[Misc][Benchmark] Add support for CustomDataset (#18511)
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@@ -64,6 +64,12 @@ become available.
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<td style="text-align: center;">✅</td>
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<td><code>lmms-lab/LLaVA-OneVision-Data</code>, <code>Aeala/ShareGPT_Vicuna_unfiltered</code></td>
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</tr>
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<tr>
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<td><strong>Custom</strong></td>
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<td style="text-align: center;">✅</td>
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<td style="text-align: center;">✅</td>
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<td>Local file: <code>data.jsonl</code></td>
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</tr>
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</tbody>
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</table>
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@@ -124,6 +130,38 @@ P99 ITL (ms): 8.39
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==================================================
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```
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### Custom Dataset
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If the dataset you want to benchmark is not supported yet in vLLM, even then you can benchmark on it using `CustomDataset`. Your data needs to be in `.jsonl` format and needs to have "prompt" field per entry, e.g., data.jsonl
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```
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{"prompt": "What is the capital of India?"}
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{"prompt": "What is the capital of Iran?"}
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{"prompt": "What is the capital of China?"}
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```
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```bash
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# start server
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VLLM_USE_V1=1 vllm serve meta-llama/Llama-3.1-8B-Instruct --disable-log-requests
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```
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```bash
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# run benchmarking script
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python3 benchmarks/benchmark_serving.py --port 9001 --save-result --save-detailed \
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--backend vllm \
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--model meta-llama/Llama-3.1-8B-Instruct \
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--endpoint /v1/completions \
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--dataset-name custom \
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--dataset-path <path-to-your-data-jsonl> \
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--custom-skip-chat-template \
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--num-prompts 80 \
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--max-concurrency 1 \
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--temperature=0.3 \
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--top-p=0.75 \
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--result-dir "./log/"
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```
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You can skip applying chat template if your data already has it by using `--custom-skip-chat-template`.
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### VisionArena Benchmark for Vision Language Models
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```bash
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@@ -203,6 +241,16 @@ python3 vllm/benchmarks/benchmark_serving.py \
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--seed 42
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```
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**`philschmid/mt-bench`**
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``` bash
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python3 vllm/benchmarks/benchmark_serving.py \
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--model Qwen/QwQ-32B \
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--dataset-name hf \
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--dataset-path philschmid/mt-bench \
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--num-prompts 80
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```
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### Running With Sampling Parameters
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When using OpenAI-compatible backends such as `vllm`, optional sampling
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