[Bugfix] [AITER] [ROCm] Fix Quark MoE Quant Config and AITER Fused MoE quant type logic (#27029)

Signed-off-by: vllmellm <vllm.ellm@embeddedllm.com>

vllm/model_executor/layers/fused_moe/rocm_aiter_fused_moe.py

@@ -492,6 +492,8 @@ def rocm_aiter_fused_experts(
             assert quant_config.w1_scale is not None
             assert quant_config.w2_scale is not None
             quant_method = QuantMethod.BLOCK_128x128.value
+        elif quant_config.use_fp8_w8a8 and quant_config.per_out_ch_quant:
+            quant_method = QuantMethod.PER_TOKEN.value
         elif quant_config.use_fp8_w8a8:
             # Currently only per tensor quantization method is enabled.
             quant_method = QuantMethod.PER_TENSOR.value

vllm/model_executor/layers/quantization/quark/quark_moe.py

@@ -342,7 +342,8 @@ class QuarkW8A8Fp8MoEMethod(QuarkMoEMethod):
             w2_scale=layer.w2_weight_scale,
             a1_scale=layer.w13_input_scale,
             a2_scale=layer.w2_input_scale,
-            per_act_token_quant=self.weight_qscheme == "per_channel",
+            per_act_token_quant=self.input_qscheme == "per_channel",
+            per_out_ch_quant=self.weight_qscheme == "per_channel",
         )
 
     def apply(

vllm/model_executor/layers/quantization/utils/w8a8_utils.py

@@ -464,8 +464,16 @@ class Fp8LinearOp:
         else:
             qinput, x_scale = input_2d, input_scale
 
-        per_tensor_weights = weight_scale.numel() == 1
-        per_tensor_activations = x_scale.numel() == 1
+        # Must have dim() conditions
+        # In per-token quant scenario, when the number of token is 1,
+        # the scale will only have 1 elements.
+        # Without checking the dim(),
+        # we cannot distingushes between per-tensor and per-token quant.
+        # Example:
+        # When the number of token is 1, per-token scale is [[1]]
+        # When per-tensor scale is [1] or ().
+        per_tensor_weights = (weight_scale.numel() == 1) and weight_scale.dim() < 2
+        per_tensor_activations = (x_scale.numel() == 1) and x_scale.dim() < 2
 
         # TODO(luka) do this dispatch during init (after ScaledMM refactor)
         w8a8_scaled_mm_func = dispatch_w8a8_scaled_mm(