[Bug]: can't pickle model config error on V0 engine for deepseek-r1

[cjackal]

Your current environment

AFAICT it happens regardless of the GPU arch

the particular version that I have tested is:

vLLM API server version 0.8.0rc2.dev9+g6eaf1e5c (for cuda)

🐛 Describe the bug

When VLLM_USE_V1=0, launching vLLM server with --trust-remote-code fails with the following error - Can't pickle <class 'transformers_modules.configuration_deepseek.DeepseekV3Config'>: it's not the same object as transformers_modules.configuration_deepseek.DeepseekV3Config

traceback

INFO 03-17 21:48:11 [__init__.py:256] Automatically detected platform cuda.
WARNING 03-17 21:48:13 [api_server.py:750] LoRA dynamic loading & unloading is enabled in the API server. This should ONLY be used for local development!
INFO 03-17 21:48:13 [api_server.py:972] vLLM API server version 0.8.0rc2.dev9+g6eaf1e5c
INFO 03-17 21:48:13 [api_server.py:973] args: Namespace(subparser='serve', model_tag='/app/model/deepseek-r1-gguf-q2-k-xl/DeepSeek-R1-UD-Q2_K_XL.gguf', config='', host='0.0.0.0', port=8080, 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, chat_template_content_format='auto', response_role='assistant', ssl_keyfile=None, ssl_certfile=None, ssl_ca_certs=None, enable_ssl_refresh=False, ssl_cert_reqs=0, root_path=None, middleware=[], return_tokens_as_token_ids=False, disable_frontend_multiprocessing=False, enable_request_id_headers=False, enable_auto_tool_choice=False, tool_call_parser=None, tool_parser_plugin='', model='/app/model/deepseek-r1-gguf-q2-k-xl/DeepSeek-R1-UD-Q2_K_XL.gguf', task='auto', tokenizer='/app/model/deepseek-r1-gguf-q2-k-xl/', hf_config_path='/app/model/deepseek-r1-gguf-q2-k-xl/', skip_tokenizer_init=False, revision=None, code_revision=None, tokenizer_revision=None, tokenizer_mode='auto', trust_remote_code=True, allowed_local_media_path=None, download_dir=None, load_format='auto', config_format=<ConfigFormat.AUTO: 'auto'>, dtype='auto', kv_cache_dtype='auto', max_model_len=16384, guided_decoding_backend='xgrammar', logits_processor_pattern=None, model_impl='auto', distributed_executor_backend=None, pipeline_parallel_size=1, tensor_parallel_size=4, enable_expert_parallel=False, max_parallel_loading_workers=None, ray_workers_use_nsight=False, block_size=None, enable_prefix_caching=None, disable_sliding_window=False, use_v2_block_manager=True, num_lookahead_slots=0, seed=None, swap_space=4, cpu_offload_gb=0, gpu_memory_utilization=0.9, num_gpu_blocks_override=None, max_num_batched_tokens=4096, max_num_partial_prefills=1, max_long_partial_prefills=1, long_prefill_token_threshold=0, max_num_seqs=None, max_logprobs=20, disable_log_stats=False, quantization=None, rope_scaling=None, rope_theta=None, hf_overrides=None, enforce_eager=False, 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, mm_processor_kwargs=None, disable_mm_preprocessor_cache=False, enable_lora=False, enable_lora_bias=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, use_tqdm_on_load=True, multi_step_stream_outputs=True, scheduler_delay_factor=0.0, enable_chunked_prefill=True, speculative_model=None, speculative_model_quantization=None, num_speculative_tokens=None, speculative_disable_mqa_scorer=False, 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=['deepseek-ai/deepseek-r1'], qlora_adapter_name_or_path=None, show_hidden_metrics_for_version=None, otlp_traces_endpoint=None, collect_detailed_traces=None, disable_async_output_proc=False, scheduling_policy='fcfs', scheduler_cls='vllm.core.scheduler.Scheduler', override_neuron_config=None, override_pooler_config=None, compilation_config=None, kv_transfer_config=None, worker_cls='auto', worker_extension_cls='', generation_config='auto', override_generation_config=None, enable_sleep_mode=False, calculate_kv_scales=False, additional_config=None, enable_reasoning=True, reasoning_parser='deepseek_r1', disable_log_requests=False, max_log_len=None, disable_fastapi_docs=False, enable_prompt_tokens_details=False, enable_server_load_tracking=False, dispatch_function=<function ServeSubcommand.cmd at 0x7fa13df06950>)
INFO 03-17 21:48:13 [config.py:208] Replacing legacy 'type' key with 'rope_type'
INFO 03-17 21:48:19 [config.py:583] This model supports multiple tasks: {'score', 'reward', 'classify', 'embed', 'generate'}. Defaulting to 'generate'.
WARNING 03-17 21:48:19 [config.py:662] gguf quantization is not fully optimized yet. The speed can be slower than non-quantized models.
INFO 03-17 21:48:19 [config.py:1499] Defaulting to use mp for distributed inference
INFO 03-17 21:48:19 [config.py:1677] Chunked prefill is enabled with max_num_batched_tokens=4096.
INFO 03-17 21:48:20 [cuda.py:159] Forcing kv cache block size to 64 for FlashMLA backend.
INFO 03-17 21:48:20 [api_server.py:236] Started engine process with PID 353
INFO 03-17 21:48:23 [__init__.py:256] Automatically detected platform cuda.
WARNING 03-17 21:48:24 [api_server.py:750] LoRA dynamic loading & unloading is enabled in the API server. This should ONLY be used for local development!
