The torch==2.5.0 PyPI wheel distribution logs an error message to the console on import on arm64 platforms.
Python 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import torch Error in cpuinfo: prctl(PR_SVE_GET_VL) failed >>> torch.__version__ '2.5.0'
The import succeeds and the console error does not appear to impact functionality. The issue is not reproducible after downgrading to torch==2.4.1.
Running cpuinfo directly does not return an error:
$ cpuinfo Python Version: 3.10.12.final.0 (64 bit) Cpuinfo Version: 9.0.0 ...
Reproduced across two local arm64 systems, could not reproduce on x86.
VersionsRunning in a Docker container based on nvcr.io/nvidia/clara-holoscan/holoscan:v2.5.0-dgpu
PyTorch version: 2.5.0
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A
OS: Ubuntu 22.04.2 LTS (aarch64)
GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0
Clang version: Could not collect
CMake version: version 3.24.0
Libc version: glibc-2.35
Python version: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] (64-bit runtime)
Is CUDA available: False
CUDA runtime version: 12.2.128
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: GPU 0: NVIDIA RTX 6000 Ada Generation
Nvidia driver version: 535.183.01
cuDNN version: Probably one of the following:
/usr/lib/aarch64-linux-gnu/libcudnn.so.8.9.4
/usr/lib/aarch64-linux-gnu/libcudnn_adv_infer.so.8.9.4
/usr/lib/aarch64-linux-gnu/libcudnn_adv_train.so.8.9.4
/usr/lib/aarch64-linux-gnu/libcudnn_cnn_infer.so.8.9.4
/usr/lib/aarch64-linux-gnu/libcudnn_cnn_train.so.8.9.4
/usr/lib/aarch64-linux-gnu/libcudnn_ops_infer.so.8.9.4
/usr/lib/aarch64-linux-gnu/libcudnn_ops_train.so.8.9.4
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Architecture: aarch64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
CPU(s): 12
On-line CPU(s) list: 0-11
Vendor ID: ARM
Model name: Cortex-A78AE
Model: 1
Thread(s) per core: 1
Core(s) per cluster: 4
Socket(s): -
Cluster(s): 3
Stepping: r0p1
CPU max MHz: 1971.2000
CPU min MHz: 115.2000
BogoMIPS: 62.50
Flags: fp asimd evtstrm aes pmull sha1 sha2 crc32 atomics fphp asimdhp cpuid asimdrdm lrcpc dcpop asimddp uscat ilrcpc flagm paca pacg
L1d cache: 768 KiB (12 instances)
L1i cache: 768 KiB (12 instances)
L2 cache: 3 MiB (12 instances)
L3 cache: 6 MiB (3 instances)
NUMA node(s): 1
NUMA node0 CPU(s): 0-11
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 Reg file data sampling: 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: Mitigation; CSV2, BHB
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] numpy==1.23.5
[pip3] onnx==1.17.0
[pip3] torch==2.5.0
[pip3] torchvision==0.20.0
[conda] Could not collect
cc @ezyang @gchanan @zou3519 @kadeng @msaroufim @malfet @snadampal @milpuz01
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