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We identified a configuration mismatch preventing successful vLLM testing due to parameter constraints. Following a review with @tsai1247, we recommend that @ZoneTwelve submit a hotfix to this PR incorporating the required configuration adjustments.

(APIServer pid=11098)   Value error, max_num_batched_tokens (4096) is smaller than max_model_len (40960). This effectively limits the maximum sequence length to max_num_batched_tokens and makes vLLM reject longer sequences. Please increase max_num_batched_tokens or decrease max_model_len. [type=value_error, input_value=ArgsKwargs((), {'runner_t..., 'stream_interval': 1}), input_type=ArgsKwargs]

Please hot fix the optuna range (at file: vllm/benchmarks/sweep/serve_optuna.py):

DEFAULT_VLLM_SEARCH_SPACE: dict[str, Any] = {
    "gpu_memory_utilization": {
        "type": "float",
        "low": 0.5,
        "high": 0.98,
        "step": 0.02,
    },
    "max_num_batched_tokens": {
        "type": "categorical",
        "choices": [None, 512, 1024, 2048, 4096, 8192, 10240, 20480, 40960, 81920, 102400],
    },
    "max_num_seqs": {
        "type": "categorical",
        "choices": [None, 4, 8, 16, 32, 64, 128, 256, 512, 1024],
    },
    "enable_chunked_prefill": {"type": "bool"},
    "enable_prefix_caching": {"type": "bool"},
}

fix: _start_best_server will not create a new subprocess now. It works like the normal vllm serve command

fix: _start_best_server will not create a new subprocess now. It works like the normal vllm serve command

Thanks for the immediate patch. This issue is being referenced in our Notion: Container Exit Post-Evaluation