INFO 03-17 21:48:25 [llm_engine.py:241] Initializing a V0 LLM engine (v0.8.0rc2.dev9+g6eaf1e5c) with config: model='/app/model/deepseek-r1-gguf-q2-k-xl/DeepSeek-R1-UD-Q2_K_XL.gguf', speculative_config=None, tokenizer='/app/model/deepseek-r1-gguf-q2-k-xl/', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=True, dtype=torch.bfloat16, max_seq_len=16384, download_dir=None, load_format=gguf, tensor_parallel_size=4, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=gguf, enforce_eager=False, kv_cache_dtype=auto,  device_config=cuda, decoding_config=DecodingConfig(guided_decoding_backend='xgrammar', reasoning_backend='deepseek_r1'), observability_config=ObservabilityConfig(show_hidden_metrics=False, otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=None, served_model_name=deepseek-ai/deepseek-r1, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=None, chunked_prefill_enabled=True, use_async_output_proc=True, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=None, compilation_config={"splitting_ops":[],"compile_sizes":[],"cudagraph_capture_sizes":[256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],"max_capture_size":256}, use_cached_outputs=True, 
WARNING 03-17 21:48:25 [multiproc_worker_utils.py:310] Reducing Torch parallelism from 96 threads to 1 to avoid unnecessary CPU contention. Set OMP_NUM_THREADS in the external environment to tune this value as needed.
INFO 03-17 21:48:25 [custom_cache_manager.py:19] Setting Triton cache manager to: vllm.triton_utils.custom_cache_manager:CustomCacheManager
ERROR 03-17 21:48:25 [engine.py:443] Can't pickle <class 'transformers_modules.configuration_deepseek.DeepseekV3Config'>: it's not the same object as transformers_modules.configuration_deepseek.DeepseekV3Config
ERROR 03-17 21:48:25 [engine.py:443] Traceback (most recent call last):
ERROR 03-17 21:48:25 [engine.py:443]   File "/app/.venv/lib/python3.10/site-packages/vllm/engine/multiprocessing/engine.py", line 431, in run_mp_engine
ERROR 03-17 21:48:25 [engine.py:443]     engine = MQLLMEngine.from_vllm_config(
ERROR 03-17 21:48:25 [engine.py:443]   File "/app/.venv/lib/python3.10/site-packages/vllm/engine/multiprocessing/engine.py", line 126, in from_vllm_config
ERROR 03-17 21:48:25 [engine.py:443]     return cls(
ERROR 03-17 21:48:25 [engine.py:443]   File "/app/.venv/lib/python3.10/site-packages/vllm/engine/multiprocessing/engine.py", line 80, in __init__
ERROR 03-17 21:48:25 [engine.py:443]     self.engine = LLMEngine(*args, **kwargs)
ERROR 03-17 21:48:25 [engine.py:443]   File "/app/.venv/lib/python3.10/site-packages/vllm/engine/llm_engine.py", line 280, in __init__
ERROR 03-17 21:48:25 [engine.py:443]     self.model_executor = executor_class(vllm_config=vllm_config, )
ERROR 03-17 21:48:25 [engine.py:443]   File "/app/.venv/lib/python3.10/site-packages/vllm/executor/executor_base.py", line 271, in __init__
ERROR 03-17 21:48:25 [engine.py:443]     super().__init__(*args, **kwargs)
ERROR 03-17 21:48:25 [engine.py:443]   File "/app/.venv/lib/python3.10/site-packages/vllm/executor/executor_base.py", line 52, in __init__
ERROR 03-17 21:48:25 [engine.py:443]     self._init_executor()
ERROR 03-17 21:48:25 [engine.py:443]   File "/app/.venv/lib/python3.10/site-packages/vllm/executor/mp_distributed_executor.py", line 90, in _init_executor
ERROR 03-17 21:48:25 [engine.py:443]     worker = ProcessWorkerWrapper(result_handler,
ERROR 03-17 21:48:25 [engine.py:443]   File "/app/.venv/lib/python3.10/site-packages/vllm/executor/multiproc_worker_utils.py", line 171, in __init__
ERROR 03-17 21:48:25 [engine.py:443]     self.process.start()
ERROR 03-17 21:48:25 [engine.py:443]   File "/usr/lib/python3.10/multiprocessing/process.py", line 121, in start
ERROR 03-17 21:48:25 [engine.py:443]     self._popen = self._Popen(self)
ERROR 03-17 21:48:25 [engine.py:443]   File "/usr/lib/python3.10/multiprocessing/context.py", line 288, in _Popen
ERROR 03-17 21:48:25 [engine.py:443]     return Popen(process_obj)
ERROR 03-17 21:48:25 [engine.py:443]   File "/usr/lib/python3.10/multiprocessing/popen_spawn_posix.py", line 32, in __init__
ERROR 03-17 21:48:25 [engine.py:443]     super().__init__(process_obj)
ERROR 03-17 21:48:25 [engine.py:443]   File "/usr/lib/python3.10/multiprocessing/popen_fork.py", line 19, in __init__
ERROR 03-17 21:48:25 [engine.py:443]     self._launch(process_obj)
ERROR 03-17 21:48:25 [engine.py:443]   File "/usr/lib/python3.10/multiprocessing/popen_spawn_posix.py", line 47, in _launch
ERROR 03-17 21:48:25 [engine.py:443]     reduction.dump(process_obj, fp)
ERROR 03-17 21:48:25 [engine.py:443]   File "/usr/lib/python3.10/multiprocessing/reduction.py", line 60, in dump
ERROR 03-17 21:48:25 [engine.py:443]     ForkingPickler(file, protocol).dump(obj)
ERROR 03-17 21:48:25 [engine.py:443] _pickle.PicklingError: Can't pickle <class 'transformers_modules.configuration_deepseek.DeepseekV3Config'>: it's not the same object as transformers_modules.configuration_deepseek.DeepseekV3Config

