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docs: drop the per-override name rule and tidy bundle comments
Every launch renames the bound recipe and fingerprints exclude name, so bundles need not set one per override. Drop a misindented commented-out flag and move the NATS comment above request_plane.
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‎inferencex-e2e/benchmarks/multi_node/srt-slurm-recipes/RECIPES.md‎

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@@ -20,7 +20,7 @@ qwen3.5/trtllm/gb300-fp4/agentx/disagg-variants.yaml
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- Workloads are `1k1k`, `8k1k`, or `agentx`. Existing bundles spanning several fixed sequence lengths use `fixed-seq-len`; keep their override selectors intact.
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- Use lowercase, hyphen-separated filenames beginning with `agg` or `disagg`. Include topology and the settings that distinguish sibling recipes, such as parallelism, batch size, concurrency, MTP, offload, or cache configuration. Avoid dates, numbered latency/throughput labels, and repeating the model or hardware already in the path.
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- In topology names, `1p4d` denotes prefill/decode worker counts, not necessarily physical nodes. Role-qualified `p-tp4` and `d-tp8` identify prefill/decode TP; `b` denotes batch size and `c` concurrency. The YAML is authoritative for runtime settings.
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- A master-config entry with two or more rows of one recipe design keeps them in one `<agg|disagg>[-<axis>]-variants.yaml`; the axis only tells bundles in one directory apart. `base` holds everything the points share, with `schema: 2` beside it, and each row gets one plain `override_<topology>_c<conc>` block (or a similarly point-identifying name, without dates or hardware) holding only its deltas, including its `name`. An override's `null` deletes the base key, so a null that a point needs, such as TensorRT-LLM's `cuda_graph_config:`, stays in `base`. Rows select it with `srt-recipe: <bundle>.yaml:override_<name>`, relative to `srt-recipe-dir`. Do not add `zip_override_*` blocks or share a bundle across entries, and keep one override per row: recipe references participate in eval grouping. Standalone files remain for single-row entries, adapted upstream recipes whose `# Source:` base materially differs, and points too different to share a base, such as a TP low-latency recipe beside wide-EP ones.
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- A master-config entry with two or more rows of one recipe design keeps them in one `<agg|disagg>[-<axis>]-variants.yaml`; the axis only tells bundles in one directory apart. `base` holds everything the points share, with `schema: 2` beside it, and each row gets one plain `override_<topology>_c<conc>` block (or a similarly point-identifying name, without dates or hardware) holding only its deltas. An override's `null` deletes the base key, so a null that a point needs, such as TensorRT-LLM's `cuda_graph_config:`, stays in `base`. Rows select it with `srt-recipe: <bundle>.yaml:override_<name>`, relative to `srt-recipe-dir`. Do not add `zip_override_*` blocks or share a bundle across entries, and keep one override per row: recipe references participate in eval grouping. Standalone files remain for single-row entries, adapted upstream recipes whose `# Source:` base materially differs, and points too different to share a base, such as a TP low-latency recipe beside wide-EP ones.
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- Update `srt-recipe-dir`, `srt-recipe`, and `eval-srt-recipe` references in master configs, launcher path rules, workflow filters, and local documentation together when moving a file. Preserve upstream source URLs as provenance and leave historical performance-changelog entries unchanged. No aliases for the old layout are provided.
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Shared runtime assets stay under `configs/` beside the model directories; they are not standalone recipes. The four files in `configs/dsv4-moe-load-balancer-configs/` are copied verbatim from NVIDIA/srt-slurm commit `deb1dfd9934398664f92d194169c183e009da83b`, preserving the EPLB initial expert assignments formerly used by the DSV4 TRT recipes; no checked-in recipe currently references them. The srt driver ([`infx/launch/drivers/srt/checkout.py`](../../../infx/launch/drivers/srt/checkout.py)) stages them into the job checkout's `configs/` directory for the recipes' bind mounts. Keeping a recipe in this tree does not activate it; the master configs determine the benchmark matrix.

‎inferencex-e2e/benchmarks/multi_node/srt-slurm-recipes/dsr1/sglang/b200-fp8/8k1k/disagg-stp-variants.yaml‎

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watchdog-timeout: 1000000
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enable-flashinfer-allreduce-fusion: true
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disable-radix-cache: true
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# disable-chunked-prefix-cache: true
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health_check:
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max_attempts: 360

‎inferencex-e2e/benchmarks/multi_node/srt-slurm-recipes/dsr1/sglang/gb200-fp8/8k1k/disagg-dep-stp-variants.yaml‎

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base:
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dynamo:
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# Use NATS for a recipe prior to Dynamo commit 39d2a68.
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request_plane: "nats"
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source:
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pypi: 0.8.1
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# Use NATS for a recipe prior to Dynamo commit 39d2a68.
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frontend:
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type: dynamo

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