`torch.det` with python 3.10 and torch 2.5.0+cu121 raises RuntimeError

[lykius]

🐛 Describe the bug

With python 3.10 and torch 2.5.0+cu121, torch.det on a cuda tensor raises the following error:

RuntimeError: Error in dlopen for library libnvrtc.so.12and libnvrtc-XXXXXXXX.so.12

Code to reproduce:

import torch

torch.det(torch.rand(4, 4).cuda())

Versions

PyTorch version: 2.5.0+cu121 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.5 LTS (x86_64) 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: 3.10.9 (main, Feb 8 2023, 09:53:56) [GCC 11.3.0] (64-bit runtime) Python platform: Linux-6.8.0-49-generic-x86_64-with-glibc2.35 Is CUDA available: True CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce RTX 2070 with Max-Q Design Nvidia driver version: 535.183.01 cuDNN version: Could not collect HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True

CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 39 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 12 On-line CPU(s) list: 0-11 Vendor ID: GenuineIntel Model name: Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz CPU family: 6 Model: 158 Thread(s) per core: 2 Core(s) per socket: 6 Socket(s): 1 Stepping: 10 CPU max MHz: 4500,0000 CPU min MHz: 800,0000 BogoMIPS: 5199.98 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb pti ssbd ibrs ibpb stibp tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp vnmi md_clear flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 192 KiB (6 instances) L1i cache: 192 KiB (6 instances) L2 cache: 1,5 MiB (6 instances) L3 cache: 12 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-11 Vulnerability Gather data sampling: Mitigation; Microcode Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled Vulnerability L1tf: Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable Vulnerability Mds: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Meltdown: Mitigation; PTI Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Mitigation; IBRS Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; IBRS; IBPB conditional; STIBP conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected Vulnerability Srbds: Mitigation; Microcode Vulnerability Tsx async abort: Not affected

Versions of relevant libraries: [pip3] numpy==2.1.3 [pip3] torch==2.5.0+cu121 [conda] Could not collect

cc @seemethere @malfet @osalpekar @atalman @ptrblck @msaroufim

[malfet]

This sounds very much like a duplicate of https://github.com/pytorch/pytorch/issues/140797

@lykius do you mind sharing your LD_LIBRARY_PATH? And perhaps, try invoking PyTorch without it. Will it work?

[lykius]

Hi @malfet,

My LD_LIBRARY_PATH is blank, I just checked to be sure. Some additional info: I get the error with torch >= 2.5.0, no issue with previous versions. So maybe this situation is somehow linked to #140797, as you suggest.