[Bug]: Server - `aqlm` fails with `--cpu-offload-gb`

JMPSequeira commented 1 month ago

Your current environment

The output of `python collect_env.py`

```text PyTorch version: 2.4.0+cu121 Is debug build: False CUDA used to build PyTorch: 12.1 ROCM used to build PyTorch: N/A OS: Arch Linux (x86_64) GCC version: (GCC) 14.2.1 20240910 Clang version: Could not collect CMake version: Could not collect Libc version: glibc-2.40 Python version: 3.12.6 (main, Sep 8 2024, 13:18:56) [GCC 14.2.1 20240805] (64-bit runtime) Python platform: Linux-6.10.10-arch1-1-x86_64-with-glibc2.40 Is CUDA available: True CUDA runtime version: 12.6.68 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce RTX 4070 Ti SUPER GPU 1: NVIDIA GeForce RTX 4070 Ti SUPER Nvidia driver version: 560.35.03 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: 39 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 28 On-line CPU(s) list: 0-27 Vendor ID: GenuineIntel Model name: Intel(R) Core(TM) i7-14700KF CPU family: 6 Model: 183 Thread(s) per core: 2 Core(s) per socket: 20 Socket(s): 1 Stepping: 1 CPU(s) scaling MHz: 27% CPU max MHz: 5600.0000 CPU min MHz: 800.0000 BogoMIPS: 6837.00 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 est tm2 ssse3 sdbg fma cx16 xtpr pdcm sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize arch_lbr ibt flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 768 KiB (20 instances) L1i cache: 1 MiB (20 instances) L2 cache: 28 MiB (11 instances) L3 cache: 33 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-27 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: Mitigation; Clear Register File 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] numpy==1.26.4 [pip3] nvidia-cublas-cu12==12.1.3.1 [pip3] nvidia-cuda-cupti-cu12==12.1.105 [pip3] nvidia-cuda-nvrtc-cu12==12.1.105 [pip3] nvidia-cuda-runtime-cu12==12.1.105 [pip3] nvidia-cudnn-cu12==9.1.0.70 [pip3] nvidia-cufft-cu12==11.0.2.54 [pip3] nvidia-curand-cu12==10.3.2.106 [pip3] nvidia-cusolver-cu12==11.4.5.107 [pip3] nvidia-cusparse-cu12==12.1.0.106 [pip3] nvidia-ml-py==12.560.30 [pip3] nvidia-nccl-cu12==2.20.5 [pip3] nvidia-nvjitlink-cu12==12.6.68 [pip3] nvidia-nvtx-cu12==12.1.105 [pip3] pyzmq==26.2.0 [pip3] torch==2.4.0 [pip3] torchvision==0.19.0 [pip3] transformers==4.45.1 [pip3] triton==3.0.0 [conda] Could not collect ROCM Version: Could not collect Neuron SDK Version: N/A vLLM Version: N/A vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled GPU Topology: [4mGPU0 GPU1 CPU Affinity NUMA Affinity GPU NUMA ID[0m GPU0 X PHB 0-27 0 N/A GPU1 PHB X 0-27 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 ```

Model Input Dumps

No response

🐛 Describe the bug

Model: ISTA-DASLab/Meta-Llama-3.1-70B-Instruct-AQLM-PV-2Bit-1x16 Command: vllm serve ~/ai/models/Meta-Llama-3.1-70B-Instruct/AQLM-PV-2Bit-1x16/ --max-model-len 8192 --quantization aqlm -tp 2 --host 0.0.0.0 --port 8050 --served-model-name llama3.1-70b --disable-custom-all-reduce --cpu-offload-gb 10

Loading safetensors checkpoint shards:   0% Completed | 0/5 [00:00<?, ?it/s]                                                                
Loading safetensors checkpoint shards:  20% Completed | 1/5 [00:00<00:01,  2.56it/s]                                                        
Loading safetensors checkpoint shards:  40% Completed | 2/5 [00:00<00:01,  2.50it/s]                                                        
Loading safetensors checkpoint shards:  60% Completed | 3/5 [00:01<00:00,  2.39it/s]                                                        
Loading safetensors checkpoint shards:  80% Completed | 4/5 [00:01<00:00,  2.36it/s] 
Loading safetensors checkpoint shards: 100% Completed | 5/5 [00:01<00:00,  3.20it/s]                                      23:02:17 [27/1973]
Loading safetensors checkpoint shards: 100% Completed | 5/5 [00:01<00:00,  2.80it/s]

INFO 09-26 23:01:47 model_runner.py:1025] Loading model weights took 1.9590 GB
(VllmWorkerProcess pid=41043) INFO 09-26 23:01:49 model_runner.py:1025] Loading model weights took 1.9590 GB
Traceback (most recent call last):                                                                                                          
  File "/home/js/.pyenv/vllm/bin/vllm", line 8, in <module>
    sys.exit(main())                                                  
             ^^^^^^                                                   
  File "/home/js/.pyenv/vllm/lib/python3.12/site-packages/vllm/scripts.py", line 165, in main
    args.dispatch_function(args)
  File "/home/js/.pyenv/vllm/lib/python3.12/site-packages/vllm/scripts.py", line 37, in serve                                                   uvloop.run(run_server(args))
  File "/home/js/.pyenv/vllm/lib/python3.12/site-packages/uvloop/__init__.py", line 109, in run
    return __asyncio.run(                                             
           ^^^^^^^^^^^^^^                                                                                                                     File "/usr/lib/python3.12/asyncio/runners.py", line 194, in run
    return runner.run(main)                                           
           ^^^^^^^^^^^^^^^^                                                                                                                   File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
    return self._loop.run_until_complete(task)            
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "uvloop/loop.pyx", line 1517, in uvloop.loop.Loop.run_until_complete                                                                 
  File "/home/js/.pyenv/vllm/lib/python3.12/site-packages/uvloop/__init__.py", line 61, in wrapper                                              return await main                                                                                                                       
           ^^^^^^^^^^
  File "/home/js/.pyenv/vllm/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 538, in run_server                   
    async with build_async_engine_client(args) as engine_client:                                                                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^                     
  File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
    return await anext(self.gen)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/home/js/.pyenv/vllm/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 105, in build_async_engine_client
    async with build_async_engine_client_from_engine_args(
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/lib/python3.12/contextlib.py", line 210, in __aenter__
    return await anext(self.gen)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/home/js/.pyenv/vllm/lib/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 192, in build_async_engine_client_from_engine_args
    raise RuntimeError(
RuntimeError: Engine process failed to start
/usr/lib/python3.12/multiprocessing/resource_tracker.py:254: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
  warnings.warn('resource_tracker: There appear to be %d '
/usr/lib/python3.12/multiprocessing/resource_tracker.py:254: UserWarning: resource_tracker: There appear to be 1 leaked shared_memory objects to clean up at shutdown
  warnings.warn('resource_tracker: There appear to be %d '

The model runs fine without --cpu-offload-gb.

I did chat with the Ask vLLM chatbot and it did point me in the direction of (/tests/quantization/test_cpu_offload.py)[https://github.com/vllm-project/vllm/blob/main/tests/quantization/test_cpu_offload.py] which does not test for aqlm.

Is this a bug or is it not possible to run aqlm with cpu offloading?

Before submitting a new issue...

[X] Make sure you already searched for relevant issues, and asked the chatbot living at the bottom right corner of the documentation page, which can answer lots of frequently asked questions.

mgoin commented 1 month ago

I don't think we tested this since the aqlm implementation isn't commonly used. Thanks for reporting, I can look into this!

cduk commented 1 week ago

Also crashes on GGUF

vllm-project / vllm