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[Bug]: Hermes tool choice can not supprot format 'string' #11250

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warlockedward opened this issue Dec 17, 2024 · 7 comments
Open
1 task done

[Bug]: Hermes tool choice can not supprot format 'string' #11250

warlockedward opened this issue Dec 17, 2024 · 7 comments
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bug Something isn't working

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@warlockedward
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Your current environment

The output of `python collect_env.py` 
Collecting environment information...
PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

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: Could not collect
Libc version: glibc-2.35

Python version: 3.11.9 (main, Apr 19 2024, 16:48:06) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-124-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: Tesla V100-SXM2-32GB
GPU 1: Tesla V100-SXM2-32GB
GPU 2: Tesla V100-SXM2-32GB
GPU 3: Tesla V100-SXM2-32GB
GPU 4: Tesla V100-SXM2-32GB
GPU 5: Tesla V100-SXM2-32GB
GPU 6: Tesla V100-SXM2-32GB
GPU 7: Tesla V100-SXM2-32GB

Nvidia driver version: 550.120
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.2.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture:                         x86_64
CPU op-mode(s):                       32-bit, 64-bit
Address sizes:                        46 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               96
On-line CPU(s) list:                  0-95
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) Gold 6271C CPU @ 2.60GHz
CPU family:                           6
Model:                                85
Thread(s) per core:                   2
Core(s) per socket:                   24
Socket(s):                            2
Stepping:                             7
BogoMIPS:                             5200.00
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp_epp pku ospke avx512_vnni md_clear flush_l1d arch_capabilities
Virtualization:                       VT-x
L1d cache:                            1.5 MiB (48 instances)
L1i cache:                            1.5 MiB (48 instances)
L2 cache:                             48 MiB (48 instances)
L3 cache:                             66 MiB (2 instances)
NUMA node(s):                         2
NUMA node0 CPU(s):                    0-23,48-71
NUMA node1 CPU(s):                    24-47,72-95
Vulnerability Gather data sampling:   Mitigation; Microcode
Vulnerability Itlb multihit:          KVM: Mitigation: VMX disabled
Vulnerability L1tf:                   Not affected
Vulnerability Mds:                    Not affected
Vulnerability Meltdown:               Not affected
Vulnerability Mmio stale data:        Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow:   Not affected
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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Mitigation; TSX disabled

