[ROCm][Quant] Minimax-M3: Enable fp8_per_channel for bf16 weights on mi300x (#45854)

Signed-off-by: Hongxia Yang <hongxia.yang@amd.com>
Signed-off-by: tjtanaa <tunjian.tan@embeddedllm.com>
Co-authored-by: tjtanaa <tunjian.tan@embeddedllm.com>

vllm/model_executor/layers/fused_moe/config.py

@@ -603,6 +603,8 @@ def fp8_w8a8_moe_quant_config(
     a2_gscale: torch.Tensor | None = None,
     g1_alphas: torch.Tensor | None = None,
     g2_alphas: torch.Tensor | None = None,
+    gemm1_alpha: float | None = None,
+    gemm1_beta: float | None = None,
     gemm1_clamp_limit: float | None = None,
 ) -> FusedMoEQuantConfig:
     """
@@ -623,6 +625,8 @@ def fp8_w8a8_moe_quant_config(
         per_act_token_quant=per_act_token_quant,
         per_out_ch_quant=per_out_ch_quant,
         block_shape=block_shape,
+        gemm1_alpha=gemm1_alpha,
+        gemm1_beta=gemm1_beta,
         gemm1_clamp_limit=gemm1_clamp_limit,
     )
 

vllm/model_executor/layers/fused_moe/oracle/fp8.py

@@ -568,6 +568,8 @@ def make_fp8_moe_quant_config(
         block_shape=block_shape,
         per_act_token_quant=per_act_token_quant,
         per_out_ch_quant=per_out_ch_quant,
+        gemm1_alpha=gemm1_alpha,
+        gemm1_beta=gemm1_beta,
         gemm1_clamp_limit=swiglu_limit,
     )
 

vllm/model_executor/layers/quantization/fp8.py

@@ -787,6 +787,8 @@ class Fp8MoEMethod(FusedMoEMethodBase):
             a2_scale=a2_scale,
             block_shape=self.weight_block_size,
             swiglu_limit=getattr(layer, "swiglu_limit", None),
+            gemm1_alpha=getattr(layer, "swiglu_alpha", None),
+            gemm1_beta=getattr(layer, "swiglu_beta", None),
         )
 
         # Inject biases into the quant config if the model has them

vllm/model_executor/layers/quantization/online/fp8.py

@@ -483,6 +483,8 @@ class _Fp8OnlineMoEBase(OnlineMoEMethodBase):
             per_act_token_quant=self.per_act_token_quant,
             per_out_ch_quant=self.per_out_ch_quant,
             swiglu_limit=getattr(layer, "swiglu_limit", None),
+            gemm1_alpha=getattr(layer, "swiglu_alpha", None),
+            gemm1_beta=getattr(layer, "swiglu_beta", None),
         )
 
 

vllm/platforms/rocm.py

@@ -459,6 +459,7 @@ class RocmPlatform(Platform):
         "modelopt_mixed",
         "fp8_per_tensor",
         "fp8_per_block",
+        "fp8_per_channel",
         "online",
         "gpt_oss_mxfp4",
     ]