update layer.py

vllm/model_executor/layers/fused_moe/layer.py

@@ -28,8 +28,8 @@ from vllm.model_executor.layers.fused_moe.config import (
 from vllm.model_executor.layers.fused_moe.modular_kernel import (
     FusedMoEActivationFormat, FusedMoEModularKernel,
     FusedMoEPermuteExpertsUnpermute, FusedMoEPrepareAndFinalize)
-from vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe import (
-    is_rocm_aiter_moe_enabled)
+# from vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe import (
+#     is_rocm_aiter_moe_enabled)
 from vllm.model_executor.layers.quantization.base_config import (
     QuantizationConfig, QuantizeMethodBase)
 from vllm.model_executor.utils import set_weight_attrs
@@ -228,7 +228,8 @@ class UnquantizedFusedMoEMethod(FusedMoEMethodBase, CustomOp):
         self.topk_indices_dtype = None
         self.moe = moe
 
-        self.rocm_aiter_moe_enabled = is_rocm_aiter_moe_enabled()
+        # self.rocm_aiter_moe_enabled = is_rocm_aiter_moe_enabled()
+        self.rocm_aiter_moe_enabled = False
         if self.rocm_aiter_moe_enabled:
             from .rocm_aiter_fused_moe import rocm_aiter_fused_experts
             self.rocm_aiter_fused_experts = rocm_aiter_fused_experts
@@ -309,15 +310,15 @@ class UnquantizedFusedMoEMethod(FusedMoEMethodBase, CustomOp):
         layer.w13_weight.data = self._maybe_pad_weight(layer.w13_weight.data)
         layer.w2_weight.data = self._maybe_pad_weight(layer.w2_weight.data)
         # Lazy import to avoid importing triton.
-        from vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe import (
-            shuffle_weights)
+        # from vllm.model_executor.layers.fused_moe.rocm_aiter_fused_moe import (
+        #     shuffle_weights)
 
-        if self.rocm_aiter_moe_enabled:
-            shuffled_w13, shuffled_w2 = shuffle_weights(
-                layer.w13_weight.data, layer.w2_weight.data)
+        # if self.rocm_aiter_moe_enabled:
+        #     shuffled_w13, shuffled_w2 = shuffle_weights(
+        #         layer.w13_weight.data, layer.w2_weight.data)
 
-            layer.w13_weight.data = shuffled_w13
-            layer.w2_weight.data = shuffled_w2
+        #     layer.w13_weight.data = shuffled_w13
+        #     layer.w2_weight.data = shuffled_w2
 
         if current_platform.is_cpu():
             if current_platform.get_cpu_architecture() == CpuArchEnum.X86: