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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]: TypeError: 'NoneType' object is not callable #6991

Closed anhnh2002 closed 3 months ago

anhnh2002 commented 4 months ago

Your current environment

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 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: version 3.29.3
Libc version: glibc-2.31

Python version: 3.10.14 (main, May  6 2024, 19:42:50) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.4.0-187-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 10.1.243
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: 
GPU 0: NVIDIA A100-PCIE-40GB
GPU 1: NVIDIA A100-PCIE-40GB

Nvidia driver version: 535.183.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.7
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.7
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
Byte Order:                         Little Endian
Address sizes:                      40 bits physical, 57 bits virtual
CPU(s):                             52
On-line CPU(s) list:                0-51
Thread(s) per core:                 1
Core(s) per socket:                 52
Socket(s):                          1
NUMA node(s):                       1
Vendor ID:                          GenuineIntel
CPU family:                         6
Model:                              134
Model name:                         Intel Xeon Processor (Icelake)
Stepping:                           0
CPU MHz:                            2194.848
BogoMIPS:                           4389.69
Virtualisation:                     VT-x
Hypervisor vendor:                  KVM
Virtualisation type:                full
L1d cache:                          1.6 MiB
L1i cache:                          1.6 MiB
L2 cache:                           208 MiB
L3 cache:                           16 MiB
NUMA node0 CPU(s):                  0-51
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:      Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Retbleed:             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 IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Vulnerable, KVM SW loop
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected
Flags:                              fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves wbnoinvd arat avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid md_clear arch_capabilities

Versions of relevant libraries:
[pip3] flake8==7.0.0
[pip3] flake8-bugbear==24.4.26
[pip3] flashinfer==0.1.2+cu124torch2.4
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.24.4
[pip3] nvidia-nccl-cu12==2.20.5
[pip3] onnxruntime==1.18.1
[pip3] sentence-transformers==3.0.1
[pip3] torch==2.3.0
[pip3] torchaudio==2.3.1
[pip3] torchtext==0.18.0
[pip3] torchvision==0.18.0
[pip3] transformers==4.43.3
[pip3] triton==2.3.0
[conda] flashinfer                0.1.2+cu124torch2.4          pypi_0    pypi
[conda] numpy                     1.23.5                   pypi_0    pypi
[conda] nvidia-nccl-cu12          2.20.5                   pypi_0    pypi
[conda] sentence-transformers     3.0.1                    pypi_0    pypi
[conda] torch                     2.3.0                    pypi_0    pypi
[conda] torchaudio                2.3.1                    pypi_0    pypi
[conda] torchtext                 0.18.0                   pypi_0    pypi
[conda] torchvision               0.18.0                   pypi_0    pypi
[conda] transformers              4.43.3                   pypi_0    pypi
[conda] triton                    2.3.0                    pypi_0    pypi
ROCM Version: Could not collect
Neuron SDK Version: N/A
vLLM Version: 0.5.1
vLLM Build Flags:
CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled
GPU Topology:
GPU0    GPU1    CPU Affinity    NUMA Affinity   GPU NUMA ID
GPU0     X      NV12    0-51    0               N/A
GPU1    NV12     X      0-51    0               N/A

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

🐛 Describe the bug

CUDA_VISIBLE_DEVICES=0 python -m vllm.entrypoints.openai.api_server --served-model-name Qwen2-7B-Instruct --model /home/anhnh/.cache/huggingface/hub/models--google--gemma-2-9b-it/snapshots/1937c70277fcc5f7fb0fc772fc5bc69378996e71 --dtype bfloat16 --host 0.0.0.0 --port 8888 --api-key test-000 --max-model-len 4096 --gpu-memory-utilization 0.5

logs

INFO 07-31 13:54:35 api_server.py:206] vLLM API server version 0.5.1
INFO 07-31 13:54:35 api_server.py:207] args: Namespace(host='0.0.0.0', port=8888, uvicorn_log_level='info', allow_credentials=False, allowed_origins=['*'], allowed_methods=['*'], allowed_headers=['*'], api_key='test-000', lora_modules=None, chat_template=None, response_role='assistant', ssl_keyfile=None, ssl_certfile=None, ssl_ca_certs=None, ssl_cert_reqs=0, root_path=None, middleware=[], model='/home/anhnh/.cache/huggingface/hub/models--google--gemma-2-9b-it/snapshots/1937c70277fcc5f7fb0fc772fc5bc69378996e71', tokenizer=None, skip_tokenizer_init=False, revision=None, code_revision=None, tokenizer_revision=None, tokenizer_mode='auto', trust_remote_code=False, download_dir=None, load_format='auto', dtype='bfloat16', kv_cache_dtype='auto', quantization_param_path=None, max_model_len=4096, guided_decoding_backend='outlines', distributed_executor_backend=None, worker_use_ray=False, pipeline_parallel_size=1, tensor_parallel_size=1, max_parallel_loading_workers=None, ray_workers_use_nsight=False, block_size=16, enable_prefix_caching=False, disable_sliding_window=False, use_v2_block_manager=False, num_lookahead_slots=0, seed=0, swap_space=4, gpu_memory_utilization=0.5, num_gpu_blocks_override=None, max_num_batched_tokens=None, max_num_seqs=256, max_logprobs=20, disable_log_stats=False, quantization=None, rope_scaling=None, rope_theta=None, enforce_eager=False, max_context_len_to_capture=None, max_seq_len_to_capture=8192, disable_custom_all_reduce=False, tokenizer_pool_size=0, tokenizer_pool_type='ray', tokenizer_pool_extra_config=None, enable_lora=False, max_loras=1, max_lora_rank=16, lora_extra_vocab_size=256, lora_dtype='auto', long_lora_scaling_factors=None, max_cpu_loras=None, fully_sharded_loras=False, device='auto', scheduler_delay_factor=0.0, enable_chunked_prefill=False, speculative_model=None, num_speculative_tokens=None, speculative_draft_tensor_parallel_size=None, speculative_max_model_len=None, speculative_disable_by_batch_size=None, ngram_prompt_lookup_max=None, ngram_prompt_lookup_min=None, spec_decoding_acceptance_method='rejection_sampler', typical_acceptance_sampler_posterior_threshold=None, typical_acceptance_sampler_posterior_alpha=None, model_loader_extra_config=None, preemption_mode=None, served_model_name=['Qwen2-7B-Instruct'], qlora_adapter_name_or_path=None, otlp_traces_endpoint=None, engine_use_ray=False, disable_log_requests=False, max_log_len=None)
WARNING 07-31 13:54:35 utils.py:562] Gemma 2 uses sliding window attention for every odd layer, which is currently not supported by vLLM. Disabling sliding window and capping the max length to the sliding window size (4096).
INFO 07-31 13:54:35 llm_engine.py:169] Initializing an LLM engine (v0.5.1) with config: model='/home/anhnh/.cache/huggingface/hub/models--google--gemma-2-9b-it/snapshots/1937c70277fcc5f7fb0fc772fc5bc69378996e71', speculative_config=None, tokenizer='/home/anhnh/.cache/huggingface/hub/models--google--gemma-2-9b-it/snapshots/1937c70277fcc5f7fb0fc772fc5bc69378996e71', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, rope_scaling=None, rope_theta=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=4096, download_dir=None, load_format=LoadFormat.AUTO, tensor_parallel_size=1, pipeline_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'), observability_config=ObservabilityConfig(otlp_traces_endpoint=None), seed=0, served_model_name=Qwen2-7B-Instruct, use_v2_block_manager=False, enable_prefix_caching=False)
INFO 07-31 13:54:36 selector.py:79] Using Flashinfer backend.
WARNING 07-31 13:54:36 selector.py:80] Flashinfer will be stuck on llama-2-7b, please avoid using Flashinfer as the backend when running on llama-2-7b.
INFO 07-31 13:54:36 selector.py:79] Using Flashinfer backend.
WARNING 07-31 13:54:36 selector.py:80] Flashinfer will be stuck on llama-2-7b, please avoid using Flashinfer as the backend when running on llama-2-7b.
INFO 07-31 13:54:40 model_runner.py:255] Loading model weights took 17.3781 GB
[rank0]: Traceback (most recent call last):
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/runpy.py", line 196, in _run_module_as_main
[rank0]:     return _run_code(code, main_globals, None,
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/runpy.py", line 86, in _run_code
[rank0]:     exec(code, run_globals)
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/entrypoints/openai/api_server.py", line 216, in <module>
[rank0]:     engine = AsyncLLMEngine.from_engine_args(
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 431, in from_engine_args
[rank0]:     engine = cls(
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 360, in __init__
[rank0]:     self.engine = self._init_engine(*args, **kwargs)
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/engine/async_llm_engine.py", line 507, in _init_engine
[rank0]:     return engine_class(*args, **kwargs)
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 256, in __init__
[rank0]:     self._initialize_kv_caches()
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 353, in _initialize_kv_caches
[rank0]:     self.model_executor.determine_num_available_blocks())
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/executor/gpu_executor.py", line 76, in determine_num_available_blocks
[rank0]:     return self.driver_worker.determine_num_available_blocks()
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/worker/worker.py", line 173, in determine_num_available_blocks
[rank0]:     self.model_runner.profile_run()
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/worker/model_runner.py", line 874, in profile_run
[rank0]:     self.execute_model(model_input, kv_caches, intermediate_tensors)
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/mnt/anhnh/miniconda3/envs/commonenv/lib/python3.10/site-packages/vllm/worker/model_runner.py", line 1201, in execute_model
[rank0]:     BatchDecodeWithPagedKVCacheWrapper(
[rank0]: TypeError: 'NoneType' object is not callable
anhnh2002 commented 4 months ago

I tried vllm v0.5.2/v0.5.3 and got same errors

LiuXiaoxuanPKU commented 4 months ago

It seems flashinfer is not installed. Could you just check if flashinfer is installed correctly by python -c "import flashinfer". flashinfer is not installed by default with vllm, you need to install flashinfer manually by installing the correct version (https://github.com/flashinfer-ai/flashinfer/releases/tag/v0.1.3).

elinx commented 3 months ago

I solved it after install flashinfer using: https://github.com/vllm-project/vllm/blob/db35186391a2abfc6c91d703527dac20d2488107/Dockerfile#L195

LiuXiaoxuanPKU commented 3 months ago

Feel free to reopen the issue if there are more questions.