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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 14, 05:30 UTC

Fix: AWQ Marlin get_quant_method does not recognize "modules_to_not_convert" (#21888)

Signed-off-by: JunHowie <JunHowie@aliyun.com> Co-authored-by: JunHowie <JunHowie@aliyun.com> Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

Jun-Howie committed Aug 12, 2025 at 17:03 UTC 1ece7f30baa9d94ff57e13d851725acf657a9690
1 file changed +6 -2
vllm/model_executor/layers/quantization/awq_marlin.py
+6 -2
@@ -10,7 +10,8 @@ import vllm.model_executor.layers.fused_moe # noqa
10 from vllm import _custom_ops as ops
11 from vllm.logger import init_logger
12 from vllm.model_executor.layers.fused_moe.layer import (
13 - FusedMoE, FusedMoEMethodBase, FusedMoeWeightScaleSupported)
13 + FusedMoE, FusedMoEMethodBase, FusedMoeWeightScaleSupported,
14 + UnquantizedFusedMoEMethod)
15 from vllm.model_executor.layers.linear import (LinearBase, LinearMethodBase,
16 UnquantizedLinearMethod,
17 set_weight_attrs)
@@ -141,6 +142,9 @@ class AWQMarlinConfig(QuantizationConfig):
142 elif isinstance(layer, FusedMoE):
143 from vllm.model_executor.layers.quantization.moe_wna16 import (
144 MoeWNA16Config)
145 + if is_layer_skipped_awq(
146 + prefix, getattr(self, "modules_to_not_convert", [])):
147 + return UnquantizedFusedMoEMethod(layer.moe_config)
148 if not check_moe_marlin_supports_layer(layer, self.group_size):
149 logger.warning_once(
150 f"Layer '{prefix}' is not supported by AWQMoeMarlin. "
@@ -520,4 +524,4 @@ class AWQMoEMethod(FusedMoEMethodBase):
524 expert_map=expert_map,
525 w1_zeros=layer.w13_qzeros,
526 w2_zeros=layer.w2_qzeros,
523 - workspace=layer.workspace)
527 + workspace=layer.workspace)
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