[BugFix]Fix precision issue for LoRA feature (#4141)

vLLM version: v0.11.0
vLLM main: vllm-project/vllm

### What this PR does / why we need it?
   Fix the precision issue of the LoRA feature in vllm-ascend.

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?
```bash
pytest tests/lora/test_llama_tp.py::test_llama_lora -s
```
<img width="1319" height="879" alt="lora_test"
src="https://github.com/user-attachments/assets/2a0b2325-5b05-4bbc-ac03-a7c9f0ad9d4c"
/>


- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: hukongyi <hukongyi@cmbchina.com>

CMakeLists.txt

@@ -62,6 +62,10 @@ set(VLLM_ASCEND_CUSTOM_OP
 )
 
 set(VLLM_ASCEND_CUSTOM_OP_EXCLUDE
+    ${KERNEL_FILES}/bgmv_expand.cpp
+    ${KERNEL_FILES}/bgmv_shrink.cpp
+    ${KERNEL_FILES}/sgmv_expand.cpp
+    ${KERNEL_FILES}/sgmv_shrink.cpp
     ${CMAKE_CURRENT_SOURCE_DIR}/csrc/batch_matmul_transpose/op_kernel/batch_matmul_transpose_kernel.cpp
 )
 

csrc/kernels/bgmv_expand.cpp

@@ -342,7 +342,7 @@ private:
 
 // declare all dtype kernel
 BGMV_EXPAND_TYPE_DECLARE(half)
-#if (__CCE_AICORE__ >= 220)
+#if !defined(__CCE_AICORE__) || (__CCE_AICORE__ >= 220)
     BGMV_EXPAND_TYPE_DECLARE(bfloat16_t)
 #endif
 
@@ -356,7 +356,7 @@ extern void bgmv_expand_impl(AscendType type, void* stream, void* x, void* weigh
         bgmv_expand_half<<<blockDim, nullptr, stream>>>(x, weight, indices, indicesSize, yIn, yOut, batchSize, numTokensPerCore,
                                                         maxLoRARank, outputHiddenDim, sliceOffset, outputFullDim);
     } else if (type == AscendType::BF16) {
-        #if (__CCE_AICORE__ >= 220)
+        #if !defined(__CCE_AICORE__) || (__CCE_AICORE__ >= 220)
         bgmv_expand_bfloat16_t<<<blockDim, nullptr, stream>>>(x, weight, indices, indicesSize, yIn, yOut, batchSize,
                                                                   numTokensPerCore, maxLoRARank, outputHiddenDim,
                                                                   sliceOffset, outputFullDim);

csrc/kernels/bgmv_shrink.cpp

@@ -226,7 +226,7 @@ private:
 
 // declare all dtype kernel
 BGMV_SHRINK_TYPE_DECLARE(half)
-#if (__CCE_AICORE__ >= 220)
+#if !defined(__CCE_AICORE__) || (__CCE_AICORE__ >= 220)
     BGMV_SHRINK_TYPE_DECLARE(bfloat16_t)
 #endif
 
@@ -240,7 +240,7 @@ extern void bgmv_shrink_impl(AscendType type, void* stream, void* x, void* weigh
         bgmv_shrink_half<<<blockDim, nullptr, stream>>>(x, weight, indices, indicesSize, y, batchSize, numTokensPerCore, 
                                                         inputHiddenDim, maxLoRARank, scale);
     } else if (type == AscendType::BF16) {
-        #if (__CCE_AICORE__ >= 220)
+        #if !defined(__CCE_AICORE__) || (__CCE_AICORE__ >= 220)
         bgmv_shrink_bfloat16_t<<<blockDim, nullptr, stream>>>(x, weight, indices, indicesSize, y, batchSize, numTokensPerCore, 
                                                                   inputHiddenDim, maxLoRARank, scale);
         #endif

csrc/kernels/sgmv_expand.cpp

@@ -357,7 +357,7 @@ private:
 
 // declare all dtype kernel
 SGMV_EXPAND_TYPE_DECLARE(half)
-#if (__CCE_AICORE__ >= 220)
+#if !defined(__CCE_AICORE__) || (__CCE_AICORE__ >= 220)
     SGMV_EXPAND_TYPE_DECLARE(bfloat16_t)
 #endif
 
@@ -375,7 +375,7 @@ extern void sgmv_expand_impl(AscendType type, void* stream, void* x, void* weigh
                                                         numTokensPerCore, maxLoRARank, outputHiddenDim, sliceOffset, 
                                                         outputFullDim);
     } else if (type == AscendType::BF16) {
-        #if (__CCE_AICORE__ >= 220)
+        #if !defined(__CCE_AICORE__) || (__CCE_AICORE__ >= 220)
         sgmv_expand_bfloat16_t<<<blockDim, nullptr, stream>>>(x, weight, loraIndices, loraIndicesSize, 
                                                                   seqLen, seqLenSize, yIn, yOut, batchSize,
                                                                   numTokensPerCore, maxLoRARank, outputHiddenDim,

csrc/kernels/sgmv_shrink.cpp

@@ -242,7 +242,7 @@ private:
 
 // declare all dtype kernel
 SGMV_SHRINK_TYPE_DECLARE(half)
-#if (__CCE_AICORE__ >= 220)
+#if !defined(__CCE_AICORE__) || (__CCE_AICORE__ >= 220)
     SGMV_SHRINK_TYPE_DECLARE(bfloat16_t)
 #endif
 
@@ -260,7 +260,7 @@ extern void sgmv_shrink_impl(AscendType type, void* stream, void* x, void* weigh
                                                         numTokensPerCore, inputHiddenDim, maxLoRARank,
                                                         scale);
     } else if (type == AscendType::BF16) {
-        #if (__CCE_AICORE__ >= 220)
+        #if !defined(__CCE_AICORE__) || (__CCE_AICORE__ >= 220)
         sgmv_shrink_bfloat16_t<<<blockDim, nullptr, stream>>>(x, weight, loraIndices, loraIndicesSize, 
                                                                   seqLen, seqLenSize, 
                                                                   y, batchSize,

vllm_ascend/lora/punica_npu.py

@@ -255,6 +255,7 @@ class PunicaWrapperNPU(PunicaWrapperBase):
         # Embedding layer only need expand op
         expand_fun: Callable = (self._expand_prefill
                                 if self.is_prefill else self._expand_decode)
+        x = x.to(torch.float32)
         expand_fun(y, x, lora_b_stacked, add_inputs)
 
     def add_lora_linear(self,