v0.20.0

Performance

• The CPU boundary CNN loads with its input shape pinned and its
  convolution padding hoisted. Profiling demux --method cnn on the CPU
  put 38% of all CPU time in tract's padded_valid_x_loop, the per-element
  im2col path it falls back to when pads != 0 — the defect
  escapepod-classify already works around for the charging network. The
  loader also still optimized the graph with length symbolic, a choice
  #187 made obsolete when prep started padding every read to one shape.
  Measured on 119,255 RNA004 reads at 32 threads: 600 → 401 CPU-seconds from
  the input fact alone, 380 with the hoist; sorted per-read classifications
  identical. The rewrite now lives in escapepod_demux::onnx_rewrite and the
  CTC-CRF encoder loader applies it too. Pinning batch 1 means the CPU batch
  entry point runs reads one at a time, which is what CPU batching measured
  against anyway.

• Per-read work on the LLR path is bounded. The fingerprint is computed
  from at most the last MAX_FINGERPRINT_WINDOW (30,000) samples of the
  adapter window, and the LLR detector is handed at most LLR_DECODE_BOUND
  (200,000) samples of a read, in the fused pipeline and in demux detect
  and demux train. Neither touches a real read: adapter windows on a
  MinKNOW RNA004 run sat at 4,070 (median) / 5,120 (p90) samples, and 98% of
  its reads are under the decode bound. What they bound is the read-length
  tail: 2.7% of that run's reads (over 100k samples, up to 11.3M) held 62%
  of all samples, LLR reported "adapter" windows up to 4.6M samples on
  stalled pores, and the pipeline spent its last 6 of 11 seconds on one
  rayon worker fingerprinting one such chunk while the pool idled. With the
  reads the caps target filtered out, wall fell 11.4 → 5.1 s and CPU 61 →
  31 s on node-local input. --method cnn was already bounded and is
  unaffected. ADAPTed's own LLR sees only max_obs_trace samples; adopting
  that would be the parity-improving choice but renormalizes most real reads
  and needs a validation run first.

Fixed

• DtwSvmModel::validate now checks everything the predictor indexes by
  class or pair: thresholds, prob_a/prob_b, the dual_coef row count,
  classes and label_mapper coverage, and n_classes >= 2. A short
  thresholds used to accept every call for the classes past its end; the
  others panicked inside a rayon worker on the first read. A WarpDemuX
  model's threshold_type must be kernel or ratio — anything else
  silently selected the ratio rule. GbmModel::validate refuses a tree with
  a back-edge, which recursed without end in GbmPredictor::new.
• demux train no longer skips an unreadable POD5 (or batch) and exits 0
  with a consensus built from whatever else was there — the #293 failure
  the other stages were cured of in #294.
• demux classify --window with --model is an error rather than silently
  ignored: a DTW-SVM model carries its own window, and the WarpDemuX and
  GBM heads use none. The documented example used it that way.
• demux classify's SVM and GBM status lines go through tracing to
  stderr like every other stage's, so -q silences them and a piped stdout
  stays clean.
• A reads-table row that fails to decode is warned about instead of
  vanishing from the output of every demux stage.
• compute_consensus_fingerprint breaks a tie between equally common
  fingerprint lengths deterministically (shortest wins); it used to fall to
  HashMap iteration order, the last non-determinism in demux train.
• The AVX2 and AVX-512 logsumexp kernels guard the -inf - -inf = NaN of
  an all-unreached lattice cell themselves. chain_head reduces through
  them over the first rows of every --ref-scores scan, and its result was
  correct only because ln8's max(x, MIN_POSITIVE) clamp happened to
  return its second operand on an unordered compare — the accident
  chain_tail's guard was written to stop depending on. Bit-identical for
  every reachable lane; pinned by chain_head_absorbs_unreached.
• The GPU CRF encoder remembers a failed --ref-scores panel upload instead
  of discarding the error and retrying it every batch, and the fused
  pipeline reports the fallback at the end of the run (the host scan it
  falls to is +57% wall, #297).
• GPU DTW-SVM classification returns an error when its producer thread dies
  or returns fewer results than queries; every caller zipped the result with
  its queries, so the missing reads silently dropped out of the output.

Removed

• linfa and linfa-svm from escapepod-demux's train feature. They
  were compiled for every --features train build and never imported; the
  SVM fit has been a labels-only stub since #152.

---

Which artifact

Artifact	Linkage	--gpu
…-x86_64-unknown-linux-musl.tar.gz	static (musl)	no
…-aarch64-unknown-linux-musl.tar.gz	static (musl)	no
…-x86_64-unknown-linux-gnu-gpu.tar.gz	dynamic, glibc ≥ 2.28	yes
…-x86_64-apple-darwin.tar.gz	dynamic	no
…-aarch64-apple-darwin.tar.gz	dynamic	no

The musl builds are the portable default and the right thing for
an unattended installer to fetch. The GPU paths cannot be static —
they dlopen their runtimes — so they ship in the single dynamically
linked …-linux-gnu-gpu artifact instead, built against glibc 2.28
(RHEL/Rocky/Alma 8+, Ubuntu 20.04+).

What …-linux-gnu-gpu needs at run time

Only when --gpu is actually requested — otherwise it behaves
exactly like the musl one. It expects a CUDA 12 runtime and
cuDNN 9, with an NVIDIA driver ≥ 535 (the DTW kernels target the
CUDA 12.2 driver API), and a CUDA-enabled libonnxruntime matching
the ort 2.0.0-rc.13 it links.

Rather than assembling that by hand, see
GPU acceleration,
which covers the pixi environment that supplies it and how to
confirm the CUDA execution provider actually loaded.