e4c7287acb
D2c M4, gate 7 (delete). - int_hyper_synth::decode_conditional, the unchecked conditional decode, is deleted; its callers decode through decode_conditional_checked (the lowering, with its check ranges): the int_hyper_decode_frame example (step 3 of tools/wai_sota_vectors.sh), wai_decode_bench's tiny-vector case, int_payload's JSON-equivalence unit tests, tests/int_hyper_synth.rs, int_kernels_vectors.rs, int_video_keyframe.rs, int_video_sota_keyframe.rs, and byte-exact's neural_keyframe_golden (the trap: it gains the check ranges, outputs equal; gate 2's duplicate test through ops::decode goes). - The pretrained synthesis-only and hyper-decoder-only goldens (tests/int_hyper_synth.rs) are also held through the lowering. - The conditional codec's direct guard (legacy's run_checked) is test-only since gate 6. run_net_checked, check_layer and igdn_check stay: their one production caller left is int_mlicpp (M5); run_net and decode stay for the world renderer (M6), and int_hyper_synth's kernel_equivalence with them, since their conv dispatch is still run_net's. Docs say so. - Doc references (int_video, int_video_golden, two tools) and CHANGELOG. Co-Authored-By: Claude Opus 5.5 <[email protected]>
68 lines
3.2 KiB
Rust
68 lines
3.2 KiB
Rust
//! `wai.video.int_hyper` on the full pretrained model — a real 256×256 clip whose
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//! I-frame is the byte-exact `int_hyper` decode of the pretrained mbt2018_mean
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//! (exported to integers), panned into P-frames by integer motion compensation.
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//! Reads the int_hyper vector + the panned-clip bitstream from `WAI_SOTA_INT_DIR`
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//! (default `/tmp/sota_int`), regenerated by `tools/wai_sota_vectors.sh` (the
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//! model is too large to commit). CI (`wai-sota-vectors.yml`) regenerates them and
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//! runs this with `WAI_REQUIRE_SOTA_VECTORS=1`, so an absent vector fails there;
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//! locally it skips loudly. A `WAI_SOTA_INT_DIR` naming a directory that does not
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//! exist, or one missing a file this test reads, fails either way. The committed
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//! 16×16 `int_video_keyframe` test is the never-skip companion.
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#![cfg(all(feature = "neural_int", feature = "video_int"))]
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#[path = "support/require_vectors.rs"]
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mod require_vectors;
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use require_vectors::{env_dir, load_all};
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use wai::int_hyper_synth::{decode_conditional_checked, CondBitstream, CondEntropy, IntModel};
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use wai::int_video::{decode_pframes, fnv1a};
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fn hex16(s: &str) -> [u8; 8] {
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let mut o = [0u8; 8];
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for (i, b) in o.iter_mut().enumerate() {
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*b = u8::from_str_radix(&s[i * 2..i * 2 + 2], 16).unwrap();
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}
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o
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}
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#[test]
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fn sota_int_hyper_keyframe_clip_decodes_byte_for_byte() {
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const TEST: &str = "int_video_sota_keyframe::sota_int_hyper_keyframe_clip_decodes_byte_for_byte";
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const PRODUCE: &str = "tools/wai_sota_vectors.sh <dir> (then WAI_SOTA_INT_DIR=<dir>, default /tmp/sota_int)";
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let d = env_dir(TEST, "WAI_SOTA_INT_DIR", "/tmp/sota_int", PRODUCE);
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let Some([g, hh, e, b, vb, conf]) = load_all(
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TEST,
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&d,
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[
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"int_synth_sota_model.json", "int_hs_model.json", "cond_entropy.json",
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"cond_bitstream.json", "video_sota_bitstream.json", "video_sota.json",
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],
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PRODUCE,
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) else {
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return;
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};
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// frame 0: the int_hyper learned I-frame (byte-exact 256×256 photo).
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let g_s = IntModel::from_json(&g);
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let h_s = IntModel::from_json(&hh);
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let ent = CondEntropy::from_value(&e);
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let bs = CondBitstream::from_value(&b);
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let (frame0, h, w) = decode_conditional_checked(&g_s, &h_s, &ent, &bs.stream()).expect("int_hyper I-frame");
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// frames 1..N: integer motion-compensated P-frames panning the keyframe.
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let clip = decode_pframes(&frame0, h, w, &vb).expect("p-frames");
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let want = conf["frame_hashes"].as_array().unwrap();
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assert_eq!(clip.frames.len(), want.len());
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assert_eq!(format!("{:016x}", fnv1a(&frame0)), want[0].as_str().unwrap(), "I-frame = int_hyper decode");
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let mut all = Vec::new();
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for (i, frame) in clip.frames.iter().enumerate() {
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let got = format!("{:016x}", fnv1a(frame));
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assert_eq!(got, want[i].as_str().unwrap(), "frame {i} byte-for-byte");
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all.extend_from_slice(&hex16(&got));
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}
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assert_eq!(format!("{:016x}", fnv1a(&all)), conf["clip_hash"].as_str().unwrap(), "clip hash");
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println!("int_hyper-keyframe video (pretrained model): {} frames {h}x{w}, I-frame={} (learned), clip {}",
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clip.frames.len(), &want[0].as_str().unwrap()[..8], conf["clip_hash"].as_str().unwrap());
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}
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