[Bug]: RuntimeError: Worker failed with error 'DeepGEMM backend is not available or outdated.' When deploy DeepSeek-V3.2 #29946
Description
Your current environment
vllm v0.11.2, but add customized DeepSeekV32Tokenizer (like #29837, but with some modifications try to get work on v0.11.2).
The output of python collect_env.py
Collecting environment information...
==============================
System Info
==============================
OS : Ubuntu 22.04.3 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
==============================
PyTorch Info
==============================
PyTorch version : 2.9.0+cu128
Is debug build : False
CUDA used to build PyTorch : 12.8
ROCM used to build PyTorch : N/A
==============================
Python Environment
==============================
Python version : 3.12.9 | packaged by Anaconda, Inc. | (main, Feb 6 2025, 18:56:27) [GCC 11.2.0] (64-bit runtime)
Python platform : Linux-6.8.0-57-generic-x86_64-with-glibc2.35
==============================
CUDA / GPU Info
==============================
Is CUDA available : True
CUDA runtime version : 12.8.93
CUDA_MODULE_LOADING set to :
GPU models and configuration :
GPU 0: NVIDIA H20-3e
GPU 1: NVIDIA H20-3e
GPU 2: NVIDIA H20-3e
GPU 3: NVIDIA H20-3e
GPU 4: NVIDIA H20-3e
GPU 5: NVIDIA H20-3e
GPU 6: NVIDIA H20-3e
GPU 7: NVIDIA H20-3e
Nvidia driver version : 570.124.06
cuDNN version : Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.8.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.8.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.8.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.8.0
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.8.0
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.8.0
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.8.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.8.0
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
Address sizes: 52 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 192
On-line CPU(s) list: 0-191
Vendor ID: GenuineIntel
Model name: INTEL(R) XEON(R) PLATINUM 8558
CPU family: 6
Model: 207
Thread(s) per core: 2
Core(s) per socket: 48
Socket(s): 2
Stepping: 2
CPU max MHz: 4000.0000
CPU min MHz: 800.0000
BogoMIPS: 4200.00
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 tsc_known_freq pni pclmulqdq dtes64 monitor 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 cat_l2 cdp_l3 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 4.5 MiB (96 instances)
L1i cache: 3 MiB (96 instances)
L2 cache: 192 MiB (96 instances)
L3 cache: 520 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-47,96-143
NUMA node1 CPU(s): 48-95,144-191
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 Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
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 BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
==============================
Versions of relevant libraries
==============================
[pip3] flashinfer-python==0.5.2
[pip3] numpy==1.26.4
[pip3] nvidia-cublas-cu12==12.8.4.1
[pip3] nvidia-cuda-cupti-cu12==12.8.90
[pip3] nvidia-cuda-nvrtc-cu12==12.8.93
[pip3] nvidia-cuda-runtime-cu12==12.8.90
[pip3] nvidia-cudnn-cu12==9.10.2.21
[pip3] nvidia-cudnn-frontend==1.16.0
[pip3] nvidia-cufft-cu12==11.3.3.83
[pip3] nvidia-cufile-cu12==1.13.1.3
[pip3] nvidia-curand-cu12==10.3.9.90
[pip3] nvidia-cusolver-cu12==11.7.3.90
[pip3] nvidia-cusparse-cu12==12.5.8.93
[pip3] nvidia-cusparselt-cu12==0.7.1
[pip3] nvidia-cutlass-dsl==4.3.0
[pip3] nvidia-ml-py==13.580.82
[pip3] nvidia-nccl-cu12==2.27.5
[pip3] nvidia-nvjitlink-cu12==12.8.93
[pip3] nvidia-nvshmem-cu12==3.3.20
[pip3] nvidia-nvtx-cu12==12.8.90
[pip3] pyzmq==26.3.0
[pip3] torch==2.9.0
[pip3] torchaudio==2.9.0
[pip3] torchvision==0.24.0
