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Python: 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11.2.0]
CUDA available: True
GPU 0,1,2: CUDA GPU
GPU 0,1,2 Compute Capability: 8.0
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 11.8, V11.8.89
CUDA Driver Version: 535.54.03
PyTorch: 2.5.1+cu124
sglang: 0.4.0
flashinfer: 0.1.6+cu121torch2.4
triton: 3.1.0
transformers: 4.48.0
torchao: 0.6.1
numpy: 1.26.4
aiohttp: 3.11.8
fastapi: 0.115.5
hf_transfer: 0.1.8
huggingface_hub: 0.27.0
interegular: 0.3.3
modelscope: 1.20.1
orjson: 3.10.12
packaging: 24.2
psutil: 6.1.0
pydantic: 2.10.4
multipart: 0.0.17
zmq: 26.2.0
uvicorn: 0.32.1
uvloop: 0.21.0
vllm: 0.6.4.post1
openai: 1.58.1
anthropic: Module Not Found
decord: 0.6.0
NVIDIA Topology:
GPU0 GPU1 GPU2 NIC0 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X PIX NODE SYS 1,3,5,7,9,11 1 N/A
GPU1 PIX X NODE SYS 1,3,5,7,9,11 1 N/A
GPU2 NODE NODE X SYS 1,3,5,7,9,11 1 N/A
NIC0 SYS SYS 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: 1048576
The text was updated successfully, but these errors were encountered:
Describe the bug
I attempted to serve the Phi-4 Lora Fine-tuning model by setting tensor parallel size 2 using the sglang framework, but the following error occurred.
Reproduction
Model Name: Microsoft Phi-4
nohup python -m sglang.launch_server --model-path /home/work/ai/Microsoft_Phi-4/phi-4_quantized_8bit --lora-paths lora=/home/work/ai/Microsoft_Phi-4/lora_tuning_1221 --port 8001 --mem-fraction-static 0.8 --host 0.0.0.0 --dtype auto --disable-radix-cache --disable-cuda-graph --quantization gptq_marlin --max-total-tokens 16384 --tp 2 &
Environment
Python: 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11.2.0]
CUDA available: True
GPU 0,1,2: CUDA GPU
GPU 0,1,2 Compute Capability: 8.0
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 11.8, V11.8.89
CUDA Driver Version: 535.54.03
PyTorch: 2.5.1+cu124
sglang: 0.4.0
flashinfer: 0.1.6+cu121torch2.4
triton: 3.1.0
transformers: 4.48.0
torchao: 0.6.1
numpy: 1.26.4
aiohttp: 3.11.8
fastapi: 0.115.5
hf_transfer: 0.1.8
huggingface_hub: 0.27.0
interegular: 0.3.3
modelscope: 1.20.1
orjson: 3.10.12
packaging: 24.2
psutil: 6.1.0
pydantic: 2.10.4
multipart: 0.0.17
zmq: 26.2.0
uvicorn: 0.32.1
uvloop: 0.21.0
vllm: 0.6.4.post1
openai: 1.58.1
anthropic: Module Not Found
decord: 0.6.0
NVIDIA Topology:
GPU0 GPU1 GPU2 NIC0 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X PIX NODE SYS 1,3,5,7,9,11 1 N/A
GPU1 PIX X NODE SYS 1,3,5,7,9,11 1 N/A
GPU2 NODE NODE X SYS 1,3,5,7,9,11 1 N/A
NIC0 SYS SYS 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: 1048576
The text was updated successfully, but these errors were encountered: