# `wai.audio.int_codec` — the committed vector

**Provenance.** Generated here. The signal the codec is trained on, and the clip the
vector codes, are written by `tools/wai_int_audio_export.py` itself from a seed: 16 kHz,
mono, signed 16-bit, a sequence of tones, chirps, noise bursts and speech-like formant
sweeps. The tool reads no audio file. Apache-2.0, like the rest of the repository.

- `audio_model.bin` — the integer synthesis (`WAM1`): 16 latent channels, four
  transposed convolutions with integer IGDN between them.
- `audio_bitstream.json` — the export's JSON form: the latent (16 × 512), its
  per-channel tables and its rANS stream. `audio_bitstream.wia1` is the same bitstream
  as a `WIA1` payload, converted by `wai_int_payload_vectors gen`.
- `audio.json` — the decoded PCM's FNV-1a, its sample count (8192) and its rate.
- `sha256.json` — the decoded PCM's SHA-256 (SPEC §7 *Digests*), written by
  `WAI_WRITE_SHA256_SIDECARS=1 cargo test --test int_kernels_vectors int_audio_clip`
  after the decode has reproduced `audio.json`'s FNV-1a.

**How it was made.** From `wai/`, with torch 2.14.1, numpy 1.26.4 and CompressAI 1.2.8
on an arm64 host:

    python tools/wai_int_audio_export.py <out> --seed 1 --channels 16 --samples 8192 --steps 2500

then `audio_model.bin`, `audio_bitstream.json` and `audio.json` copied from `<out>`.
The seed is **1**: stream 0 of the seed is the training signal (8 s), stream 1 the coded
clip. Training is seeded from the same seed, with deterministic algorithms and four
threads. Two runs gave byte-identical files. A different host or torch build may train
to different weights; the committed files are what conformance checks, and their
decode is integer and the same everywhere.

The signal alone needs only the Python standard library:

    python3 tools/wai_int_audio_export.py --signal-only clip.s16 --seed 1 --stream 1 --samples 8192

The site's demo clip is an export of the same tool with the same seed and the
command's defaults (32 channels, 32768 samples, 3500 steps).

**Checked.** `tools/wai_audio_provenance_check.py` correlates the decoded clip (the
staged-delivery case `audio_int_codec_1l`'s stage 0) against the reference recordings
the CI host has, and fails above 0.5.