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-ml-py==12.560.30
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pyzmq==26.2.0
[pip3] torch==2.5.1
[pip3] torchvision==0.20.1
[pip3] transformers==4.46.2
[pip3] triton==3.1.0
[conda] numpy                     1.26.4                   pypi_0    pypi
[conda] nvidia-cublas-cu12        12.4.5.8                 pypi_0    pypi
[conda] nvidia-cuda-cupti-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-nvrtc-cu12    12.4.127                 pypi_0    pypi
[conda] nvidia-cuda-runtime-cu12  12.4.127                 pypi_0    pypi
[conda] nvidia-cudnn-cu12         9.1.0.70                 pypi_0    pypi
[conda] nvidia-cufft-cu12         11.2.1.3                 pypi_0    pypi
[conda] nvidia-curand-cu12        10.3.5.147               pypi_0    pypi
[conda] nvidia-cusolver-cu12      11.6.1.9                 pypi_0    pypi
[conda] nvidia-cusparse-cu12      12.3.1.170               pypi_0    pypi
[conda] nvidia-ml-py              12.560.30                pypi_0    pypi
[conda] nvidia-nccl-cu12          2.21.5                   pypi_0    pypi
[conda] nvidia-nvjitlink-cu12     12.4.127                 pypi_0    pypi
[conda] nvidia-nvtx-cu12          12.4.127                 pypi_0    pypi
[conda] pyzmq                     26.2.0                   pypi_0    pypi
[conda] torch                     2.5.1                    pypi_0    pypi
[conda] torchvision               0.20.1                   pypi_0    pypi
[conda] transformers              4.46.2                   pypi_0    pypi
[conda] triton                    3.1.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.3.post2.dev338+gf0f2e563
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    GPU1    GPU2    GPU3    GPU4    GPU5    GPU6    GPU7    NIC0    NIC1    NIC2    NIC3    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV1     NV2     NV1     SYS     SYS     SYS     NV2     NODE    NODE    SYS     SYS     0-23,48-71      0               N/A
GPU1    NV1      X      NV1     NV2     SYS     SYS     NV2     SYS     NODE    NODE    SYS     SYS     0-23,48-71      0               N/A
GPU2    NV2     NV1      X      NV2     SYS     NV1     SYS     SYS     PIX     PIX     SYS     SYS     0-23,48-71      0               N/A
GPU3    NV1     NV2     NV2      X      NV1     SYS     SYS     SYS     PIX     PIX     SYS     SYS     0-23,48-71      0               N/A
GPU4    SYS     SYS     SYS     NV1      X      NV2     NV2     NV1     SYS     SYS     PIX     PIX     24-47,72-95     1               N/A
GPU5    SYS     SYS     NV1     SYS     NV2      X      NV1     NV2     SYS     SYS     PIX     PIX     24-47,72-95     1               N/A
GPU6    SYS     NV2     SYS     SYS     NV2     NV1      X      NV1     SYS     SYS     NODE    NODE    24-47,72-95     1               N/A
GPU7    NV2     SYS     SYS     SYS     NV1     NV2     NV1      X      SYS     SYS     NODE    NODE    24-47,72-95     1               N/A
NIC0    NODE    NODE    PIX     PIX     SYS     SYS     SYS     SYS      X      PIX     SYS     SYS
NIC1    NODE    NODE    PIX     PIX     SYS     SYS     SYS     SYS     PIX      X      SYS     SYS
NIC2    SYS     SYS     SYS     SYS     PIX     PIX     NODE    NODE    SYS     SYS      X      PIX
NIC3    SYS     SYS     SYS     SYS     PIX     PIX     NODE    NODE    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

NCCL_P2P_DISABLE=0
VLLM_WORKER_MULTIPROC_METHOD=spawn
NCCL_NSOCKS_PERTHREAD=2
NCCL_SOCKET_NTHREADS=2
LD_LIBRARY_PATH=/model/anaconda3/envs/vllm/lib/python3.11/site-packages/cv2/../../lib64:/usr/local/cuda-12.4/lib64${LD_LIBRARY_PATH:+:}
NCCL_CROSS_NIC=0
CUDA_MODULE_LOADING=LAZY

Model Input Dumps

vllm serve /model/models/calme-3.2-instruct-78b/ --guided-decoding-backend xgrammar --block-size 32 --max-num-seqs 100 --port xxxxxxxxxx --api-key xxxxxxxxxxxxxxxx -tp 8 --served-model-name Qwen2.5-72B-Instruct --dtype float16 --max-model-len 65536 --enable-chunked-prefill false --seed 818 --multi-step-stream-outputs true --enable-auto-tool-choice --tool-call-parser hermes --tokenizer-pool-size 50

