[Refactor] Refactor DeepEP dispatcher (#22822)
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> Co-authored-by: Cheng Wan <54331508+ch-wan@users.noreply.github.com>
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Cheng Wan
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@@ -1472,6 +1472,12 @@ Please consult the documentation below and [server_args.py](https://github.com/s
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}><code>auto</code></td>
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}><code>normal</code>, <code>low_latency</code>, <code>auto</code></td>
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<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}><code>--deepep-dispatcher-output-dtype</code></td>
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Select DeepEP dispather output dtype, could be <code>bf16</code>, <code>fp8</code>, <code>int8</code> (only Ascend A2/A3 NPU), <code>nvfp4</code> or <code>auto</code>. Default is <code>auto</code>, which follows a priority order (server argument → deprecated env var → input_global_scale check → dispatcher_output_dtype from quant_config → flashinfer/cutlass backend → NPU BF16 default → GPU FP8 default).</td>
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}><code>auto</code></td>
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}><code>bf16</code>, <code>fp8</code>, <code>int8</code>, <code>nvfp4</code>, <code>auto</code></td>
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</tr>
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<td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}><code>--ep-num-redundant-experts</code></td>
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<td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Allocate this number of redundant experts in expert parallel.</td>
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