[pip3] transformers==4.57.2
[pip3] triton==3.5.0
[conda] flashinfer-python 0.5.2 pypi_0 pypi
[conda] numpy 1.26.4 pypi_0 pypi
[conda] nvidia-cublas-cu12 12.8.4.1 pypi_0 pypi
[conda] nvidia-cuda-cupti-cu12 12.8.90 pypi_0 pypi
[conda] nvidia-cuda-nvrtc-cu12 12.8.93 pypi_0 pypi
[conda] nvidia-cuda-runtime-cu12 12.8.90 pypi_0 pypi
[conda] nvidia-cudnn-cu12 9.10.2.21 pypi_0 pypi
[conda] nvidia-cudnn-frontend 1.16.0 pypi_0 pypi
[conda] nvidia-cufft-cu12 11.3.3.83 pypi_0 pypi
[conda] nvidia-cufile-cu12 1.13.1.3 pypi_0 pypi
[conda] nvidia-curand-cu12 10.3.9.90 pypi_0 pypi
[conda] nvidia-cusolver-cu12 11.7.3.90 pypi_0 pypi
[conda] nvidia-cusparse-cu12 12.5.8.93 pypi_0 pypi
[conda] nvidia-cusparselt-cu12 0.7.1 pypi_0 pypi
[conda] nvidia-cutlass-dsl 4.3.0 pypi_0 pypi
[conda] nvidia-ml-py 13.580.82 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.27.5 pypi_0 pypi
[conda] nvidia-nvjitlink-cu12 12.8.93 pypi_0 pypi
[conda] nvidia-nvshmem-cu12 3.3.20 pypi_0 pypi
[conda] nvidia-nvtx-cu12 12.8.90 pypi_0 pypi
[conda] pyzmq 26.3.0 pypi_0 pypi
[conda] torch 2.9.0 pypi_0 pypi
[conda] torchaudio 2.9.0 pypi_0 pypi
[conda] torchvision 0.24.0 pypi_0 pypi
[conda] transformers 4.57.2 pypi_0 pypi
[conda] triton 3.5.0 pypi_0 pypi
==============================
vLLM Info
==============================
ROCM Version : Could not collect
vLLM Version : 0.11.2
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled
GPU Topology:
GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 NIC1 NIC2 NIC3 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X NV18 NV18 NV18 NV18 NV18 NV18 NV18 NODE NODE SYS SYS 0-47,96-143 0 N/A
GPU1 NV18 X NV18 NV18 NV18 NV18 NV18 NV18 NODE NODE SYS SYS 0-47,96-143 0 N/A
GPU2 NV18 NV18 X NV18 NV18 NV18 NV18 NV18 NODE NODE SYS SYS 0-47,96-143 0 N/A
GPU3 NV18 NV18 NV18 X NV18 NV18 NV18 NV18 NODE NODE SYS SYS 0-47,96-143 0 N/A
GPU4 NV18 NV18 NV18 NV18 X NV18 NV18 NV18 SYS SYS NODE NODE 48-95,144-191 1 N/A
GPU5 NV18 NV18 NV18 NV18 NV18 X NV18 NV18 SYS SYS NODE NODE 48-95,144-191 1 N/A
GPU6 NV18 NV18 NV18 NV18 NV18 NV18 X NV18 SYS SYS NODE NODE 48-95,144-191 1 N/A
GPU7 NV18 NV18 NV18 NV18 NV18 NV18 NV18 X SYS SYS NODE NODE 48-95,144-191 1 N/A
NIC0 NODE NODE NODE NODE SYS SYS SYS SYS X PIX SYS SYS
NIC1 NODE NODE NODE NODE SYS SYS SYS SYS PIX X SYS SYS
NIC2 SYS SYS SYS SYS NODE NODE NODE NODE SYS SYS X PIX
NIC3 SYS SYS SYS SYS NODE NODE 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
==============================
Environment Variables
==============================
LD_LIBRARY_PATH=/usr/local/cuda/bin
PYTORCH_NVML_BASED_CUDA_CHECK=1
TORCHINDUCTOR_COMPILE_THREADS=1
🐛 Describe the bug
I am trying to deploy DeepSeek-V3.2.
But without a default chat template, I have to customized a tokenizer based on vllm==v0.11.2，like #29837 did.
The porting of DeepSeekV32Tokenizer was completed quickly, and the model and tokenizer loaded successfully using the startup command below:
CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 VLLM_USE_V1=1 VLLM_WORKER_MULTIPROC_METHOD=spawn python -m vllm.entrypoints.openai.api_server \
--served-model-name DeepSeek-V3.2 \
--model /nvme0/ai_models/LLM/DeepSeek-V3.2 \
--tokenizer-mode deepseek_v32 \
--gpu-memory-utilization 0.95 \
--tensor-parallel-size 8 \
--host 0.0.0.0 \
--port 37001 \
--dtype auto \
--api-key sk-abc2dd6275a9187c77faccfdc730d352 \
--max-model-len 131072 \
--max-num-batched-tokens 32768 \
--trust-remote-code \
--reasoning-parser deepseek_r1 \
--enable-auto-tool-choice \
--tool-call-parser deepseek_v31 \
--enable-log-requests \
--enable-log-outputs > /nvme2/logs/vllm_log_format/DeepSeek-V3.2_20251203_37001.log 2>&1 &
However, the following error eventually occurred:
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] WorkerProc hit an exception.
