From c455b771fdfd9185ca5c20d315c07dd5390b5459 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?RickyChen=20/=20=E9=99=B3=E6=98=AD=E5=84=92?=
 <ricky.chen@infinirc.com>
Date: Tue, 6 Jan 2026 01:25:38 +0800
Subject: [PATCH] [Bugfix][CPU] Fix RotaryEmbedding fallback causing gibberish
 with --enforce-eager (#31643)

Signed-off-by: rickychen-infinirc <ricky.chen@infinirc.com>
---
 vllm/model_executor/custom_op.py              |  5 +++--
 .../layers/rotary_embedding/base.py           | 22 +++++++++++++++++++
 2 files changed, 25 insertions(+), 2 deletions(-)

diff --git a/vllm/model_executor/custom_op.py b/vllm/model_executor/custom_op.py
index 66250f816f..a80768c33a 100644
--- a/vllm/model_executor/custom_op.py
+++ b/vllm/model_executor/custom_op.py
@@ -67,8 +67,9 @@ class CustomOp(nn.Module):
         return self.forward_native(*args, **kwargs)
 
     def forward_cpu(self, *args, **kwargs):
-        # By default, we assume that CPU ops are compatible with CUDA ops.
-        return self.forward_cuda(*args, **kwargs)
+        # By default, we assume that CPU ops are compatible with the
+        # PyTorch-native implementation.
+        return self.forward_native(*args, **kwargs)
 
     def forward_tpu(self, *args, **kwargs):
         # By default, we assume that TPU ops are compatible with the
diff --git a/vllm/model_executor/layers/rotary_embedding/base.py b/vllm/model_executor/layers/rotary_embedding/base.py
index 7e83ea9a13..bd82728ed1 100644
--- a/vllm/model_executor/layers/rotary_embedding/base.py
+++ b/vllm/model_executor/layers/rotary_embedding/base.py
@@ -250,6 +250,28 @@ class RotaryEmbedding(RotaryEmbeddingBase):
             )
         return query, key
 
+    def forward_cpu(
+        self,
+        positions: torch.Tensor,
+        query: torch.Tensor,
+        key: torch.Tensor | None = None,
+    ) -> tuple[torch.Tensor, torch.Tensor | None]:
+        from vllm import _custom_ops as ops
+
+        self._match_cos_sin_cache_dtype(query)
+
+        # ops.rotary_embedding() is an in-place operation
+        # that updates the query and key tensors.
+        ops.rotary_embedding(
+            positions,
+            query,
+            key,
+            self.head_size,
+            self.cos_sin_cache,
+            self.is_neox_style,
+        )
+        return query, key
+
     def extra_repr(self) -> str:
         s = f"head_size={self.head_size}, rotary_dim={self.rotary_dim}"
         s += f", max_position_embeddings={self.max_position_embeddings}"