+------------------------------------------------------------------------------------------------+
| npu-smi 25.5.0 Version: 25.5.0 |
+---------------------------+---------------+----------------------------------------------------+
| NPU Name | Health | Power(W) Temp(C) Hugepages-Usage(page)|
| Chip | Bus-Id | AICore(%) Memory-Usage(MB) HBM-Usage(MB) |
+===========================+===============+====================================================+
| 4 910B4-1 | OK | 92.3 39 0 / 0 |
| 0 | 0000:01:00.0 | 0 0 / 0 3403 / 65536 |
+===========================+===============+====================================================+
| 5 910B4-1 | OK | 93.0 37 0 / 0 |
| 0 | 0000:02:00.0 | 0 0 / 0 3402 / 65536 |
+===========================+===============+====================================================+
+---------------------------+---------------+----------------------------------------------------+
| NPU Chip | Process id | Process name | Process memory(MB) |
+===========================+===============+====================================================+
| No running processes found in NPU 4 |
+===========================+===============+====================================================+
| No running processes found in NPU 5 |
+===========================+===============+====================================================+
package_name=Ascend-cann-toolkit
version=8.3.RC2
innerversion=V100R001C23SPC002B210
compatible_version=[V100R001C15],[V100R001C18],[V100R001C19],[V100R001C20],[V100R001C21],[V100R001C23]
arch=aarch64
os=linux
path=/usr/local/Ascend/ascend-toolkit/8.3.RC2/aarch64-linux
Collecting environment information...
==============================
System Info
==============================
OS : Ubuntu 22.04.5 LTS (aarch64)
GCC version : (Ubuntu 11.4.0-1ubuntu1~22.04.2) 11.4.0
Clang version : Could not collect
CMake version : version 4.2.1
Libc version : glibc-2.35
==============================
PyTorch Info
==============================
PyTorch version : 2.8.0+cpu
Is debug build : False
CUDA used to build PyTorch : None
ROCM used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.11.13 (main, Nov 20 2025, 16:02:27) [GCC 11.4.0] (64-bit runtime)
Python platform : Linux-5.10.0-216.0.0.115.oe2203sp4.aarch64-aarch64-with-glibc2.35
==============================
CUDA / GPU Info
==============================
Is CUDA available : False
CUDA runtime version : No CUDA
CUDA_MODULE_LOADING set to : N/A
GPU models and configuration : No CUDA
Nvidia driver version : No CUDA
cuDNN version : No CUDA
HIP runtime version : N/A
MIOpen runtime version : N/A
Is XNNPACK available : True
==============================
CPU Info
==============================
Architecture: aarch64
CPU op-mode(s): 64-bit
Byte Order: Little Endian
CPU(s): 192
On-line CPU(s) list: 0-191
Vendor ID: HiSilicon
Model name: Kunpeng-920
Model: 0
Thread(s) per core: 1
Core(s) per cluster: 48
Socket(s): -
Cluster(s): 4
Stepping: 0x1
BogoMIPS: 200.00
Flags: fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm jscvt fcma dcpop asimddp asimdfhm ssbs
L1d cache: 12 MiB (192 instances)
L1i cache: 12 MiB (192 instances)
L2 cache: 96 MiB (192 instances)
L3 cache: 192 MiB (8 instances)
NUMA node(s): 8
NUMA node0 CPU(s): 0-23
NUMA node1 CPU(s): 24-47
NUMA node2 CPU(s): 48-71
NUMA node3 CPU(s): 72-95
NUMA node4 CPU(s): 96-119
NUMA node5 CPU(s): 120-143
NUMA node6 CPU(s): 144-167
NUMA node7 CPU(s): 168-191
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; __user pointer sanitization
Vulnerability Spectre v2: Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
==============================
Versions of relevant libraries
==============================
[pip3] numpy==1.26.4
[pip3] pyzmq==27.1.0
[pip3] torch==2.8.0+cpu
[pip3] torch_npu==2.8.0
[pip3] torchvision==0.23.0
[pip3] transformers==4.57.3
[conda] Could not collect
==============================
vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.1.dev9501+g331f1e60d.d20260302 (git sha: 331f1e60d, date: 20260302)
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
Could not collect
==============================
Environment Variables
==============================
LD_LIBRARY_PATH=/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_1/lib:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_1/examples:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_1/tests/atbopstest:/usr/local/Ascend/ascend-toolkit/latest/tools/aml/lib64:/usr/local/Ascend/ascend-toolkit/latest/tools/aml/lib64/plugin:/usr/local/Ascend/ascend-toolkit/latest/lib64:/usr/local/Ascend/ascend-toolkit/latest/lib64/plugin/opskernel:/usr/local/Ascend/ascend-toolkit/latest/lib64/plugin/nnengine:/usr/local/Ascend/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling/lib/linux/aarch64:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_0/lib:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_0/examples:/usr/local/Ascend/nnal/atb/latest/atb/cxx_abi_0/tests/atbopstest:/usr/local/Ascend/ascend-toolkit/latest/tools/aml/lib64:/usr/local/Ascend/ascend-toolkit/latest/tools/aml/lib64/plugin:/usr/local/Ascend/ascend-toolkit/latest/lib64:/usr/local/Ascend/ascend-toolkit/latest/lib64/plugin/opskernel:/usr/local/Ascend/ascend-toolkit/latest/lib64/plugin/nnengine:/usr/local/Ascend/ascend-toolkit/latest/opp/built-in/op_impl/ai_core/tbe/op_tiling:/usr/local/Ascend/driver/lib64/common/:/usr/local/Ascend/driver/lib64/driver/:
OMP_NUM_THREADS=1
TORCH_DEVICE_BACKEND_AUTOLOAD=1
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
我想在昇腾服务器上部署你们的代码，尝试测试AFD功能，请问需要的vllm、vllm-ascend仓库代码版本代码是？
目前vllm代码采用了
https://github.com/JiusiServe/vllm/tree/afd-dev
（命令为：VLLM_TARGET_DEVICE=empty pip install -v -e . --no-build-isolation）
vllm-ascend代码采用你们仓库的ascendmian-1020分支
（"torch-npu==2.7.1.dev20250724"改为"torch-npu>=2.7.1.dev20250724"，因为我的环境torch-npu 2.8.0）
（命令为：pip install -v -e . --no-build-isolation）
两个仓库都可以编译通过，但是目前两个仓库的代码是不匹配的。