🐛 Describe the bug

INFO 12-17 04:39:28 llm_engine.py:446] init engine (profile, create kv cache, warmup model) took 119.34 seconds
INFO 12-17 04:39:28 api_server.py:578] Using supplied chat template:
INFO 12-17 04:39:28 api_server.py:578] None
INFO 12-17 04:39:28 serving_chat.py:74] "auto" tool choice has been enabled please note that while the parallel_tool_calls client option is preset for compatibility reasons, it will be ignored.
INFO 12-17 04:39:28 launcher.py:19] Available routes are:
INFO 12-17 04:39:28 launcher.py:27] Route: /openapi.json, Methods: GET, HEAD
INFO 12-17 04:39:28 launcher.py:27] Route: /docs, Methods: GET, HEAD
INFO 12-17 04:39:28 launcher.py:27] Route: /docs/oauth2-redirect, Methods: GET, HEAD
INFO 12-17 04:39:28 launcher.py:27] Route: /redoc, Methods: GET, HEAD
INFO 12-17 04:39:28 launcher.py:27] Route: /health, Methods: GET
INFO 12-17 04:39:28 launcher.py:27] Route: /tokenize, Methods: POST
INFO 12-17 04:39:28 launcher.py:27] Route: /detokenize, Methods: POST
INFO 12-17 04:39:28 launcher.py:27] Route: /v1/models, Methods: GET
INFO 12-17 04:39:28 launcher.py:27] Route: /version, Methods: GET
INFO 12-17 04:39:28 launcher.py:27] Route: /v1/chat/completions, Methods: POST
INFO 12-17 04:39:28 launcher.py:27] Route: /v1/completions, Methods: POST
INFO 12-17 04:39:28 launcher.py:27] Route: /v1/embeddings, Methods: POST
INFO 12-17 04:39:28 launcher.py:27] Route: /score, Methods: POST
INFO 12-17 04:39:28 launcher.py:27] Route: /v1/score, Methods: POST
INFO: Started server process [2694250]
INFO: Waiting for application startup.
INFO: Application startup complete.
INFO: Uvicorn running on http://0.0.0.0:xxxxxxxxxxxx (Press CTRL+C to quit)
INFO 12-17 04:39:51 chat_utils.py:331] Detected the chat template content format to be 'string'. You can set --chat-template-content-format to override this.
INFO: 192.254.90.4:56388 - "POST /v1/chat/completions HTTP/1.1" 500 Internal Server Error
INFO: 192.254.90.4:56388 - "POST /v1/chat/completions HTTP/1.1" 500 Internal Server Error
INFO: 192.254.90.4:56388 - "POST /v1/chat/completions HTTP/1.1" 500 Internal Server Error

This is a fine-tuned model based on Qwen 2.5-72B, which is currently ranked #1 on huggingface, I would like to use it, but I found that an exception occurs in the handling of tool choice, I tried contacting the author of the big model, and it told me that this model supports Hermes's chat-template format, but I found that after running the VLLM I got this error warning, I also tried to use the --chat-template-content-format string method but it still failed, I hope to get help, thanks a lot!
The big model author replied to me with the link: https://huggingface.co/MaziyarPanahi/calme-3.2-instruct-78b/discussions/8

Translated with DeepL.com (free version)

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@warlockedward warlockedward added the bug Something isn't working label Dec 17, 2024
@DarkLight1337
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Can you show the error log?

@warlockedward
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Can you show the error log?

I use the export VLLM_TRACE_FUNCTION=1 and export VLLM_LOGGING_LEVEL=DEBUG parameter, but found that the function call does not have any error message, but Tool choice just suggests that the error is unavailable

@DarkLight1337
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Do you get a similar issue in the latest release version of vLLM? (v0.6.4)

@warlockedward
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Do you get a similar issue in the latest release version of vLLM? (v0.6.4)

I am using v0.6.4.post1

@DarkLight1337
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The output of collect_env.py suggests that you're using vLLM Version: 0.6.3.post2.dev338+gf0f2e563

@warlockedward
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的输出collect_env.py表明你正在使用vLLM Version: 0.6.3.post2.dev338+gf0f2e563

My info grabbed the wrong machine, I'll reupload it

Collecting environment information...
PyTorch version: 2.5.1+cu124
Is debug build: False
CUDA used to build PyTorch: 12.4
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 12.3.0-1ubuntu1~22.04) 12.3.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.11.11 (main, Dec 11 2024, 16:28:39) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-124-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.4.131
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: Tesla V100-SXM2-32GB
GPU 1: Tesla V100-SXM2-32GB
GPU 2: Tesla V100-SXM2-32GB
GPU 3: Tesla V100-SXM2-32GB
GPU 4: Tesla V100-SXM2-32GB
GPU 5: Tesla V100-SXM2-32GB
GPU 6: Tesla V100-SXM2-32GB
GPU 7: Tesla V100-SXM2-32GB

Nvidia driver version: 550.120
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.2.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.2.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 96
On-line CPU(s) list: 0-95
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Gold 6271C CPU @ 2.60GHz
CPU family: 6
Model: 85
Thread(s) per core: 2
Core(s) per socket: 24
Socket(s): 2
Stepping: 7
BogoMIPS: 5200.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp_epp pku ospke avx512_vnni md_clear flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 1.5 MiB (48 instances)
L1i cache: 1.5 MiB (48 instances)
L2 cache: 48 MiB (48 instances)
L3 cache: 66 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-23,48-71
NUMA node1 CPU(s): 24-47,72-95
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Mitigation; Enhanced IBRS
Vulnerability Spec rstack overflow: Not affected
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; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; TSX disabled

