[Bugfix] Fix GPT-OSS on AMD after #28603 (#28816)

Signed-off-by: zhewenli <zhewenli@meta.com>

.buildkite/test-amd.yaml

@@ -1068,7 +1068,7 @@ steps:
     # this runner has 2 GPUs available even though num_gpus=2 is not set
     - pytest -v -s tests/compile/test_fusion_all_reduce.py
     # Limit to Inductor partition, no custom ops, and allreduce & attn fusion to reduce running time
-    # Wrap with quotes to escape yaml 
+    # Wrap with quotes to escape yaml
     - "pytest -v -s tests/compile/test_fusions_e2e.py::test_tp2_attn_quant_allreduce_rmsnorm -k 'True and Llama-3.1 and -quant_fp8 and -rms_norm'"
 
 - label: Blackwell Fusion E2E Tests # 30 min
@@ -1095,10 +1095,11 @@ steps:
     # test_fp8_kv_scale_compile requires FlashAttention (not supported on default L4/L40)
     - pytest -v -s tests/compile/test_full_graph.py::test_fp8_kv_scale_compile
 
-- label: Blackwell GPT-OSS Eval
+- label: ROCm GPT-OSS Eval
   timeout_in_minutes: 60
   working_dir: "/vllm-workspace/"
-  gpu: b200
+  agent_pool: mi325_1
+  mirror_hardwares: [amdproduction]
   optional: true # run on nightlies
   source_file_dependencies:
   - tests/evals/gpt_oss
@@ -1107,7 +1108,7 @@ steps:
   - vllm/v1/attention/backends/flashinfer.py
   commands:
     - uv pip install --system 'gpt-oss[eval]==0.0.5'
-    - pytest -s -v tests/evals/gpt_oss/test_gpqa_correctness.py --model openai/gpt-oss-20b --metric 0.58
+    - VLLM_ROCM_USE_AITER_MHA=0 VLLM_ROCM_USE_AITER=1 VLLM_USE_AITER_UNIFIED_ATTENTION=1 pytest -s -v tests/evals/gpt_oss/test_gpqa_correctness.py --model openai/gpt-oss-20b --metric 0.58
 
 - label: Blackwell Quantized MoE Test
   timeout_in_minutes: 60

vllm/model_executor/layers/quantization/mxfp4.py

@@ -755,8 +755,8 @@ class Mxfp4MoEMethod(FusedMoEMethodBase):
 
             self.w13_weight = w13_weight
             self.w2_weight = w2_weight
-            layer.w13_weight = Parameter(w13_weight.data, requires_grad=False)
-            layer.w2_weight = Parameter(w2_weight.data, requires_grad=False)
+            layer.w13_weight = Parameter(w13_weight.storage.data, requires_grad=False)
+            layer.w2_weight = Parameter(w2_weight.storage.data, requires_grad=False)
         else:
             raise ValueError(f"Unsupported backend: {self.mxfp4_backend}")