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vllm-project / vllm

A high-throughput and memory-efficient inference and serving engine for LLMs
https://docs.vllm.ai
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[Bug]:vllm-0.4.2 running error #4972

Open tohneecao opened 3 months ago

tohneecao commented 3 months ago

Your current environment

The output of `python collect_env.py`

🐛 Describe the bug

compile steps：

  1. pip install -r requirements-build.txt ；pip install -r requirements-dev.txt ；pip install -r requirements-common.txt ；pip install -r requirements-cuda.txt ；
  2. python setup.py build
  3. python setup.py bdist_wheel
  4. pip install dist/*.whl

cd. benchmarks/ python benchmark_throughput.py --model /local_model_root/model/qwen-14b-chat/qwen/Qwen-14B-Chat/ --dataset /local_model_root/model/datasets/ShareGPT_V3_unfiltered_cleaned_split.json --trust-remote-code

get error blow: Namespace(backend='vllm', dataset='/local_model_root/model/datasets/ShareGPT_V3_unfiltered_cleaned_split.json', input_len=None, output_len=None, model='/local_model_root/model/qwen-14b-chat/qwen/Qwen-14B-Chat/', tokenizer='/local_model_root/model/qwen-14b-chat/qwen/Qwen-14B-Chat/', quantization=None, tensor_parallel_size=1, n=1, use_beam_search=False, num_prompts=1000, seed=0, hf_max_batch_size=None, trust_remote_code=True, max_model_len=None, dtype='auto', gpu_memory_utilization=0.9, enforce_eager=False, kv_cache_dtype='auto', quantization_param_path=None, device='cuda', enable_prefix_caching=False, enable_chunked_prefill=False, max_num_batched_tokens=None, download_dir=None) INFO 05-22 16:54:52 llm_engine.py:100] Initializing an LLM engine (v0.4.2) with config: model='/local_model_root/model/qwen-14b-chat/qwen/Qwen-14B-Chat/', speculative_config=None, tokenizer='/local_model_root/model/qwen-14b-chat/qwen/Qwen-14B-Chat/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.float16, max_seq_len=2048, 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=/local_model_root/model/qwen-14b-chat/qwen/Qwen-14B-Chat/) WARNING 05-22 16:54:52 tokenizer.py:126] Using a slow tokenizer. This might cause a significant slowdown. Consider using a fast tokenizer instead. INFO 05-22 16:54:52 utils.py:660] Found nccl from library /root/.config/vllm/nccl/cu12/libnccl.so.2.18.1 Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py", line 1535, in _get_module return importlib.import_module("." + module_name, self.name) File "/usr/lib/python3.10/importlib/init.py", line 126, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "", line 1050, in _gcd_import File "", line 1027, in _find_and_load File "", line 1006, in _find_and_load_unlocked File "", line 688, in _load_unlocked File "", line 883, in exec_module File "", line 241, in _call_with_frames_removed File "/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py", line 97, in from accelerate.hooks import AlignDevicesHook, add_hook_to_module File "/usr/local/lib/python3.10/dist-packages/accelerate/init.py", line 16, in from .accelerator import Accelerator File "/usr/local/lib/python3.10/dist-packages/accelerate/accelerator.py", line 35, in from .checkpointing import load_accelerator_state, load_custom_state, save_accelerator_state, save_custom_state File "/usr/local/lib/python3.10/dist-packages/accelerate/checkpointing.py", line 24, in from .utils import ( File "/usr/local/lib/python3.10/dist-packages/accelerate/utils/init.py", line 177, in from .bnb import has_4bit_bnb_layers, load_and_quantize_model File "/usr/local/lib/python3.10/dist-packages/accelerate/utils/bnb.py", line 29, in from ..big_modeling import dispatch_model, init_empty_weights File "/usr/local/lib/python3.10/dist-packages/accelerate/big_modeling.py", line 24, in from .hooks import ( File "/usr/local/lib/python3.10/dist-packages/accelerate/hooks.py", line 30, in from .utils.other import recursive_getattr File "/usr/local/lib/python3.10/dist-packages/accelerate/utils/other.py", line 36, in from .transformer_engine import convert_model File "/usr/local/lib/python3.10/dist-packages/accelerate/utils/transformer_engine.py", line 21, in import transformer_engine.pytorch as te File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/init.py", line 6, in from .module import LayerNormLinear File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/module/init.py", line 6, in from .layernorm_linear import LayerNormLinear File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/module/layernorm_linear.py", line 15, in from .. import cpp_extensions as tex File "/usr/local/lib/python3.10/dist-packages/transformer_engine/pytorch/cpp_extensions/init.py", line 6, in from transformer_engine_extensions import * ImportError: /usr/local/lib/python3.10/dist-packages/transformer_engine_extensions.cpython-310-x86_64-linux-gnu.so: undefined symbol: _ZN2at4_ops5zeros4callEN3c108ArrayRefINS2_6SymIntEEENS2_8optionalINS2_10ScalarTypeEEENS6_INS2_6LayoutEEENS6_INS2_6DeviceEEENS6_IbEE

