docs(rl): stop the verl guide sending readers to a vLLM version it cannot run on

[glamr-agent]

Source issue: DYN-4321.

Overview:

The verl guide pins a combination that cannot be built. The verl core selected by the recipe snapshot the page pins imports FusedMoE from vllm.model_executor.layers.fused_moe.layer at import time. vLLM exports that name up to and including 0.26.0 and renamed it to FusedMoEFactory in 0.27.0, so on ai-dynamo[vllm]==1.5.0, which pins vllm[flashinfer,runai,otel]==0.28.0, the rollout backend raises ImportError: FP8 quantization not available and the Dynamo stack never starts. A reader who works around that stops at ModuleNotFoundError: No module named 'flash_attn', and both documented commands are then rejected during trainer config validation.

Details:

• Prerequisites now list flash-attn as an explicit install: the selected verl reaches flash_attn.bert_padding on the CUDA path with no fallback and declares the dependency nowhere.
• An IMPORTANT note bounds the environment to vLLM 0.26.0 and names the renamed symbol and the exact error.
• Both commands now pass the three _per_gpu micro-batch overrides the pinned verl requires, since it leaves use_dynamic_bsz at false and every micro-batch field at null and neither the smoke script nor the recipe trainer config sets one.
• The training example spells out actor_rollout_ref.rollout.tensor_model_parallel_size=2, the selected verl's own default, so behavior is unchanged and it is now visible that the rollout spans both requested GPUs.

Where should the reviewer start?

The IMPORTANT note, and specifically the number 0.27.0 — one release earlier than the originating report's 0.28.0. vllm/model_executor/layers/fused_moe/layer.py defines FusedMoE through v0.26.0 and FusedMoEFactory from v0.27.0, with no surviving alias and no stable 0.26.1 between them.

Validation

python3 docs/fern/scripts/docs_lint.py --scan docs passes with 0 errors, and pre-commit run --files docs/fern/pages/use-cases/reinforcement-learning/verl.md passes. Each new claim was checked against the pinned upstream source it describes. There is no end-to-end verl run behind this; reproducing the failure needs vLLM 0.27.0 or newer with a full verl training stack.

Related Issues

🚫 This PR is NOT linked to an issue:

• Confirmed — no related issue

Summary by CodeRabbit

• Documentation
  • Updated the reinforcement learning integration guide with explicit flash-attn installation requirements.
  • Documented the supported vLLM version constraint for the selected dependency versions.
  • Added required per-GPU micro-batch and tensor parallelism settings to validation and training commands.
  • Clarified native-router worker layout behavior and configuration expectations.

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[github-actions]

🌿 Fern Docs Preview: https://nvidia-preview-01a08d25-40d4-717c-bf2a-334d85e49040.docs.buildwithfern.com/dynamo/dev

[glamr-agent]

Automated evidence record — validation complete

Validation status: complete

Evidence summary: [2/2 validated]

AI review assessment (advisory, not an approval): sound. An AI agent judged the change logically consistent with the diff and the recorded results. Repository CI and human reviewers decide whether this merges.

Validation result: pass. Both documentation gates ran green against the changed page. The tracker-identifier lint rule was proved to fire on a tampered copy of the page and not on the committed one. Every factual claim in the new prose was confirmed against the exact pinned upstream source it describes, and the patch applies to its base and reproduces the commit.

Evidence audit: complete [2/2 validated] — the command report below comes from recorded runs.

Commands and results [2/2 validated]

Generated from the commands recorded during this run.

Check 1

Checks the changed files with the repository's fast lint and formatting commands.

Result: Passed (exit 0)

Command:

bash -c 'set -e; python3 docs/fern/scripts/docs_lint.py --scan docs; pre-commit run --files docs/fern/pages/use-cases/reinforcement-learning/verl.md --hook-stage manual'

Check 2

Inspects the changed code when the claim cannot be tested with a local command.

Result: Passed (exit 0)

Command:

bash -c 'set -e; for tag in v0.26.0 v0.27.0 v0.27.1 v0.28.0; do src=$(curl -sSfL "https://raw.githubusercontent.com/vllm-project/vllm/$tag/vllm/model_executor/layers/fused_moe/layer.py"); printf "%s  FusedMoE=%s  FusedMoEFactory=%s  definition=%s\n" "$tag" "$(printf "%s" "$src" | grep -cE "\bFusedMoE\b" || true)" "$(printf "%s" "$src" | grep -cE "\bFusedMoEFactory\b" || true)" "$(printf "%s" "$src" | grep -nE "^def FusedMoE" | tr "\n" " " || true)"; done'

[coderabbitai]

No actionable comments were generated in the recent review. 🎉

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📥 Commits

Reviewing files that changed from the base of the PR and between 7650b76 and f11b2ba.