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-ml-py==12.560.30
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pyzmq==26.2.0
[pip3] torch==2.5.1
[pip3] torchvision==0.20.1
[pip3] transformers==4.47.0
[pip3] triton==3.1.0
[conda] numpy 1.26.4 pypi_0 pypi
[conda] nvidia-cublas-cu12 12.4.5.8 pypi_0 pypi
[conda] nvidia-cuda-cupti-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cuda-nvrtc-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cuda-runtime-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-cudnn-cu12 9.1.0.70 pypi_0 pypi
[conda] nvidia-cufft-cu12 11.2.1.3 pypi_0 pypi
[conda] nvidia-curand-cu12 10.3.5.147 pypi_0 pypi
[conda] nvidia-cusolver-cu12 11.6.1.9 pypi_0 pypi
[conda] nvidia-cusparse-cu12 12.3.1.170 pypi_0 pypi
[conda] nvidia-ml-py 12.560.30 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.21.5 pypi_0 pypi
[conda] nvidia-nvjitlink-cu12 12.4.127 pypi_0 pypi
[conda] nvidia-nvtx-cu12 12.4.127 pypi_0 pypi
[conda] pyzmq 26.2.0 pypi_0 pypi
[conda] torch 2.5.1 pypi_0 pypi
[conda] torchvision 0.20.1 pypi_0 pypi
[conda] transformers 4.47.0 pypi_0 pypi
[conda] triton 3.1.0 pypi_0 pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.6.4.post2.dev390+g0064f697d
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 NIC1 NIC2 NIC3 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X NV1 NV2 NV1 SYS SYS SYS NV2 NODE NODE SYS SYS 0-23,48-71 0 N/A
GPU1 NV1 X NV1 NV2 SYS SYS NV2 SYS NODE NODE SYS SYS 0-23,48-71 0 N/A
GPU2 NV2 NV1 X NV2 SYS NV1 SYS SYS PIX PIX SYS SYS 0-23,48-71 0 N/A
GPU3 NV1 NV2 NV2 X NV1 SYS SYS SYS PIX PIX SYS SYS 0-23,48-71 0 N/A
GPU4 SYS SYS SYS NV1 X NV2 NV2 NV1 SYS SYS PIX PIX 24-47,72-95 1 N/A
GPU5 SYS SYS NV1 SYS NV2 X NV1 NV2 SYS SYS PIX PIX 24-47,72-95 1 N/A
GPU6 SYS NV2 SYS SYS NV2 NV1 X NV1 SYS SYS NODE NODE 24-47,72-95 1 N/A
GPU7 NV2 SYS SYS SYS NV1 NV2 NV1 X SYS SYS NODE NODE 24-47,72-95 1 N/A
NIC0 NODE NODE PIX PIX SYS SYS SYS SYS X PIX SYS SYS
NIC1 NODE NODE PIX PIX SYS SYS SYS SYS PIX X SYS SYS
NIC2 SYS SYS SYS SYS PIX PIX NODE NODE SYS SYS X PIX
NIC3 SYS SYS SYS SYS PIX PIX NODE NODE 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

NCCL_P2P_DISABLE=1
VLLM_WORKER_MULTIPROC_METHOD=spawn
NCCL_NSOCKS_PERTHREAD=2
NCCL_SOCKET_NTHREADS=2
LD_LIBRARY_PATH=/model/anaconda3/envs/vllm/lib/python3.11/site-packages/cv2/../../lib64:/usr/local/cuda-12.4/lib64${LD_LIBRARY_PATH:+:}
NCCL_CROSS_NIC=0
CUDA_MODULE_LOADING=LAZY

@DarkLight1337
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Thanks for providing this info!

@K-Mistele can you help look into this?

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@warlockedward @DarkLight1337 and others