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py", line 1535, in _get_module return importlib.import_module("." + module_name, self.name) File "/usr/lib/python3.10/importlib/init.py", line 126, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "", line 1050, in _gcd_import File "", line 1027, in _find_and_load File "", line 1006, in _find_and_load_unlocked File "", line 688, in _load_unlocked File "", line 883, in exec_module File "", line 241, in _call_with_frames_removed File "/usr/local/lib/python3.10/dist-packages/transformers/models/clip/modeling_clip.py", line 29, in from ...modeling_utils import PreTrainedModel File "/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py", line 45, in from .generation import GenerationConfig, GenerationMixin File "", line 1075, in _handle_fromlist File "/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py", line 1525, in getattr module = self._get_module(self._class_to_module[name]) File "/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py", line 1537, in _get_module raise RuntimeError( RuntimeError: Failed to import transformers.generation.utils because of the following error (look up to see its traceback): /usr/local/lib/python3.10/dist-packages/transformer_engine_extensions.cpython-310-x86_64-linux-gnu.so: undefined symbol: _ZN2at4_ops5zeros4callEN3c108ArrayRefINS2_6SymIntEEENS2_8optionalINS2_10ScalarTypeEEENS6_INS2_6LayoutEEENS6_INS2_6DeviceEEENS6_IbEE

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "/workspace/vllm-0.4.2/benchmarks/benchmark_throughput.py", line 387, in main(args) File "/workspace/vllm-0.4.2/benchmarks/benchmark_throughput.py", line 221, in main elapsed_time = run_vllm( File "/workspace/vllm-0.4.2/benchmarks/benchmark_throughput.py", line 85, in run_vllm llm = LLM( File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/llm.py", line 123, in init self.llm_engine = LLMEngine.from_engine_args( File "/usr/local/lib/python3.10/dist-packages/vllm/engine/llm_engine.py", line 292, in from_engine_args engine = cls( File "/usr/local/lib/python3.10/dist-packages/vllm/engine/llm_engine.py", line 160, in init self.model_executor = executor_class( File "/usr/local/lib/python3.10/dist-packages/vllm/executor/executor_base.py", line 41, in init self._init_executor() File "/usr/local/lib/python3.10/dist-packages/vllm/executor/gpu_executor.py", line 23, in _init_executor self._init_non_spec_worker() File "/usr/local/lib/python3.10/dist-packages/vllm/executor/gpu_executor.py", line 67, in _init_non_spec_worker self.driver_worker = self._create_worker() File "/usr/local/lib/python3.10/dist-packages/vllm/executor/gpu_executor.py", line 59, in _create_worker wrapper.init_worker(**self._get_worker_kwargs(local_rank, rank, File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker_base.py", line 129, in init_worker mod = importlib.import_module(self.worker_module_name) File "/usr/lib/python3.10/importlib/init.py", line 126, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "", line 1050, in _gcd_import File "", line 1027, in _find_and_load File "", line 1006, in _find_and_load_unlocked File "", line 688, in _load_unlocked File "", line 883, in exec_module File "", line 241, in _call_with_frames_removed File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker.py", line 23, in from vllm.worker.model_runner import ModelRunner File "/usr/local/lib/python3.10/dist-packages/vllm/worker/model_runner.py", line 23, in from vllm.model_executor.model_loader import get_model File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/model_loader/init.py", line 7, in from vllm.model_executor.model_loader.loader import (BaseModelLoader, File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/model_loader/loader.py", line 28, in from vllm.model_executor.models.llava import LlavaForConditionalGeneration File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/models/llava.py", line 7, in from transformers import CLIPVisionModel, LlavaConfig File "", line 1075, in _handle_fromlist File "/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py", line 1526, in getattr value = getattr(module, name) File "/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py", line 1525, in getattr module = self._get_module(self._class_to_module[name]) File "/usr/local/lib/python3.10/dist-packages/transformers/utils/import_utils.py", line 1537, in _get_module raise RuntimeError( RuntimeError: Failed to import transformers.models.clip.modeling_clip because of the following error (look up to see its traceback): Failed to import transformers.generation.utils because of the following error (look up to see its traceback): /usr/local/lib/python3.10/dist-packages/transformer_engine_extensions.cpython-310-x86_64-linux-gnu.so: undefined symbol: _ZN2at4_ops5zeros4callEN3c108ArrayRefINS2_6SymIntEEENS2_8optionalINS2_10ScalarTypeEEENS6_INS2_6LayoutEEENS6_INS2_6DeviceEEENS6_IbEE

tohneecao commented 3 months ago

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 3.27.6 Libc version: glibc-2.35

