当前环境

Collecting environment information...
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WARNING 06-30 12:42:35 _custom_ops.py:14] Failed to import from vllm._C with ModuleNotFoundError("No module named 'vllm._C'")
PyTorch version: 2.5.0.dev20240613+rocm6.1
Is debug build: False
CUDA used to build PyTorch: N/A
ROCM used to build PyTorch: 6.1.40091-a8dbc0c19

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.29.5
Libc version: glibc-2.35

Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.15.0-113-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: AMD Instinct MI100 (gfx908:sramecc+:xnack-)
Nvidia driver version: Could not collect
cuDNN version: Could not collect
HIP runtime version: 6.1.40091
MIOpen runtime version: 3.1.0
Is XNNPACK available: True

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      43 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             16
On-line CPU(s) list:                0-15
Vendor ID:                          AuthenticAMD
Model name:                         AMD EPYC 7282 16-Core Processor
CPU family:                         23
Model:                              49
Thread(s) per core:                 1
Core(s) per socket:                 16
Socket(s):                          1
Stepping:                           0
Frequency boost:                    enabled
CPU max MHz:                        2800.0000
CPU min MHz:                        1500.0000
BogoMIPS:                           5600.24
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 sse4_1 sse4_2 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 hw_pstate ssbd mba ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
Virtualization:                     AMD-V
L1d cache:                          512 KiB (16 instances)
L1i cache:                          512 KiB (16 instances)
L2 cache:                           8 MiB (16 instances)
L3 cache:                           64 MiB (4 instances)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-15
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:             Mitigation; untrained return thunk; SMT disabled
Vulnerability Spec rstack overflow: Mitigation; SMT disabled
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; STIBP disabled; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] libtorch==1.2.0.1
[pip3] numpy==1.26.4
[pip3] pytorch-triton-rocm==3.0.0+01cbe5045a
[pip3] torch==2.5.0.dev20240613+rocm6.1
[pip3] torchaudio==2.4.0.dev20240614+rocm6.1
[pip3] torchvision==0.19.0.dev20240614+rocm6.1
[pip3] transformers==4.41.2
[pip3] triton==2.1.0
[conda] Could not collect
ROCM Version: 6.1.40093-bd86f1708
Neuron SDK Version: N/A
vLLM Version: 0.5.0.post1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
Could not collect

🐛 描述bug

我使用了这个Docker:https://hub.docker.com/r/eliovp/rocm6.1.2_py3.10_torch2.5_vllm0.5_bkc,并搭配MI100。但是我总是遇到这个问题：
"""
Traceback (most recent call last):
File "", line 1, in
File "/usr/local/lib/python3.10/dist-packages/torch/cuda/memory.py", line 685, in mem_get_info
return torch.cuda.cudart().cudaMemGetInfo(device)
RuntimeError: HIP error: invalid argument
HIP内核错误可能会在其他API调用中异步报告，因此下面的堆栈跟踪可能不正确。
为了调试，请考虑传递AMD_SERIALIZE_KERNEL=3。
使用TORCH_USE_HIP_DSA编译以启用设备端Assert。
"""