[fix]fix tests of kernels

vllm/model_executor/layers/fused_moe/config.py

@@ -50,6 +50,7 @@ def get_config_quant_dtype(
     use_int8_w8a8: bool,
     use_int8_w8a16: bool,
     use_int4_w4a16: bool,
+    use_int4_w4a8: bool,
     use_mxfp4_w4a4: bool,
 ) -> Union[None, torch.dtype, str]:
     if use_fp8_w8a8:
@@ -130,6 +131,7 @@ class FusedMoEQuantConfig:
         use_int8_w8a8: bool = False,
         use_int8_w8a16: bool = False,
         use_int4_w4a16: bool = False,
+        use_int4_w4a8: bool = False,
         use_mxfp4_w4a4: bool = False,
         per_act_token_quant: bool = False,
         per_out_ch_quant: bool = False,
@@ -141,6 +143,7 @@ class FusedMoEQuantConfig:
                 use_int8_w8a8,
                 use_int8_w8a16,
                 use_int4_w4a16,
+                use_int4_w4a8,
                 use_mxfp4_w4a4,
             ]
         ]) <= 1, "Quantization flags are mutually exclusive."
@@ -150,6 +153,7 @@ class FusedMoEQuantConfig:
             use_int8_w8a8=use_int8_w8a8,
             use_int8_w8a16=use_int8_w8a16,
             use_int4_w4a16=use_int4_w4a16,
+            use_int4_w4a8=use_int4_w4a8,
             use_mxfp4_w4a4=use_mxfp4_w4a4,
         )
         return FusedMoEQuantConfig(

vllm/model_executor/layers/fused_moe/fused_moe.py

@@ -676,7 +676,6 @@ def invoke_fused_moe_kernel(A: torch.Tensor,
                             B_scale: Optional[torch.Tensor],
                             B_zp: Optional[torch.Tensor],
                             topk_weights: Optional[torch.Tensor],
-                            topk_ids: torch.Tensor,
                             sorted_token_ids: torch.Tensor,
                             expert_ids: torch.Tensor,
                             num_tokens_post_padded: torch.Tensor,
@@ -1863,6 +1862,7 @@ def fused_experts_impl(
                                    use_int8_w8a8=use_int8_w8a8,
                                    use_int8_w8a16=use_int8_w8a16,
                                    use_int4_w4a16=use_int4_w4a16,
+                                   use_int4_w4a8=use_int4_w4a8,
                                    use_mxfp4_w4a4=use_mxfp4_w4a4)
 
     get_config_func = functools.partial(
@@ -1955,7 +1955,6 @@ def fused_experts_impl(
                                 w1_scale,
                                 w1_zp,
                                 curr_topk_weights,
-                                curr_topk_ids,
                                 sorted_token_ids,
                                 expert_ids,
                                 num_tokens_post_padded,
@@ -2008,7 +2007,6 @@ def fused_experts_impl(
                                 w2_scale,
                                 w2_zp,
                                 curr_topk_weights,
-                                curr_topk_ids,
                                 sorted_token_ids,
                                 expert_ids,
                                 num_tokens_post_padded,
@@ -2370,7 +2368,7 @@ class TritonExperts(mk.FusedMoEPermuteExpertsUnpermute):
             use_int8_w8a8=self.use_int8_w8a8,
             use_int8_w8a16=self.use_int8_w8a16,
             use_int4_w4a16=self.use_int4_w4a16,
-            use_int4_w4a8= self.use_int4_w4a8,
+            use_int4_w4a8=self.use_int4_w4a8,
             per_channel_quant=self.per_act_token_quant,
             block_shape=self.block_shape,
             B_bias=None  # TODO support B_bias
@@ -2384,7 +2382,7 @@ def modular_triton_fused_moe(
     use_int8_w8a8: bool,
     use_int8_w8a16: bool,
     use_int4_w4a16: bool,
-    use_int4_w4a8:bool,
+    use_int4_w4a8: bool,
     use_mxfp4_w4a4: bool,
     per_act_token_quant: bool,
     block_shape: Optional[List[int]] = None,
@@ -2396,7 +2394,7 @@ def modular_triton_fused_moe(
             use_int8_w8a8=use_int8_w8a8,
             use_int8_w8a16=use_int8_w8a16,
             use_int4_w4a16=use_int4_w4a16,
-            use_int4_w4a8= use_int4_w4a8,
+            use_int4_w4a8=use_int4_w4a8,
             use_mxfp4_w4a4=use_mxfp4_w4a4,
             per_act_token_quant=per_act_token_quant,
             block_shape=block_shape,