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A high-throughput and memory-efficient inference and serving engine for LLMs
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[Bug]: gguf file without .gguf extension fails to run, even with "--quantization gguf --load-format gguf" flags #7993

Closed ericcurtin closed 2 months ago

ericcurtin commented 2 months ago

Your current environment

The output of `python collect_env.py` ```text $ python collect_env.py Collecting environment information... WARNING 08-29 11:55:28 _custom_ops.py:17] Failed to import from vllm._C with ImportError('libcuda.so.1: cannot open shared object file: No such file or directory') 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: Fedora release 40 (Forty) (x86_64) GCC version: (GCC) 14.2.1 20240801 (Red Hat 14.2.1-1) Clang version: 18.1.6 (Fedora 18.1.6-3.fc40) CMake version: version 3.28.2 Libc version: glibc-2.39 Python version: 3.12.5 (main, Aug 7 2024, 00:00:00) [GCC 14.2.1 20240801 (Red Hat 14.2.1-1)] (64-bit runtime) Python platform: Linux-6.10.6-200.fc40.x86_64-x86_64-with-glibc2.39 Is CUDA available: False CUDA runtime version: No CUDA CUDA_MODULE_LOADING set to: N/A GPU models and configuration: No CUDA Nvidia driver version: No CUDA cuDNN version: No CUDA 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): 12 On-line CPU(s) list: 0-11 Vendor ID: GenuineIntel Model name: Intel(R) Core(TM) i7-10850H CPU @ 2.70GHz CPU family: 6 Model: 165 Thread(s) per core: 2 Core(s) per socket: 6 Socket(s): 1 Stepping: 2 CPU(s) scaling MHz: 82% CPU max MHz: 5100.0000 CPU min MHz: 800.0000 BogoMIPS: 5399.81 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 sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid mpx rdseed adx smap clflushopt intel_pt xsaveopt xsavec xgetbv1 xsaves dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp vnmi pku ospke md_clear flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 192 KiB (6 instances) L1i cache: 192 KiB (6 instances) L2 cache: 1.5 MiB (6 instances) L3 cache: 12 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-11 Vulnerability Gather data sampling: Mitigation; Microcode Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Mitigation; Enhanced IBRS 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 SW loop, KVM SW loop Vulnerability Srbds: Mitigation; Microcode Vulnerability Tsx async abort: Not affected Versions of relevant libraries: [pip3] flake8==7.1.0 [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==12.6.20 [pip3] nvidia-nvtx-cu12==12.1.105 [pip3] pyzmq==26.2.0 [pip3] torch==2.4.0 [pip3] torchvision==0.19.0 [pip3] transformers==4.44.2 [pip3] triton==3.0.0 [conda] Could not collect ROCM Version: Could not collect Neuron SDK Version: N/A vLLM Version: 0.5.5@09c7792610ada9f88bbf87d32b472dd44bf23cc2 vLLM Build Flags: CUDA Archs: Not Set; ROCm: Disabled; Neuron: Disabled GPU Topology: Could not collect ```

🐛 Describe the bug

Running .gguf files without .gguf extension does not work... renaming these files with .gguf extension and running without any flags (just using "vllm serve granite-code:latest.gguf") works.

Expected behaviour is that we don't require .gguf extension to run .gguf file.

