[Rocm][fused_moe][fp4] view weight to torch.float4_e2m1fn_x2 when running...

[Rocm][fused_moe][fp4] view weight to torch.float4_e2m1fn_x2 when running aiter fused moe for fp4 model (#27474)
Signed-off-by: zejunchen-zejun <zejun.chen@amd.com>

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

@@ -458,6 +458,7 @@ class QuarkOCP_MX_MoEMethod(QuarkMoEMethod):
 
         self.weight_dtype = self.weight_quant["dtype"].replace("fp", "mxfp")
         self.input_dtype = self.input_quant["dtype"].replace("fp", "mxfp")
+        self.fp4_dtype = getattr(torch, "float4_e2m1fn_x2", None)
 
         self.ocp_mx_scheme = OCP_MX_Scheme.from_quant_dtype(
             self.input_dtype, self.weight_dtype
@@ -581,6 +582,17 @@ class QuarkOCP_MX_MoEMethod(QuarkMoEMethod):
         w2_weight_scale = layer.w2_weight_scale.view(s0 * s1, -1)
         w2_weight_scale = e8m0_shuffle(w2_weight_scale)
         layer.w2_weight_scale.data = w2_weight_scale.view(s0, s1, -1)
+
+        if self.fp4_dtype is not None:
+            layer.w13_weight = torch.nn.Parameter(
+                layer.w13_weight.view(self.fp4_dtype),
+                requires_grad=layer.w13_weight.requires_grad,
+            )
+            layer.w2_weight = torch.nn.Parameter(
+                layer.w2_weight.view(self.fp4_dtype),
+                requires_grad=layer.w2_weight.requires_grad,
+            )
+
         torch.cuda.empty_cache()
 
     def get_fused_moe_quant_config(