[Optimize]Change AI Vector core number getting function to glibc ABI free funcition (#1974)

### What this PR does / why we need it?
Change AI Vector core number getting function to glibc ABI free
function. After this PR merged in, there should been no glibc ABI
problems for bump torch version to 2.7.1.

### Does this PR introduce _any_ user-facing change?
No

- vLLM version: v0.9.2
- vLLM main:
f59ec35b7f

Signed-off-by: leo-pony <nengjunma@outlook.com>

csrc/torch_binding.cpp

@@ -22,8 +22,6 @@
 #include <torch_npu/csrc/npu/Module.h>
 #include <pybind11/pybind11.h>
 #include "acl/acl.h"
-#include "tiling/platform/platform_ascendc.h"
-#include "aclnn/opdev/platform.h"
 #include "ops.h"
 #include "utils.h"
 
@@ -85,14 +83,13 @@ std::tuple<at::Tensor, at::Tensor> rotary_embedding(at::Tensor &positions, at::T
                           query_ptr, key_ptr, cos_sin_cache_ptr, rot_dim, query_stride, key_stride,
                           dst_query_stride, dst_key_stride, num_heads, num_kv_heads, head_size]() -> int {
         auto dtype_num = get_dtype_from_torch(scalar_type);
-        fe::PlatFormInfos platform_infos;
         int device_id = 0;
-        fe::PlatformInfoManager::GeInstance().GetRuntimePlatformInfosByDevice(device_id, platform_infos);
-        uint32_t aivNum = platform_infos.GetCoreNumByType("aiv");
-        uint32_t loop_cnt = (num_tokens + aivNum - 1) / aivNum;
+        int64_t aiv_num = 0;
+        TORCH_CHECK(aclGetDeviceCapability(device_id, ACL_DEVICE_INFO_VECTOR_CORE_NUM, &aiv_num) == ACL_SUCCESS);
+        uint32_t loop_cnt = (num_tokens + aiv_num - 1) / aiv_num;
         rotary_embedding_impl(dtype_num, is_neox, stream, position_ids_ptr, query_dst_ptr, key_dst_ptr, query_ptr,
                                 key_ptr, cos_sin_cache_ptr, rot_dim, query_stride, key_stride, dst_query_stride,
-                                dst_key_stride, num_heads, num_kv_heads, head_size, num_tokens, loop_cnt, aivNum);
+                                dst_key_stride, num_heads, num_kv_heads, head_size, num_tokens, loop_cnt, aiv_num);
         return 0;
     });
     cmd.Run();
@@ -177,13 +174,11 @@ std::tuple<at::Tensor, at::Tensor> get_masked_input_and_mask(
                          org_vocab_start_index, org_vocab_end_index,
                          num_org_vocab_padding, added_vocab_start_index,
                          added_vocab_end_index]() -> int {
-        // Get platform info
-        fe::PlatFormInfos platform_infos;
         int device_id = 0;
-        fe::PlatformInfoManager::GeInstance().GetRuntimePlatformInfosByDevice(device_id, platform_infos);
-        uint32_t aivNum = platform_infos.GetCoreNumByType("aiv");
-        uint32_t loop_cnt = (size + aivNum - 1) / aivNum;
-        
+        int64_t aiv_num = 0;
+        TORCH_CHECK(aclGetDeviceCapability(device_id, ACL_DEVICE_INFO_VECTOR_CORE_NUM, &aiv_num) == ACL_SUCCESS);
+        uint32_t loop_cnt = (size + aiv_num - 1) / aiv_num;
+
         // Call implementation
         get_masked_input_and_mask_impl(
             stream,
@@ -197,7 +192,7 @@ std::tuple<at::Tensor, at::Tensor> get_masked_input_and_mask(
             added_vocab_end_index,
             size,
             loop_cnt,
-            aivNum);
+            aiv_num);
             
         return 0;
     });

tests/e2e/singlecard/ops/test_vocabparallelembedding.py

@@ -5,6 +5,9 @@ import torch
 import torch_npu  # noqa: F401
 
 import vllm_ascend.platform  # noqa: F401
+from vllm_ascend.utils import enable_custom_op
+
+enable_custom_op()
 
 # Test parameters
 DTYPES = [torch.int32]