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feat(gliformer): add opt-in exact encoder CUDA graphs - #796
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Check name Status Explanation Linked Issues check Check skipped because no linked issues were found for this pull request. Out of Scope Changes check Check skipped because no linked issues were found for this pull request. Description Check Check skipped - CodeRabbit’s high-level summary is enabled. Title check The title clearly and concisely describes the main change: adding opt-in exact encoder CUDA graphs for GLiFormer.
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Review comments at
@packages/sie_server/src/sie_server/adapters/gliformer/cuda_graphs.py:
- Around line 65-66: Update the snapshot handling in the graph-capture code to
call `torch.cuda.memory_snapshot` without arguments, then filter the returned
segments by `segment_pool_id` matching `graph.pool()`. Keep the existing
unavailable-snapshot behavior, and update affected mocks to expect a no-argument
call.
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packages/sie_server/src/sie_server/adapters/gliformer/cuda_graphs.pypackages/sie_server/tests/adapters/test_gliformer_graphs.py
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Fixed in eeb5673. The pinned Torch 2.9.1 pool-argument binding owns borrowed tuple references; capture accounting now calls memory_snapshot() without arguments and filters the exact segment_pool_id in Python. Existing strict per-pool/device/size checks and eager fallback are retained. The focused controls passed (43 CPU cases; four real-CUDA cases remain pending the separately bounded GPU proof). Please review the latest head. @coderabbitai review |
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@coderabbitai review Please review exact head 824462e. This follow-up precomputes LayoutDeBERTa's original CPU FP32 attention scalar before CUDA capture, using a temporary instance and recording-thread override with exact restoration. The cached scalar is included in graph storage accounting and release. Eager/default and replay methods are unchanged. The two prior bounded GPU attempts remain failed; the corrected source is not yet GPU-qualified. |
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@coderabbitai review Please review the current exact-only follow-up. Bucketed mode is now rejected at configuration and runner/shape admission after its retained pretrained parity failure. Capture/replay/scalar/memory/cleanup execution is unchanged from the bitwise-verified exact branch. The other correction gives the CI thread-isolation test a same-thread eager oracle without changing its exact-equality or routing assertions. |
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svonava
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Short GLiFormer extraction calls spend much of their time launching the text encoder's CUDA kernels. This adds the opt-in load-time setting
cuda_graphs: exact, which captures repeated, unchanged input shapes for supported text-only DeBERTa encoders. The default remainsoff. Word gathering, the packed word RNN, task heads, validation, metering and decoding keep their existing execution paths.Each shape owns a private graph pool and replay stream; returned outputs belong to the caller. Recording follows the existing lock, rate limit, shape bounds, headroom and 4% device-memory budget. Unsupported inputs and capture failures use eager execution. Optional release and unload free graph storage and restore the original model attributes.
The pinned L4 experiment used
knowledgator/gliformer-large-v1at revisiond0a4e53d09cebe6bc963dd9be319d4279084bb2d, fp16, Torch 2.9.1, Transformers 4.57.6 and GLiFormer 0.1.2. All 33 exact-mode parity calls, including all task fixtures and dense embeddings, matched eager outputs and observed encoder/head arrays bit-for-bit. Private-pool accounting, output ownership, release, recapture and unload checks passed.Native
adapter.extractlatency used the fixed four short typed-decision records (42–44 compiled tokens), six balanced process blocks, 30 warmups and 200 timed calls per arm. All six preplanned pairs are included:The original three-mode experiment remains failed overall. Bucketed mode exceeded the unchanged tensor/output bounds, including valid tokens and six fixture outputs; it is now explicitly rejected rather than granted wider tolerances. The final restriction preserves the tested exact capture/replay/accounting/cleanup methods unchanged. These results measure native extraction on this fixed L4 workload, not HTTP throughput or all-model performance. Earlier import-admission and Layout capture failures are also retained. Complete experiment archive: SHA-256
3f3be1e56b41537c6e1bdcb776515763586192b83bc8bff0d853c67770fcce48(355 verified files).Validation: 65 focused CPU tests passed; two actual-CUDA tests were skipped locally. The prior GPU run executed all four original CUDA controls successfully. Ruff and scoped typecheck pass. The Linux CI fixture now compares eager and overridden outputs on the same worker thread while retaining exact equality and helper-isolation checks. Full CI and CodeRabbit review must pass on the final head.
Refs #374.
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