Closed
Description
Your current environment
==============================
System Info
==============================
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 3.29.3
Libc version : glibc-2.31
==============================
PyTorch Info
==============================
PyTorch version : 2.6.0+cu124
Is debug build : False
CUDA used to build PyTorch : 12.4
ROCM used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0] (64-bit runtime)
Python platform : Linux-3.10.0-1160.76.1.el7.x86_64-x86_64-with-glibc2.31
==============================
CUDA / GPU Info
==============================
Is CUDA available : True
CUDA runtime version : 12.1.105
CUDA_MODULE_LOADING set to : LAZY
GPU models and configuration :
GPU 0: NVIDIA A800-SXM4-80GB
GPU 1: NVIDIA A800-SXM4-80GB
GPU 2: NVIDIA A800-SXM4-80GB
GPU 3: NVIDIA A800-SXM4-80GB
GPU 4: NVIDIA A800-SXM4-80GB
GPU 5: NVIDIA A800-SXM4-80GB
GPU 6: NVIDIA A800-SXM4-80GB
GPU 7: NVIDIA A800-SXM4-80GB
Nvidia driver version : 550.54.14
cuDNN version : Could not collect
HIP runtime version : N/A
MIOpen runtime version : N/A
Is XNNPACK available : True
==============================
CPU Info
==============================
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Byte Order: Little Endian
Address sizes: 46 bits physical, 57 bits virtual
CPU(s): 128
On-line CPU(s) list: 0-127
Thread(s) per core: 2
Core(s) per socket: 32
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 106
Model name: Intel(R) Xeon(R) Platinum 8350C CPU @ 2.60GHz
Stepping: 6
Frequency boost: enabled
CPU MHz: 2601.000
CPU max MHz: 2601.0000
CPU min MHz: 800.0000
BogoMIPS: 5200.00
Virtualization: VT-x
GPU4 NV8 NV8 NV8 NV8 X NV8 NV8 NV8 SYS SYS SYS SYS PXB PXB SYS SYS 32-63,96-127 1 N/A
GPU5 NV8 NV8 NV8 NV8 NV8 X NV8 NV8 SYS SYS SYS SYS PXB PXB SYS SYS 32-63,96-127 1 N/A
GPU6 NV8 NV8 NV8 NV8 NV8 NV8 X NV8 SYS SYS SYS SYS SYS SYS PXB PXB 32-63,96-127 1 N/A
GPU7 NV8 NV8 NV8 NV8 NV8 NV8 NV8 X SYS SYS SYS SYS SYS SYS PXB PXB 32-63,96-127 1 N/A
NIC0 PXB PXB SYS SYS SYS SYS SYS SYS X PIX SYS SYS SYS SYS SYS SYS
NIC1 PXB PXB SYS SYS SYS SYS SYS SYS PIX X SYS SYS SYS SYS SYS SYS
NIC2 SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS X PIX SYS SYS SYS SYS
NIC3 SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS PIX X SYS SYS SYS SYS
NIC4 SYS SYS SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS X PIX SYS SYS
NIC5 SYS SYS SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS PIX X SYS SYS
NIC6 SYS SYS SYS SYS SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS X PIX
NIC7 SYS SYS SYS SYS SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS PIX X
Legend:
X = Self
SYS = Connection traversing PCIe as well as the SMP interconnect between NUMA nodes (e.g., QPI/UPI)
NODE = Connection traversing PCIe as well as the interconnect between PCIe Host Bridges within a NUMA node
PHB = Connection traversing PCIe as well as a PCIe Host Bridge (typically the CPU)
PXB = Connection traversing multiple PCIe bridges (without traversing the PCIe Host Bridge)
PIX = Connection traversing at most a single PCIe bridge
NV# = Connection traversing a bonded set of # NVLinks
NIC Legend:
NIC0: mlx5_0
NIC1: mlx5_1
NIC2: mlx5_2
NIC3: mlx5_3
NIC4: mlx5_4
NIC5: mlx5_5
NIC6: mlx5_6
NIC7: mlx5_7
==============================
Environment Variables
==============================
NVIDIA_VISIBLE_DEVICES=all
NVIDIA_REQUIRE_CUDA=cuda>=12.1 brand=tesla,driver>=470,driver<471 brand=unknown,driver>=470,driver<471 brand=nvidia,driver>=470,driver<471 brand=nvidiartx,driver>=470,driver<471 brand=geforce,driver>=470,driver<471 brand=geforcertx,driver>=470,driver<471 brand=quadro,driver>=470,driver<471 brand=quadrortx,driver>=470,driver<471 brand=titan,driver>=470,driver<471 brand=titanrtx,driver>=470,driver<471 brand=tesla,driver>=525,driver<526 brand=unknown,driver>=525,driver<526 brand=nvidia,driver>=525,driver<526 brand=nvidiartx,driver>=525,driver<526 brand=geforce,driver>=525,driver<526 brand=geforcertx,driver>=525,driver<526 brand=quadro,driver>=525,driver<526 brand=quadrortx,driver>=525,driver<526 brand=titan,driver>=525,driver<526 brand=titanrtx,driver>=525,driver<526
NCCL_VERSION=2.17.1-1
NVIDIA_DRIVER_CAPABILITIES=compute,utility
NVIDIA_PRODUCT_NAME=CUDA
NVIDIA_CUDA_END_OF_LIFE=1
CUDA_VERSION=12.1.0
LD_LIBRARY_PATH=/usr/local/cuda/lib64:/usr/lib/x86_64-linux-gnu:/usr/local/openmpi/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
NCCL_CUMEM_ENABLE=0
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
CUDA_MODULE_LOADING=LAZY
🐛 Describe the bug
I try to evaluate Qwen3-30B-A3B with vllm, but even i set the os.environ["VLLM_ENABLE_V1_MULTIPROCESSING"] = "0"
and set other seed like
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
os.environ['PYTHONHASHSEED'] = str(seed)
os.environ['CUBLAS_WORKSPACE_CONFIG'] = ':4096:8'
torch.cuda.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False
And evaluate with:
llm = LLM(model=model_path,tensor_parallel_size=8, seed=42,enable_prefix_caching=False)
self.sampling_params = SamplingParams(temperature=0.0,
max_tokens=max_gen_tokens, stop=self.stop,skip_special_tokens=False,spaces_between_special_tokens=False,seed=42)
# pickup output for metric calculate
output = self.llm.generate(prompt_token_ids=context_encoding,sampling_params=self.sampling_params,use_tqdm=False)
Every time, when i reboot the docker container, I received different result, I was wondering what else can i do to make the result the same
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