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] Traceback (most recent call last):
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/executor/multiproc_executor.py", line 810, in worker_busy_loop
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] output = func(*args, **kwargs)
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_worker.py", line 429, in compile_or_warm_up_model
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] cuda_graph_memory_bytes = self.model_runner.capture_model()
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 4224, in capture_model
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] self._capture_cudagraphs(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 4298, in _capture_cudagraphs
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] self._dummy_run(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] return func(*args, **kwargs)
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 3756, in _dummy_run
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] attn_metadata, _ = self._build_attention_metadata(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 1576, in _build_attention_metadata
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] attn_metadata_i = builder.build_for_cudagraph_capture(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/attention/backends/utils.py", line 332, in build_for_cudagraph_capture
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] return self.build(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/attention/backends/mla/indexer.py", line 332, in build
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] self.scheduler_metadata_buffer[:] = get_paged_mqa_logits_metadata(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/utils/deep_gemm.py", line 263, in get_paged_mqa_logits_metadata
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] return _missing()
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/utils/deep_gemm.py", line 85, in _missing
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] raise RuntimeError(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] RuntimeError: DeepGEMM backend is not available or outdated. Please install or update the `deep_gemm` to a newer version to enable FP8 kernels.
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] Traceback (most recent call last):
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/executor/multiproc_executor.py", line 810, in worker_busy_loop
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] output = func(*args, **kwargs)
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_worker.py", line 429, in compile_or_warm_up_model
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] cuda_graph_memory_bytes = self.model_runner.capture_model()
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 4224, in capture_model
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] self._capture_cudagraphs(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 4298, in _capture_cudagraphs
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] self._dummy_run(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/torch/utils/_contextlib.py", line 120, in decorate_context
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] return func(*args, **kwargs)
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 3756, in _dummy_run
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] attn_metadata, _ = self._build_attention_metadata(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/worker/gpu_model_runner.py", line 1576, in _build_attention_metadata
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] attn_metadata_i = builder.build_for_cudagraph_capture(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/attention/backends/utils.py", line 332, in build_for_cudagraph_capture
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] return self.build(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/attention/backends/mla/indexer.py", line 332, in build
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] self.scheduler_metadata_buffer[:] = get_paged_mqa_logits_metadata(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/utils/deep_gemm.py", line 263, in get_paged_mqa_logits_metadata
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] return _missing()
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] ^^^^^^^^^^
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/utils/deep_gemm.py", line 85, in _missing
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] raise RuntimeError(
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815] RuntimeError: DeepGEMM backend is not available or outdated. Please install or update the `deep_gemm` to a newer version to enable FP8 kernels.
(Worker_TP0 pid=3392998) ERROR 12-03 06:51:53 [v1/executor/multiproc_executor.py:815]
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] EngineCore failed to start.
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] Traceback (most recent call last):
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 833, in run_engine_core
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] engine_core = EngineCoreProc(*args, **kwargs)
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 606, in __init__
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] super().__init__(
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 109, in __init__
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] num_gpu_blocks, num_cpu_blocks, kv_cache_config = self._initialize_kv_caches(
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] ^^^^^^^^^^^^^^^^^^^^^^^^^^^
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/engine/core.py", line 247, in _initialize_kv_caches
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] self.model_executor.initialize_from_config(kv_cache_configs)
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/executor/abstract.py", line 116, in initialize_from_config
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] self.collective_rpc("compile_or_warm_up_model")
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/executor/multiproc_executor.py", line 358, in collective_rpc
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] return aggregate(get_response())
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] ^^^^^^^^^^^^^^
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] File "/nvme2/pyenv_tst/vllm_deepseek_v32/lib/python3.12/site-packages/vllm/v1/executor/multiproc_executor.py", line 341, in get_response
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] raise RuntimeError(
(EngineCore_DP0 pid=3392721) ERROR 12-03 06:51:53 [v1/engine/core.py:842] RuntimeError: Worker failed with error 'DeepGEMM backend is not available or outdated. Please install or update the `deep_gemm` to a newer version to enable FP8 kernels.', please check the stack trace above for the root cause
I think this may be not caused by the customized tokenizer 🤔
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