📒 Files selected for processing (1)

• docs/fern/pages/use-cases/reinforcement-learning/verl.md

Included review availability: Your plan provides up to 12 included reviews per hour; 8 remain after this review.

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Walkthrough

The verl integration guide adds explicit installation and version requirements. It updates validation and training commands with micro-batch overrides, tensor parallelism settings, and native-router worker layout guidance.

Changes

verl integration guide

Layer / File(s)	Summary
Dependency prerequisites and compatibility docs/fern/pages/use-cases/reinforcement-learning/verl.md	The guide adds flash-attn installation instructions and requires vLLM 0.26.0 for the documented verl and Dynamo configuration.
Validation and training commands docs/fern/pages/use-cases/reinforcement-learning/verl.md	Validation and training commands now set per-GPU micro-batch values and tensor parallelism. The guide also documents native-router worker layout behavior.

Estimated code review effort: 1 (Trivial) | ~3 minutes

Merge Risk: ⚪ Minimal · up to f11b2

The verl guide now documents compatible dependencies and runnable validation and training commands. No current merge-readiness risk remains.

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly identifies the main change: preventing the verl guide from directing users to an incompatible vLLM version.
Description check	✅ Passed	The description includes all required template sections, explains the compatibility issue and documentation changes, identifies the review focus, documents validation, and provides the required relate…
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check. Docstring coverage is scoped to functions touched by this diff. Analyzed 0 functions across 0…
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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[coderabbitai]

Actionable comments posted: 1

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Inline comments:
In `@docs/fern/pages/use-cases/reinforcement-learning/verl.md`:
- Line 27: Add an executable flash-attn installation command, or an upstream
installation link with the required compatibility guidance, to the setup
instructions before install_verl.sh so clean environments install the dependency
before training.

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📒 Files selected for processing (1)

• docs/fern/pages/use-cases/reinforcement-learning/verl.md

Included review availability: Your plan provides up to 12 included reviews per hour; 9 remain after this review.

[glamr-agent]

CI finished green on head f11b2ba: every check reached a terminal state with no failures and nothing left pending. Docs Lint, pre-commit, Fern Configuration Check, Fern Broken Links Check, Check for broken markdown links, lychee, codeowners, copyright-checks, DCO and pre-merge-status-check all passed. The Rust, operator and recipe jobs were skipped, as this change touches documentation only. No action is needed to advance the checks.

[glamr-agent]

Round 1 — addressed the review finding on docs/fern/pages/use-cases/reinforcement-learning/verl.md about the missing flash-attn installation step.

The page named flash-attn as a prerequisite and stated that the recipe installer does not add it, but no command on the page installed it, so a reader following it top to bottom could still reach ModuleNotFoundError: No module named 'flash_attn'. Prepare the Source now carries an Install flash-attn step:

pip install packaging psutil ninja
MAX_JOBS=4 pip install flash-attn --no-build-isolation

The step records the upstream build constraints that make the command work — PyTorch 2.2 or newer, CUDA 12.0 or newer, why --no-build-isolation is required, and the effect of a broken ninja on build time — and links the FlashAttention project for platform notes and prebuilt wheels. It also records the gpu extra of the selected verl's setup.py as the equivalent route: GPU_REQUIRES = ["liger-kernel", "flash-attn"] at line 50, wired as "gpu" in extras_require at line 66 of the verl commit this recipe snapshot selects. Neither installer path the recipe uses requests that extra.

Commit f11b2ba.

Checks run against the changed file:

python3 docs/fern/scripts/docs_lint.py --scan docs
pre-commit run --files docs/fern/pages/use-cases/reinforcement-learning/verl.md --hook-stage manual

Both passed. Docs lint reported Docs lint passed: 0 errors across 449 scanned files, with no finding on the changed page; every applicable pre-commit hook passed.

[glamr-agent]

/devin review

@coderabbitai full review

[coderabbitai]

@glamr-agent I will perform a complete review of pull request #14571.

✅ Action performed

Full review finished.

[dagil-nvidia]

/ok to test f11b2ba

[dagil-nvidia]

Docs codeowner approval. The vLLM pin and flash-attn steps match what 1.5.0 pins.