Issue torch.cuda.mem_get_info runtime error: hip error: invalid argument

[zhangnju]

🐛 Describe the bug

try to run some pytorch codes on AMD mI210 GPU, but meet the below error

import torch
torch.cuda.mem_get_info(0)
Traceback (most recent call last):
File "", line 1, in
File "/home/zhangn/.local/lib/python3.10/site-packages/torch/cuda/memory.py", line 650, in mem_get_info
return torch.cuda.cudart().cudaMemGetInfo(device)
RuntimeError: HIP error: invalid argument
HIP kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing AMD_SERIALIZE_KERNEL=3
Compile with TORCH_USE_HIP_DSA to enable device-side assertions.

torch.cuda.is_available()
True
torch.cuda.current_device()
0
torch.cuda.get_device_name()
'AMD Instinct MI210'
torch.cuda.get_device_capability()
(9, 0)
torch.cuda.device_count()
1

Versions

Collecting environment information...
PyTorch version: 2.4.0.dev20240511+rocm6.0
Is debug build: False
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: 6.0.32830-d62f6a171

OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: version 3.16.3
Libc version: glibc-2.31

Python version: 3.10.14 (main, Apr 6 2024, 18:45:05) [GCC 9.4.0] (64-bit runtime)
Python platform: Linux-5.15.0-102-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: AMD Instinct MI210 (gfx90a:sramecc+:xnack-)
Nvidia driver version: Could not collect
cuDNN version: Could not collect
HIP runtime version: 6.0.32830
MIOpen runtime version: 3.0.0
Is XNNPACK available: True

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
Address sizes: 52 bits physical, 57 bits virtual
CPU(s): 384
On-line CPU(s) list: 0-383
Thread(s) per core: 2
Core(s) per socket: 96
Socket(s): 2
NUMA node(s): 2
Vendor ID: AuthenticAMD
CPU family: 25
Model: 17
Model name: AMD EPYC 9654 96-Core Processor
Stepping: 1
Frequency boost: enabled
CPU MHz: 1500.000
CPU max MHz: 3707.8120
CPU min MHz: 1500.0000
BogoMIPS: 4792.30
Virtualization: AMD-V
L1d cache: 6 MiB
L1i cache: 6 MiB
L2 cache: 192 MiB
L3 cache: 768 MiB
NUMA node0 CPU(s): 0-95,192-287
NUMA node1 CPU(s): 96-191,288-383
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: Mitigation; safe RET
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Retpolines, IBPB conditional, IBRS_FW, STIBP always-on, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 invpcid_single hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local avx512_bf16 clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin cppc arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid overflow_recov succor smca fsrm flush_l1d

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] pytorch-triton-rocm==3.0.0+bbe6246e37
[pip3] torch==2.4.0.dev20240511+rocm6.0
[pip3] torchaudio==2.2.0.dev20240511+rocm6.0
[pip3] torchsde==0.2.6
[pip3] torchvision==0.19.0.dev20240511+rocm6.0
[conda] Could not collect

cc @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang

[jeffdaily]

What is your ROCm KFD version? Is it also ROCm 6.0? Or are you running inside a docker container with a newer version of ROCm inside the container versus what is on bare metal?

[zhangnju]

after further debugging, this issue was caused by system settings, nothing to do with pytorch. let me close it

[CrimsonDump]

after further debugging, this issue was caused by system settings, nothing to do with pytorch. let me close it

Hi I met the same problem with the same MI210, can you share about your true reasons ?