Python version: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] (64-bit runtime) Python platform: Linux-5.10.134-13.al8.x86_64-x86_64-with-glibc2.35 Is CUDA available: True CUDA runtime version: 12.2.140 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA A100-SXM4-40GB GPU 1: NVIDIA A100-SXM4-40GB GPU 2: NVIDIA A100-SXM4-40GB GPU 3: NVIDIA A100-SXM4-40GB GPU 4: NVIDIA A100-SXM4-40GB GPU 5: NVIDIA A100-SXM4-40GB GPU 6: NVIDIA A100-SXM4-40GB GPU 7: NVIDIA A100-SXM4-40GB

Nvidia driver version: 535.129.03 cuDNN version: Probably one of the following: /usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.5 /usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.5 /usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.5 /usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.5 /usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.5 /usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.5 /usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.5 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): 104 On-line CPU(s) list: 0-103 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Platinum 8269CY CPU @ 2.50GHz CPU family: 6 Model: 85 Thread(s) per core: 2 Core(s) per socket: 26 Socket(s): 2 Stepping: 7 CPU max MHz: 3800.0000 CPU min MHz: 1200.0000 BogoMIPS: 5000.00 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 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 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 pku ospke avx512_vnni md_clear flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 1.6 MiB (52 instances) L1i cache: 1.6 MiB (52 instances) L2 cache: 52 MiB (52 instances) L3 cache: 71.5 MiB (2 instances) NUMA node(s): 1 NUMA node0 CPU(s): 0-103 Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Vulnerable: Clear CPU buffers attempted, no microcode; SMT vulnerable Vulnerability Retbleed: Mitigation; Enhanced IBRS 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 IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; TSX disabled

Versions of relevant libraries: [pip3] mypy==1.9.0 [pip3] mypy-extensions==1.0.0 [pip3] numpy==1.22.2 [pip3] nvidia-nccl-cu12==2.20.5 [pip3] onnx==1.14.0 [pip3] pytorch-quantization==2.1.2 [pip3] torch==2.3.0 [pip3] torch-tensorrt==0.0.0 [pip3] torchdata==0.7.0a0 [pip3] torchtext==0.16.0a0 [pip3] torchvision==0.16.0a0 [pip3] triton==2.3.0 [pip3] vllm-nccl-cu12==2.18.1.0.4.0 [conda] Could not collectROCM Version: Could not collect Neuron SDK Version: N/A vLLM Version: 0.4.2 vLLM Build Flags: CUDA Archs: 5.2 6.0 6.1 7.0 7.2 7.5 8.0 8.6 8.7 9.0+PTX; ROCm: Disabled; Neuron: Disabled GPU Topology: GPU0 GPU1 GPU2 GPU3 GPU4 GPU5 GPU6 GPU7 NIC0 CPU Affinity NUMA Affinity GPU NUMA ID GPU0 X NV12 NV12 NV12 NV12 NV12 NV12 NV12 SYS 0-103 0 N/A GPU1 NV12 X NV12 NV12 NV12 NV12 NV12 NV12 SYS 0-103 0 N/A GPU2 NV12 NV12 X NV12 NV12 NV12 NV12 NV12 SYS 0-103 0 N/A GPU3 NV12 NV12 NV12 X NV12 NV12 NV12 NV12 SYS 0-103 0 N/A GPU4 NV12 NV12 NV12 NV12 X NV12 NV12 NV12 SYS 0-103 0 N/A GPU5 NV12 NV12 NV12 NV12 NV12 X NV12 NV12 SYS 0-103 0 N/A GPU6 NV12 NV12 NV12 NV12 NV12 NV12 X NV12 SYS 0-103 0 N/A GPU7 NV12 NV12 NV12 NV12 NV12 NV12 NV12 X SYS 0-103 0 N/A NIC0 SYS SYS SYS SYS SYS 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_bond_0

youkaichao commented 3 months ago

/usr/local/lib/python3.10/dist-packages/transformer_engine_extensions.cpython-310-x86_64-linux-gnu.so: undefined symbol: _ZN2at4_ops5zeros4callEN3c108ArrayRefINS2_6SymIntEEENS2_8optionalINS2_10ScalarTypeEEENS6_INS2_6LayoutEEENS6_INS2_6DeviceEEENS6_IbEE

error comes from transformer engine. you need to check why python imports it. usually it should not be required.