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fix(llama-cpp): cap single-pass embedding batch to fit VRAM (#10695)
发布于
2026-07-06 10:56:09 +00:00 | 991 次提交 在此版本后已推送到 master- fix(llama-cpp): cap single-pass embedding batch to fit VRAM
Embedding/score/rerank all decode or pool the whole input in one physical
batch, so EffectiveBatchSize sized the batch to the full context window. For
a large context that makes n_ubatch huge, and the per-device CUDA compute
buffer (forward-graph scratch, ~n_ubatch * n_ctx, NOT split across GPUs)
balloons into multi-GiB: a large-context embedding model then aborts on load
(exitCode=-1) even with plenty of free VRAM. Reproduced with qwen3-embedding-4b
(context 40960 -> n_batch 40960 -> abort) and qwen3-embedding-0.6b
(n_batch 8192); pinning batch:512 avoided it.This is the same root cause as issue #10485 (a large context turns the batch
into multi-GiB of scratch that must fit on a SINGLE card), but the single-pass
path bypassed the VRAM headroom guard the config layer already had — it
returned the unbounded context as the batch with no GPU awareness.Make the single-pass batch VRAM-aware: cap it to the largest batch whose
compute buffer fits the per-device VRAM headroom, clamped to
[DefaultPhysicalBatch, ctx], reusing the existing computeBufferBytesPerCell and
headroom-divisor math (no duplication). Unknown per-device VRAM (0) stays
conservative (DefaultPhysicalBatch, not the context) so a detection gap can't
OOM. The GPU is resolved through an injectable package var (config.LocalGPU,
backed by sync.Once-cached xsysinfo detection) so the per-request router call
stays cheap and tests inject a deterministic device. Explicit batch: still
wins. An input longer than the cap can no longer be pooled in one pass — the
accepted tradeoff, since a batch that OOMs the device processes nothing.Assisted-by: Claude:claude-opus-4-8 golangci-lint go-test
Signed-off-by: Ettore Di Giacinto mudler@localai.io- fix(config): single-pass batch follows context on unknown VRAM
The single-pass (embedding/score/rerank) batch cap must only shrink the batch
when the per-device VRAM ceiling is KNOWN. On unknown VRAM (CPU-only or a GPU
detection gap) SinglePassBatchForContext returned DefaultPhysicalBatch, which
under-sized the batch below the context — over-trimming score/embed/rerank
inputs (the modelTokenTrim middleware regression) with no OOM benefit on CPU
where the compute buffer lives in system RAM. Return the full context instead,
preserving the original single-pass behavior; the VRAM cap stays a downward
safety that only engages when VRAM is known.Assisted-by: Claude:claude-opus-4-8 [go-test go-vet]
Signed-off-by: Ettore Di Giacinto mudler@localai.io
Signed-off-by: Ettore Di Giacinto mudler@localai.io
Co-authored-by: Ettore Di Giacinto mudler@localai.io下载附件