The version bump (transformers 5.8.1, torch 2.11+cu130, sglang dev) broke the
existing plain-Qwen3 math recipes (qwen3-1.7b, qwen3-8b). Two fixes:

1. fsdp_engine.py: always pass attention_mask=None for the packed/varlen forward.
   The old dict(full_attention=None, sliding_attention=None) form is a
   transformers-4.x relic; on transformers>=5 a dense model (qwen3/qwen2) treats
   that dict as a *precomputed* mask, skips creation, and crashes ('dict' object
   has no attribute 'ndim'). None is correct for all archs (dense, moe, vl,
   qwen3.5/GDN) — masking is driven by cu_seqlens + position_ids. Subsumes the
   prior qwen3_5/moe/vl special-case (drop now-unused imports).

2. recipes + cli_args: set attn_impl: sdpa in actor+ref for qwen3-1.7b and
   qwen3-8b recipes (flash_attn is ABI-broken vs torch 2.11+cu130 -> import crash;
   default was flash_attention_2). Expand attn_impl choices to sdpa/eager.

Verified end-to-end: qwen3-1.7b full + delta train cleanly to step 100 on the
bumped stack; math500 avg@k rises 73.0->77.0 (full) / 72.2->78.8 (delta);
importance_weight=1.0000 (packed forward correct); zero crashes.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

….8.1)

The published sglang 0.5.12.post1 predates qwen3_5 and pins transformers 5.6.x,
so it is incompatible with the transformers==5.8.1 the recipes require. Pin
sglang to the validated main-branch build (sgl-project/sglang @ 373cadc9): it
ships qwen3_5 + TritonGDNKernel and itself requires transformers==5.8.1,
flashinfer 0.6.11.post1, torch 2.11.0, kernels<0.15 -- all matching the
validated env. Update the [tool.uv] comments to match.

Verified: every pin/override matches the working astraflow35 env (transformers
5.8.1, kernels 0.14.1, outlines-core 0.1.26, torch 2.11.0, sglang @ g373cadc92).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Comment-only alignment of the Qwen3.5 recipes + touched code to the repo's
conventions (qwen3-8b recipes / surrounding code as the baseline):
- recipe experiment.yaml/raas.yaml: restore the "# -- ... --" section banners
  and the auto-derives / adaptive-availability rationale comments the dense
  recipes use; restyle the attn_impl comment to sentence-case prose.
- model.py: capitalize the qwen3_5 registry comment to match the file.
- fsdp_engine.py: reflow the attention_mask comment so dict(...) is not split
  mid-token, matching the file's other multi-line comments.
- pyproject.toml: reflow the sglang-extra comment to the column band.
- README: tag the GPU-layout code fence (text).
No functional content changed (verified: all yaml/sh/py/toml parse; only comment
lines were added/removed).

Also refresh the recipe README install note, which still described SGLang as
pinned at 0.5.12.post1 before the git-build pin landed.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

… 3.6.1

Two pyproject fixes so a clean install reproduces the validated astraflow35 env:
- Add flash-linear-attention==0.5.0 to the sglang extra: the fast Gated-DeltaNet
  kernels Qwen3.5 GDN training used in the validated runs (optional --
  transformers falls back to a slower pure-torch path when absent). Pulls
  fla-core==0.5.0.
- networkx==3.3 -> 3.6.1 to match the validated env (the only pinned version that
  differed from astraflow35).

Verified: uv pip install --dry-run -e ".[sglang]" resolves cleanly (299
packages, exit 0) to the validated versions (flash-linear-attention 0.5.0,
fla-core 0.5.0, networkx 3.6.1, transformers 5.8.1, sglang @ 373cadc9, ...).
All other pinned ML versions already matched astraflow35; the ~60 loose utility
deps are left flexible per the repo's convention.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Switch the dense Qwen3 math recipes (qwen3-1.7b-m2po-2gpus-{full,delta},
qwen3-8b-m2po-{full,delta}) and the cli_args attn_impl default to
kernels-community/flash-attn2 -- a prebuilt, ABI-matched FlashAttention-2
kernel from the HF kernels hub (cached on first use, no source build).

The literal flash_attention_2 loads the local flash-attn wheel, which is
ABI-broken on torch 2.11+cu130 (undefined symbol); is_flash_attn_2_available()
only checks package metadata so it reports available and then crashes on import.
The kernels-hub variant is ABI-matched and is the upstream-faithful FA2 the
recipes were tuned with. A paired step-25 A/B/C on qwen3-1.7b-m2po-2gpus-full
gave overall avg@k FA2 >= sdpa >= sdpa+recompute_logprob, all within eval noise;
FA2 varlen also derives the packed block-diagonal mask from cu_seqlens, avoiding
sdpa's reliance on position_ids resets. Qwen3.5 recipes stay on sdpa.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

…ild)

Switch the [sglang] extra from the git build (373cadc9) to the published
sglang==0.5.13.post1 -- the release the recipes were recently validated against,
which ships qwen3_5 support (sglang/srt/models/qwen3_5.py) so it covers both the
Qwen3.5 and Qwen3-dense recipes. Update the Qwen3.5 READMEs' validated-stack
tables to match (sglang 0.5.13.post1, flashinfer 0.6.12). The flash-attn-4
pre-release / transformers 5.8.1 / kernels 0.14.x [tool.uv] overrides are
unchanged (0.5.13.post1 still pulls flash-attn-4 4.0.0b15).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Both full and delta variants re-run end-to-end on the published-release pin
(sglang==0.5.13.post1): training completes, full + delta weight transfer both
work, eval holds at baseline (~49-51% overall avg@k) -- no regression vs the
predecessor git build the step0->step80 table was produced on.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>