Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[Bug] Seeing random output with nvidia/Llama-3.1-Nemotron-70B-Reward #1931

Open
5 tasks done
pgimenes opened this issue Nov 5, 2024 · 0 comments
Open
5 tasks done

Comments

@pgimenes
Copy link

pgimenes commented Nov 5, 2024

Checklist

  • 1. I have searched related issues but cannot get the expected help.
  • 2. The bug has not been fixed in the latest version.
  • 3. Please note that if the bug-related issue you submitted lacks corresponding environment info and a minimal reproducible demo, it will be challenging for us to reproduce and resolve the issue, reducing the likelihood of receiving feedback.
  • 4. If the issue you raised is not a bug but a question, please raise a discussion at https://github.com/sgl-project/sglang/discussions/new/choose Otherwise, it will be closed.
  • 5. Please use English, otherwise it will be closed.

Describe the bug

I am trying to run the basic setup example with the nvidia/Llama-3.1-Nemotron-70B-Reward on a machine with 8 A6000s, but the observed output is random.

Generated output:

{"text":"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"\"","meta_info":{"prompt_tokens":6,"completion_tokens":16,"completion_tokens_wo_jump_forward":16,"cached_tokens":1,"finish_reason"{"type":"length","length":16},"id":"a3101b373bcd4fb8beab6f42e74efd53"}

Reproduction

Server side:

python -m sglang.launch_server --model-path nvidia/Llama-3.1-Nemotron-70B-Reward-HF --port 30000 --tp 8

Client side:

curl http://localhost:30000/generate \
  -H "Content-Type: application/json" \
  -d '{
    "text": "Once upon a time,",
    "sampling_params": {
      "max_new_tokens": 16,
      "temperature": 0
    }
  }'

Environment

Python: 3.11.9 (main, Apr 19 2024, 16:48:06) [GCC 11.2.0]
CUDA available: True
GPU 0,1,2,3,4,5,6,7: NVIDIA RTX A6000
GPU 0,1,2,3,4,5,6,7 Compute Capability: 8.6
CUDA_HOME: /usr
NVCC: Cuda compilation tools, release 11.5, V11.5.119
CUDA Driver Version: 550.54.15
PyTorch: 2.4.0+cu121
sglang: 0.3.5
flashinfer: 0.1.6+cu121torch2.4
triton: 3.0.0
transformers: 4.46.1
requests: 2.32.3
tqdm: 4.66.6
numpy: 1.26.4
aiohttp: 3.10.10
fastapi: 0.115.4
hf_transfer: 0.1.8
huggingface_hub: 0.26.2
interegular: 0.3.3
packaging: 24.1
PIL: 10.4.0
psutil: 6.1.0
pydantic: 2.9.2
uvicorn: 0.32.0
uvloop: 0.21.0
zmq: 26.2.0
vllm: 0.6.3.post1
multipart: 0.0.17
openai: 1.54.1
anthropic: 0.39.0
NVIDIA Topology:
GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X SYS SYS SYS SYS SYS SYS SYS SYS 0-63,128-191 0 N/A
GPU1 SYS X SYS SYS SYS SYS SYS SYS SYS 0-63,128-191 0 N/A
GPU2 SYS SYS X SYS SYS SYS SYS SYS SYS 0-63,128-191 0 N/A
GPU3 SYS SYS SYS X SYS SYS SYS SYS SYS 0-63,128-191 0 N/A
GPU4 SYS SYS SYS SYS X SYS SYS SYS SYS 64-127,192-255 1 N/A
GPU5 SYS SYS SYS SYS SYS X SYS SYS SYS 64-127,192-255 1 N/A
GPU6 SYS SYS SYS SYS SYS SYS X SYS PHB 64-127,192-255 1 N/A
GPU7 SYS SYS SYS SYS SYS SYS SYS X SYS 64-127,192-255 1 N/A
NIC0 SYS SYS SYS SYS SYS SYS PHB SYS 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

ulimit soft: 4096

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant