FIX MOE issue in AutoRound format (#18586)

Signed-off-by: wenhuach21 <wenhua.cheng@intel.com>

README.md

@@ -58,7 +58,7 @@ vLLM is fast with:
 - Efficient management of attention key and value memory with [**PagedAttention**](https://blog.vllm.ai/2023/06/20/vllm.html)
 - Continuous batching of incoming requests
 - Fast model execution with CUDA/HIP graph
-- Quantizations: [GPTQ](https://arxiv.org/abs/2210.17323), [AWQ](https://arxiv.org/abs/2306.00978), INT4, INT8, and FP8.
+- Quantizations: [GPTQ](https://arxiv.org/abs/2210.17323), [AWQ](https://arxiv.org/abs/2306.00978), [AutoRound](https://arxiv.org/abs/2309.05516),INT4, INT8, and FP8.
 - Optimized CUDA kernels, including integration with FlashAttention and FlashInfer.
 - Speculative decoding
 - Chunked prefill

vllm/model_executor/layers/quantization/auto_round.py

@@ -8,6 +8,7 @@ import torch
 from vllm.logger import init_logger
 from vllm.model_executor.layers.linear import (LinearBase,
                                                UnquantizedLinearMethod)
+from vllm.model_executor.layers.quantization import QuantizationMethods
 from vllm.model_executor.layers.quantization.base_config import (
     QuantizationConfig)
 from vllm.model_executor.layers.vocab_parallel_embedding import ParallelLMHead
@@ -74,7 +75,7 @@ class AutoRoundConfig(QuantizationConfig):
                 f"group_size={self.group_size}, sym={self.sym})")
 
     @classmethod
-    def get_name(cls):  ## use str will trigger preci issue
+    def get_name(cls) -> QuantizationMethods:
         return "auto-round"
 
     @classmethod
@@ -142,18 +143,18 @@ class AutoRoundConfig(QuantizationConfig):
                      prefix, layer.__class__.__name__, weight_bits, group_size,
                      sym)
         if backend == "auto" or "marlin" in backend:
-            if isinstance(layer, FusedMoE):
-                use_marlin = check_moe_marlin_supports_layer(layer, group_size)
-            else:
-
             AWQ_TYPE_MAP = {
                 4: scalar_types.uint4,
                 8: scalar_types.uint8,
             }
-                use_marlin = ((weight_bits, sym) in AWQ_TYPE_MAP
-                              and check_marlin_supported(
-                                  AWQ_TYPE_MAP[(weight_bits)], group_size,
-                                  not sym))
+            use_marlin = (weight_bits
+                          in AWQ_TYPE_MAP) and check_marlin_supported(
+                              AWQ_TYPE_MAP[weight_bits], group_size, not sym)
+
+            if isinstance(layer, FusedMoE):
+                use_marlin = use_marlin and check_moe_marlin_supports_layer(
+                    layer, group_size)
+
         else:
             use_marlin = False
         if use_marlin:
@@ -180,10 +181,11 @@ class AutoRoundConfig(QuantizationConfig):
             from vllm.model_executor.layers.quantization.moe_wna16 import (
                 MoeWNA16Config)
             config = {
-                "linear_quant_method": "awq",
-                "weight_bits": weight_bits,
+                "quant_method": "awq",
+                "bits": weight_bits,
                 "group_size": group_size,
                 "zero_point": not sym,
+                "lm_head": False,
             }
             return MoeWNA16Config.from_config(config).get_quant_method(
                 layer, prefix)
@@ -213,9 +215,6 @@ class AutoRoundConfig(QuantizationConfig):
                      prefix, layer.__class__.__name__, weight_bits, group_size,
                      sym)
         if backend == "auto" or "marlin" in backend:
-            if isinstance(layer, FusedMoE):
-                use_marlin = check_moe_marlin_supports_layer(layer, group_size)
-            else:
             GPTQ_TYPE_MAP = {
                 (4, True): scalar_types.uint4b8,
                 (8, True): scalar_types.uint8b128,
@@ -225,6 +224,9 @@ class AutoRoundConfig(QuantizationConfig):
                               GPTQ_TYPE_MAP[(weight_bits, sym)],
                               group_size,
                               has_zp=not sym))
+            if isinstance(layer, FusedMoE):
+                use_marlin = use_marlin and check_moe_marlin_supports_layer(
+                    layer, group_size)
         else:
             use_marlin = False
         if use_marlin:
@@ -251,11 +253,11 @@ class AutoRoundConfig(QuantizationConfig):
                 from vllm.model_executor.layers.quantization.moe_wna16 import (
                     MoeWNA16Config)
                 config = {
-                    "linear_quant_method": "gptq",
-                    "weight_bits": weight_bits,
+                    "quant_method": "gptq",
+                    "bits": weight_bits,
                     "group_size": group_size,
                     "sym": sym,
-                    "lm_head_quantized": False,
+                    "lm_head": False,
                 }
                 return MoeWNA16Config.from_config(config).get_quant_method(
                     layer, prefix)