error: ‘class torch::Library’ has no member named ‘set_python_module’
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Description
🐛 Describe the bug
I was trying to install torchvision==0.19.0 from source.
After download zip file, for command: python setup.py install, I got an error:
error: ‘class torch::Library’ has no member named ‘set_python_module’
Versions
PyTorch version: 2.4.0a0+07cecf4168.nv24.05
Is debug build: False
CUDA used to build PyTorch: 12.2
ROCM used to build PyTorch: N/A
OS: Ubuntu 22.04.4 LTS (aarch64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.22.1
Libc version: glibc-2.35
Python version: 3.10.14 (main, May 6 2024, 19:36:58) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.136-tegra-aarch64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.2.140
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: Orin (nvgpu)
Nvidia driver version: N/A
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: 0-7
Off-line CPU(s) list: 8-11
Vendor ID: ARM
Model name: Cortex-A78AE
Model: 1
Thread(s) per core: 1
Core(s) per cluster: 4
Socket(s): -
Cluster(s): 2
Stepping: r0p1
CPU max MHz: 2201.6001
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: 512 KiB (8 instances)
L1i cache: 512 KiB (8 instances)
L2 cache: 2 MiB (8 instances)
L3 cache: 4 MiB (2 instances)
NUMA node(s): 1
NUMA node0 CPU(s): 0-7
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: Mitigation; CSV2, but not BHB
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] ament-flake8==0.12.11
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[pip3] onnxruntime==1.19.0
[pip3] torch==2.4.0a0+07cecf4168.nv24.5
[conda] torch 2.4.0a0+07cecf4168.nv24.5 pypi_0 pypi
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The report identifies the setup.py install command, torchvision 0.19.0, and a torch::Library compilation error; start by reproducing it in the listed PyTorch 2.4.0a0 environment. Trace the source or build entry point that references set_python_module, then verify that the source installation completes successfully.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python
- Domain
- build-system, computer-vision
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100