Aseem139
commented
5 days ago Here are the installation details
(skoots-env2) [akas0018@m3t103 skoots]$ python -m torch.utils.collect_env /scratch/cm10/akas0018/miniconda/conda/envs/skoots-env2/lib/python3.10/runpy.py:126: RuntimeWarning: 'torch.utils.collect_env' found in sys.modules after import of package 'torch.utils', but prior to execution of 'torch.utils.collect_env'; this may result in unpredictable behaviour warn(RuntimeWarning(msg)) Collecting environment information... PyTorch version: 2.4.1+cu118 Is debug build: False CUDA used to build PyTorch: 11.8 ROCM used to build PyTorch: N/A
OS: Rocky Linux 9.2 (Blue Onyx) (x86_64) GCC version: (GCC) 11.3.1 20221121 (Red Hat 11.3.1-4) Clang version: 15.0.7 (Red Hat 15.0.7-2.el9) CMake version: version 3.20.2 Libc version: glibc-2.34
Python version: 3.10.15 (main, Oct 3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-5.14.0-284.25.1.el9_2.x86_64-x86_64-with-glibc2.34 Is CUDA available: True CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: Tesla T4 Nvidia driver version: 535.104.05 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: 46 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 52 On-line CPU(s) list: 0-51 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Gold 6230R CPU @ 2.10GHz CPU family: 6 Model: 85 Thread(s) per core: 1 Core(s) per socket: 26 Socket(s): 2 Stepping: 7 CPU max MHz: 4000.0000 CPU min MHz: 1000.0000 BogoMIPS: 4200.00 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 smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts pku ospke avx512_vnni md_clear flush_l1d arch_capabilities L1d cache: 1.6 MiB (52 instances) L1i cache: 1.6 MiB (52 instances) L2 cache: 52 MiB (52 instances) L3 cache: 71.5 MiB (2 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38,40,42,44,46,48,50 NUMA node1 CPU(s): 1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39,41,43,45,47,49,51 Vulnerability Itlb multihit: KVM: Mitigation: VMX unsupported Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT disabled Vulnerability Retbleed: Mitigation; Enhanced IBRS 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; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; TSX disabled
Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==2.0.1
[pip3] torch==2.4.1+cu118
[pip3] torchaudio==2.4.1+cu118
[pip3] torchvision==0.19.1+cu118
[pip3] triton==3.0.0
[pip3] triton-library==1.0.0rc4
[conda] blas 1.0 mkl
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] libjpeg-turbo 2.0.0 h9bf148f_0 pytorch
[conda] mkl 2023.1.0 h213fc3f_46344
[conda] mkl-fft 1.3.10 pypi_0 pypi
[conda] mkl-random 1.2.7 pypi_0 pypi
[conda] mkl-service 2.4.0 pypi_0 pypi
[conda] mkl_fft 1.3.10 py310h5eee18b_0
[conda] mkl_random 1.2.7 py310h1128e8f_0
[conda] numpy 2.0.1 pypi_0 pypi
[conda] numpy-base 2.0.1 py310hb5e798b_1
[conda] pytorch-mutex 1.0 cpu pytorch
[conda] torch 2.4.1+cu118 pypi_0 pypi
[conda] torchaudio 2.4.1+cu118 pypi_0 pypi
[conda] torchvision 0.19.1+cu118 pypi_0 pypi
[conda] triton 3.0.0 pypi_0 pypi
[conda] triton-library 1.0.0rc4 pypi_0 pypi
Hi Chris,
When trying to train the model, I am getting the following error. No clue where to begin dealing with this CUDA error. Have you ever encountered this ?