$ vllm serve ~/.local/share/ramalama/models/ollama/granite-code:latest --quantization gguf --load-format gguf
WARNING 08-29 11:56:16 _custom_ops.py:17] Failed to import from vllm._C with ImportError('libcuda.so.1: cannot open shared object file: No such file or directory')
INFO 08-29 11:56:19 api_server.py:440] vLLM API server version 0.5.5
INFO 08-29 11:56:19 api_server.py:441] args: Namespace(model_tag='/home/curtine/.local/share/ramalama/models/ollama/granite-code:latest', host=None, port=8000, uvicorn_log_level='info', allow_credentials=False, allowed_origins=['*'], allowed_methods=['*'], allowed_headers=['*'], api_key=None, lora_modules=None, prompt_adapters=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=[], return_tokens_as_token_ids=False, disable_frontend_multiprocessing=False, model='/home/curtine/.local/share/ramalama/models/ollama/granite-code:latest', 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='gguf', dtype='auto', kv_cache_dtype='auto', quantization_param_path=None, max_model_len=None, 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, cpu_offload_gb=0, gpu_memory_utilization=0.9, num_gpu_blocks_override=None, max_num_batched_tokens=None, max_num_seqs=256, max_logprobs=20, disable_log_stats=False, quantization='gguf', 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, limit_mm_per_prompt=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, enable_prompt_adapter=False, max_prompt_adapters=1, max_prompt_adapter_token=0, device='auto', num_scheduler_steps=1, scheduler_delay_factor=0.0, enable_chunked_prefill=None, speculative_model=None, speculative_model_quantization=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, disable_logprobs_during_spec_decoding=None, model_loader_extra_config=None, ignore_patterns=[], preemption_mode=None, served_model_name=None, qlora_adapter_name_or_path=None, otlp_traces_endpoint=None, collect_detailed_traces=None, engine_use_ray=False, disable_log_requests=False, max_log_len=None, dispatch_function=<function serve at 0x7f15a2e81f80>)
Traceback (most recent call last):
  File "/usr/local/lib/python3.12/site-packages/transformers/configuration_utils.py", line 722, in _get_config_dict
    config_dict = cls._dict_from_json_file(resolved_config_file)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/site-packages/transformers/configuration_utils.py", line 825, in _dict_from_json_file
    text = reader.read()
           ^^^^^^^^^^^^^
  File "<frozen codecs>", line 322, in decode
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xac in position 446: invalid start byte

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/bin/vllm", line 8, in <module>
    sys.exit(main())
             ^^^^^^
  File "/usr/local/lib64/python3.12/site-packages/vllm/scripts.py", line 156, in main
    args.dispatch_function(args)
  File "/usr/local/lib64/python3.12/site-packages/vllm/scripts.py", line 37, in serve
    asyncio.run(run_server(args))
  File "/usr/lib64/python3.12/asyncio/runners.py", line 194, in run
    return runner.run(main)
           ^^^^^^^^^^^^^^^^
  File "/usr/lib64/python3.12/asyncio/runners.py", line 118, in run
    return self._loop.run_until_complete(task)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/lib64/python3.12/asyncio/base_events.py", line 687, in run_until_complete
    return future.result()
           ^^^^^^^^^^^^^^^
  File "/usr/local/lib64/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 443, in run_server
    async with build_async_engine_client(args) as async_engine_client:
  File "/usr/lib64/python3.12/contextlib.py", line 210, in __aenter__
    return await anext(self.gen)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib64/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 117, in build_async_engine_client
    if (model_is_embedding(args.model, args.trust_remote_code,
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib64/python3.12/site-packages/vllm/entrypoints/openai/api_server.py", line 71, in model_is_embedding
    return ModelConfig(model=model_name,
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib64/python3.12/site-packages/vllm/config.py", line 169, in __init__
    self.hf_config = get_config(self.model, trust_remote_code, revision,
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib64/python3.12/site-packages/vllm/transformers_utils/config.py", line 64, in get_config
    config = AutoConfig.from_pretrained(
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/site-packages/transformers/models/auto/configuration_auto.py", line 976, in from_pretrained
    config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/site-packages/transformers/configuration_utils.py", line 632, in get_config_dict
    config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.12/site-packages/transformers/configuration_utils.py", line 726, in _get_config_dict
    raise EnvironmentError(
OSError: It looks like the config file at '/home/curtine/.local/share/ramalama/models/ollama/granite-code:latest' is not a valid JSON file.

Before submitting a new issue...

mgoin commented 2 months ago

Thanks for reporting! This would be a bit tricky to achieve cleanly since we need to pipe down the information to these places for fetching the config and tokenizer from the file

https://github.com/vllm-project/vllm/blob/f205c09854853172a446c92aa81eb7199da324ab/vllm/transformers_utils/config.py#L57-L61

https://github.com/vllm-project/vllm/blob/f205c09854853172a446c92aa81eb7199da324ab/vllm/transformers_utils/config.py#L110-L112

https://github.com/vllm-project/vllm/blob/f205c09854853172a446c92aa81eb7199da324ab/vllm/transformers_utils/tokenizer.py#L98-L103

Isotr0py commented 2 months ago

@mgoin I think we can use GGUF magic number to achieve this easily:

313174776-c3623641-3a1d-408e-bfaf-1b7c4e16aa63