Your current environment
Collecting environment information...
PyTorch version: 2.3.0+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A
OS: Ubuntu 22.04.3 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.29.2
Libc version: glibc-2.35
Python version: 3.10.12 (main, Nov 20 2023, 15:14:05) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.4.0-94-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA A100-SXM4-80GB
GPU 1: NVIDIA A100-SXM4-80GB
GPU 2: NVIDIA A100-SXM4-80GB
GPU 3: NVIDIA A100-SXM4-80GB
GPU 4: NVIDIA A100-SXM4-80GB
GPU 5: NVIDIA A100-SXM4-80GB
GPU 6: NVIDIA A100-SXM4-80GB
GPU 7: NVIDIA A100-SXM4-80GB
Nvidia driver version: 535.104.05
cuDNN version: Could not collect
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: 43 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 128
On-line CPU(s) list: 0-127
Vendor ID: AuthenticAMD
Model name: AMD EPYC 7742 64-Core Processor
CPU family: 23
Model: 49
Thread(s) per core: 1
Core(s) per socket: 64
Socket(s): 2
Stepping: 0
Frequency boost: enabled
CPU max MHz: 2250.0000
CPU min MHz: 1500.0000
BogoMIPS: 4499.81
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate sme ssbd mba sev ibrs ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr wbnoinvd arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif umip rdpid overflow_recov succor smca
Virtualization: AMD-V
L1d cache: 4 MiB (128 instances)
L1i cache: 4 MiB (128 instances)
L2 cache: 64 MiB (128 instances)
L3 cache: 512 MiB (32 instances)
NUMA node(s): 8
NUMA node0 CPU(s): 0-15
NUMA node1 CPU(s): 16-31
NUMA node2 CPU(s): 32-47
NUMA node3 CPU(s): 48-63
NUMA node4 CPU(s): 64-79
NUMA node5 CPU(s): 80-95
NUMA node6 CPU(s): 96-111
NUMA node7 CPU(s): 112-127
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: 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; Full AMD retpoline, IBPB conditional, IBRS_FW, STIBP disabled, RSB filling
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] torch==2.3.0
[pip3] torchvision==0.18.1
[pip3] transformers==4.40.0
[pip3] triton==2.3.0
[pip3] vllm-nccl-cu12==2.18.1.0.4.0
[conda] Could not collect
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.4.3
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 NIC4 NIC5 NIC6 NIC7 NIC8 NIC9 CPU Affinity NUMA Affinity GPU NUMA ID
GPU0 X NV12 NV12 NV12 NV12 NV12 NV12 NV12 SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS 48-63 3 N/A
GPU1 NV12 X NV12 NV12 NV12 NV12 NV12 NV12 SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS 48-63 3 N/A
GPU2 NV12 NV12 X NV12 NV12 NV12 NV12 NV12 PXB PXB SYS SYS SYS SYS SYS SYS SYS SYS 16-31 1 N/A
GPU3 NV12 NV12 NV12 X NV12 NV12 NV12 NV12 PXB PXB SYS SYS SYS SYS SYS SYS SYS SYS 16-31 1 N/A
GPU4 NV12 NV12 NV12 NV12 X NV12 NV12 NV12 SYS SYS SYS SYS SYS SYS SYS SYS PXB PXB 112-127 7 N/A
GPU5 NV12 NV12 NV12 NV12 NV12 X NV12 NV12 SYS SYS SYS SYS SYS SYS SYS SYS PXB PXB 112-127 7 N/A
GPU6 NV12 NV12 NV12 NV12 NV12 NV12 X NV12 SYS SYS SYS SYS SYS SYS PXB PXB SYS SYS 80-95 5 N/A
GPU7 NV12 NV12 NV12 NV12 NV12 NV12 NV12 X SYS SYS SYS SYS SYS SYS PXB PXB SYS SYS 80-95 5 N/A
NIC0 SYS SYS PXB PXB SYS SYS SYS SYS X PIX SYS SYS SYS SYS SYS SYS SYS SYS
NIC1 SYS SYS PXB PXB SYS SYS SYS SYS PIX X SYS SYS SYS SYS SYS SYS SYS SYS
NIC2 PXB PXB SYS SYS SYS SYS SYS SYS SYS SYS X PXB SYS SYS SYS SYS SYS SYS
NIC3 PXB PXB SYS SYS SYS SYS SYS SYS SYS SYS PXB X SYS SYS SYS SYS SYS SYS
NIC4 SYS SYS SYS SYS SYS SYS SYS SYS SYS SYS SYS SYS X PIX SYS SYS SYS SYS
NIC5 SYS SYS SYS SYS SYS SYS SYS SYS SYS SYS SYS SYS PIX X SYS SYS SYS SYS
NIC6 SYS SYS SYS SYS SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS X PXB SYS SYS
NIC7 SYS SYS SYS SYS SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS PXB X SYS SYS
NIC8 SYS SYS SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS SYS SYS SYS SYS X PXB
NIC9 SYS SYS SYS SYS PXB PXB SYS SYS SYS SYS SYS SYS SYS SYS SYS SYS PXB 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
NIC8: mlx5_8
NIC9: mlx5_9
🐛 Describe the bug
- The command executed when starting CLM4-V using vllm
CUDA_VISIBLE_DEVICES=0,3 python3 -m vllm.entrypoints.openai.api_server --model=/data/lush-dev/liwei/code/gpt/models/huggingface/glm-4v-9b --served-model-name=glm-4v-9b --device=cuda --port=8000 --host=0.0.0.0 --tensor-parallel-size=1 --dtype=auto --trust-remote-code
- errors info
INFO 06-11 08:11:33 llm_engine.py:161] Initializing an LLM engine (v0.4.3) with config: model='/data/lush-dev/liwei/code/gpt/models/huggingface/glm-4v-9b', speculative_config=None, tokenizer='/data/lush-dev/liwei/code/gpt/models/huggingface/glm-4v-9b', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, rope_scaling=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=8192, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, quantization_param_path=None, device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='outlines'), seed=0, served_model_name=glm-4v-9b)
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
WARNING 06-11 08:11:34 tokenizer.py:126] Using a slow tokenizer. This might cause a significant slowdown. Consider using a fast tokenizer instead.
[rank0]: Traceback (most recent call last):
[rank0]: File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
[rank0]: return _run_code(code, main_globals, None,
[rank0]: File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
[rank0]: exec(code, run_globals)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/openai/api_server.py", line 186, in <module>
[rank0]: engine = AsyncLLMEngine.from_engine_args(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 386, in from_engine_args
[rank0]: engine = cls(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 340, in __init__
[rank0]: self.engine = self._init_engine(*args, **kwargs)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 462, in _init_engine
[rank0]: return engine_class(*args, **kwargs)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/engine/llm_engine.py", line 222, in __init__
[rank0]: self.model_executor = executor_class(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/executor/executor_base.py", line 41, in __init__
[rank0]: self._init_executor()
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/executor/gpu_executor.py", line 24, in _init_executor
[rank0]: self.driver_worker.load_model()
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker.py", line 121, in load_model
[rank0]: self.model_runner.load_model()
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/worker/model_runner.py", line 134, in load_model
[rank0]: self.model = get_model(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/model_loader/__init__.py", line 21, in get_model
[rank0]: return loader.load_model(model_config=model_config,
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/model_loader/loader.py", line 243, in load_model
[rank0]: model.load_weights(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/models/chatglm.py", line 392, in load_weights
[rank0]: param = params_dict[name]
[rank0]: KeyError: 'transformer.vision.transformer.layers.45.mlp.fc2.weight'
