core.dtype("fp32"),): ("llvm.round", core.dtype("fp32")),
97 - (core.dtype("fp64"),): ("llvm.round", core.dtype("fp64")),
98 - },
99 - is_pure=True,
100 - _builder=_builder,
101 - )
86
87 @triton.jit
88 def round_int8(x):
105 - return round_f32(x).to(tl.int8)
89 + return tl.extra.hip.libdevice.round(x).to(tl.int8)
90 +
91 else:
92
93 @triton.jit