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[cjackal]

The same model runs okay with vllm=0.7.4.dev410; I guess something went wrong after setting V1 engine as default?

[DarkLight1337]

See #14925

[afeldman-nm]

@cjackal can you please share the whole CLI command which reproduces this error, including (but not limited to) the specific deepseek r1 model you used? Thanks

[afeldman-nm]

For example I was able to successfully run this command

VLLM_USE_V1=0 vllm serve --trust-remote-code deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B --port 8091

so I am wondering if this is not the model you used

[DarkLight1337]

Based on the other issue, perhaps the error only occurs when directly referencing a local model via filepath?

[cjackal]

For example I was able to successfully run this command

VLLM_USE_V1=0 vllm serve --trust-remote-code deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B --port 8091

so I am wondering if this is not the model you used

Deepseek distill qwen models belong to Qwen2 model architecture, you may try a deepseekV2 model architecture for reproducibility. I think DeepSeek-V2-Lite is the smallest.

What I'm using is https://huggingface.co/unsloth/DeepSeek-R1-GGUF/tree/main/DeepSeek-R1-UD-Q2_K_XL, but as GGUF models must first be joined you need to first download the model binary to local filepath and follow this. The specific launch command should look like:

VLLM_USE_V1=0 vllm serve /app/model/deepseek-r1-gguf-q2-k-xl/DeepSeek-R1-UD-Q2_K_XL.gguf --served-model-name deepseek-ai/deepseek-r1 --tokenizer /app/model/deepseek-r1-gguf-q2-k-xl/ --hf-config-path /app/model/deepseek-r1-gguf-q2-k-xl/ --trust-remote-code ...