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Registers wai.video.int_cond and its frame form wai.video.int_cond.frame, NeuralIntegerExact at decode-equivalence. Each frame's latent is coded given a temporal context, the previous frame's decoded feature (zero for an intra frame): an integer context network over that context gives every latent element's scale and mean, the element is decoded against its scale's table, and an integer conditional decoder and synthesis give the frame and the feature the next frame reads. Every network is a WHM1 network through whm1/1, so every scale, table choice, feature and frame is the encoder's on every decoder. The context is a feature, not pixels, so the decode takes no warp operator and wai-ops/1 gains none. integer-payloads §17 pins WIC1 (a clip of WCF1 frames) and WCF1 (one frame, carried one an object by frame-stream), their checks and decode, and the one-file set WCB1 (model.wcb: ctx, prior, dec, recon and the tables). §17.7 (informative) sets out what lowering DCVC-RT's published weights onto the topology by post-training quantisation takes, as int_hyper was lowered from mbt2018_mean: its blocks are WHG1 graphs of operators wai-ops/1 has, and its hyperprior, spatial passes and rate are what WCF1 does not carry. integer-operators §13.4a adds the lowering wcb1/1 and §13.5 its driver row; SPEC §5 Video rows and the frame-forms text, determinism-tiers rows. wai-rs: int_cond_video (CondModel, plan, load, decode_frame, decode_clip, CondFrames under FrameStream, split, join, corpus); int_payload::wire parses and writes WIC1 and WCF1, which join the magics a format_capability_mismatch names; decode_int decodes the clip; the emit paths parse both payloads. float_free reads int_ops_offload.rs, an integer module its list lacked. wai-ops: lower::wcb1. tools/wai_int_cond_export.py trains the topology on seeded procedural clips, quantises it after training and codes a six-frame 64x64 clip with the integer networks themselves (tests/vectors/int_cond/; its sidecar names its buffer, and tests/int_kernels_vectors.rs holds the clip to it under every kernel policy). int-payload-conformance/int-cond/: the clip's frames, frame streams (clean, two groups, a frame lost, another picture size, a stream that runs out), a fixture for every parse code and the decode's, set fixtures, join refusals. int_payload_verify.py --int-cond decodes the clip, the streams and the decode fixtures with its own integer networks and rANS decoder. Byte-identical on Linux x86_64 and Linux arm64. Co-Authored-By: Claude Opus 5.5 <[email protected]> |
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| .. | ||
| generate | ||
| int_audio | ||
| int_cond | ||
| int_hyper | ||
| int_mlicpp | ||
| int_splat | ||
| int_video | ||
| int_world | ||
| int_world2 | ||
| jpegai | ||
| neural_audio | ||
| staged_bounds | ||
| README.md | ||
Committed vectors
The vectors the reference implementation's tests decode, and the conformance corpora
under wai/*-conformance/ and the cross-architecture goldens are built on. A vector
changes only through its generator (CONTRIBUTING, Vectors).
Provenance. Each directory's row names the generator that writes it and the
generator's input. tests/corpus_provenance.rs requires a row for every directory.
| directory | provenance |
|---|---|
generate/ |
Generated: tools/wai_generate_model.py writes the spectral model from an integer sine table and a word list. |
int_audio/ |
Generated: tools/wai_int_audio_export.py trains the codec on a signal it generates from seed 1 and codes another signal from the same seed; it reads no audio file (int_audio/README.md). |
int_cond/ |
Generated: tools/wai_int_cond_export.py (seed 20261109) trains the conditional video codec on seeded procedural clips it draws itself (panning gratings and moving shapes), quantises it after training, and codes a held-out procedural clip from seed 20261110 with the integer networks; it reads no image or video file. |
int_hyper/ |
Generated: tools/wai_int_hyper_tiny_vector.py draws the tiny conditional codec's integer weights from a seeded generator. No image. |
int_mlicpp/ |
Generated: tools/wai_int_mlicpp_export.py (seed 20260929) codes an integer pattern of ramps, an xor texture and a disc with seeded weights; tools/wai_int_mlicpp_set_form.py writes its set-form twin. |
int_splat/ |
Generated: tools/wai_int_splat_export.py trains on a seeded procedural cloud. |
int_video/ |
int_video.* is generated by tools/wai_int_video_encode.py (a disc over a gradient), and video_nk.* by tools/wai_int_video_keyframe_encode.py (the int_hyper tiny keyframe, panned). video_real.* is not generated: tools/wai_int_video_real_encode.py pans over a third-party picture that was not made for this repository and has no recorded licence for redistribution. It is to be replaced by generated content. |
int_world/ |
Generated: tools/wai_int_world_export.py trains on a seeded procedural world. |
int_world2/ |
Generated: tools/wai_int_world2_export.py trains on seeded procedural backgrounds. |
jpegai/ |
test256.bin is the output of the ISO/IEC 6048-1 reference encoder (BSD-3) for a 256×256 generated test image of gradients and blocks (jpegai/README.md). |
neural_audio/ |
Generated: tools/wai_neural_audio_vectors.py writes, from fixed dyadic parameters and SplitMix64 codes (seeds 1 to 4), a small decoder with each model's geometry, an envelope of seeded codes and the decode it computes itself (neural_audio/README.md). No audio, no model weights. |
staged_bounds/ |
Constructed here for the bound tests: grey frames from a residual stream of zeros, and envelopes whose capability is refinement-only or companion-only (staged_bounds/README.md). No image. |