[6/N] MoE Refactor: Cleanup MoE-related configs (#8849)

This commit is contained in:
Cheng Wan
2025-08-14 21:14:53 -07:00
committed by GitHub
parent 584e1ab2d0
commit 295895120d
69 changed files with 956 additions and 1037 deletions

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@@ -213,12 +213,11 @@ Please consult the documentation below and [server_args.py](https://github.com/s
| Arguments | Description | Defaults |
|-----------|-------------|----------|
| `--ep-size` | The expert parallelism size. | 1 |
| `--moe-a2a-backend` | Select the backend for all-to-all communication for expert parallelism. | None |
| `--enable-flashinfer-cutlass-moe` | Enabling Flashinfer Cutlass MoE implementation for high throughput. | False |
| `--enable-flashinfer-trtllm-moe` | Enabling Flashinfer Trtllm MoE implementation for low latency. | False |
| `--moe-a2a-backend` | Select the backend for all-to-all communication for expert parallelism. | none |
| `--moe-runner-backend` | Select the runner backend for MoE. | 'triton' |
| `--deepep-mode` | Select the mode when enable DeepEP MoE, could be `normal`, `low_latency` or `auto`. Default is `auto`, which means `low_latency` for decode batch and `normal` for prefill batch. | auto |
| `--ep-num-redundant-experts` | Allocate this number of redundant experts in expert parallel. | 0 |
| `--ep-dispatch-algorithm` | The algorithm to choose ranks for redundant experts in expert parallel. | None |
| `--ep-dispatch-algorithm` | The algorithm to choose ranks for redundant experts in EPLB. | None |
| `--init-expert-location` | Initial location of EP experts. | trivial |
| `--enable-eplb` | Enable EPLB algorithm. | False |
| `--eplb-algorithm` | Chosen EPLB algorithm. | auto |
@@ -280,7 +279,6 @@ Please consult the documentation below and [server_args.py](https://github.com/s
| `--disable-chunked-prefix-cache` | Disable chunked prefix cache. | False |
| `--disable-fast-image-processor` | Disable fast image processor. | False |
| `--enable-return-hidden-states` | Enable returning hidden states. | False |
| `--enable-triton-kernel-moe` | Enable Triton kernel for MoE. | False |
## Debug tensor dumps