[evidence]: VSA+DMD2 parity — sparse student/dense scorers, measured band

2026-07-23 05:55:46 -07:00
parent 420ed38418
commit d3ee4fb372
10 changed files with 135 additions and 0 deletions
@@ -0,0 +1,57 @@
+{
+  "fastvideo_commit": "c459a1897899ffcec3be7765534d81000b9bb9c1",
+  "mode": "vsa_dmd2",
+  "seed": 42,
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+  "torch": "2.12.0+cu130",
+  "gpu": "NVIDIA GB200",
+  "config": "dmd2 legacy: interval2 gw3.5 lr2e-6 shift8 steps[1000,757,522] simulate nlt4 1gpu",
+  "self_noise_runs": {
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+  "self_noise_max": 0.04847508668899536
+}
@@ -0,0 +1,59 @@
+[
+ {
+  "targets": [
+   2
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+  "vsa_sparsity": 0.8,
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+  "x0_student_hash": "afb6654472fdc388"
+ },
+ {
+  "targets": [
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+  "vsa_sparsity": 0.8,
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+  "x0_student_hash": "3e19f627f7a67079"
+ },
+ {
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+   1
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+  "vsa_sparsity": 0.8,
+  "critic_t": 980.0,
+  "gen_loss": 0.19375097751617432,
+  "fake_loss": 0.9273568987846375,
+  "x0_student_hash": "a5e00f1532646e2a"
+ },
+ {
+  "targets": [
+   2
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+  "dmd_t": null,
+  "vsa_sparsity": 0.8,
+  "critic_t": 456.45648193359375,
+  "gen_loss": 0.0,
+  "fake_loss": 0.1123386099934578,
+  "x0_student_hash": "9dc08f8928d30b94"
+ }
+]
@@ -160,3 +160,4 @@
 {"ts": "2026-07-23T11:47:02Z", "gate": "anchor.train-finetune-main", "status": "pass", "model_id": "wan2.1-t2v-1.3b", "card_digest": "7171d8729ae72ae4", "metrics": {"noisy.step0": 0.0, "pred.step0": 0.0, "loss.step0": 0.0, "gnorm.step0": 7.675588130950928e-05, "loss.step1": 5.221366882324219e-05, "gnorm.step1": 0.05505657196044922, "loss.step2": 0.0007446706295013428, "gnorm.step2": 0.006015121936798096, "loss.step3": 0.0025970935821533203, "gnorm.step3": 0.032111406326293945, "loss.step4": 0.0013115331530570984, "gnorm.step4": 0.0047234296798706055, "params.w0": 0.0, "params.w5": 0.00029868653199637143}, "tolerances": {"step0": 0.0, "later": "main self-noise band (see manifest)"}, "env": {"python": "3.12.13", "machine": "aarch64", "commit": "e14afd7", "torch": "2.12.0+cu130", "cuda": "13.0", "gpu": "NVIDIA GB200", "diffusers": "0.39.0", "transformers": "5.13.0", "attention": {"policy": "AUTO", "available": ["FLASH_ATTN", "SDPA"]}}, "detail": "goldens c459a1897"}
 {"ts": "2026-07-23T11:58:27Z", "gate": "anchor.train-vsa-main", "status": "pass", "model_id": "fastwan-t2v-1.3b", "card_digest": "0bd5c7771e10ce44", "metrics": {"noisy.step0": 0.0, "pred.step0": 0.0, "loss.step0": 0.0, "gnorm.step0": 7.104873657226562e-05, "loss.step1": 0.00040608644485473633, "gnorm.step1": 0.014156341552734375, "loss.step2": 5.901604890823364e-05, "gnorm.step2": 0.18469977378845215, "loss.step3": 0.08010447025299072, "gnorm.step3": 0.9372882843017578, "loss.step4": 0.005944937467575073, "gnorm.step4": 0.15396595001220703, "params.w0": 0.0, "params.w5": 0.0010486775342362664}, "tolerances": {"step0": 0.0, "later": "main self-noise band (see manifest)"}, "env": {"python": "3.12.13", "machine": "aarch64", "commit": "c73ccc7", "torch": "2.12.0+cu130", "cuda": "13.0", "gpu": "NVIDIA GB200", "diffusers": "0.39.0", "transformers": "5.13.0", "attention": {"policy": "AUTO", "available": ["FLASH_ATTN", "SDPA"]}}, "detail": "goldens c459a1897"}
 {"ts": "2026-07-23T12:41:59Z", "gate": "anchor.train-dmd2-main", "status": "pass", "model_id": "wan2.1-t2v-1.3b", "card_digest": "7171d8729ae72ae4", "metrics": {"x0.step0": 0.0, "fake.step0": 8.051283657550812e-06, "x0.step1": 0.0, "gen.step1": 4.5299530029296875e-06, "fake.step1": 1.3254117220640182e-05, "x0.step2": 1.0, "fake.step2": 2.8714537620544434e-05, "x0.step3": 1.0, "gen.step3": 0.0007560849189758301, "fake.step3": 1.97533518075943e-05, "x0.step4": 1.0, "fake.step4": 2.2767577320337296e-05, "params.w5_student": 8.810074752674709e-05, "params.w5_critic": 4.3383224253287114e-06}, "tolerances": {"x0.step0": 0.0, "later": "band"}, "env": {"python": "3.12.13", "machine": "aarch64", "commit": "a95f36e", "torch": "2.12.0+cu130", "cuda": "13.0", "gpu": "NVIDIA GB200", "diffusers": "0.39.0", "transformers": "5.13.0", "attention": {"policy": "AUTO", "available": ["FLASH_ATTN", "SDPA"]}}, "detail": "goldens c459a1897"}
+{"ts": "2026-07-23T12:54:46Z", "gate": "anchor.train-vsa_dmd2-main", "status": "pass", "model_id": "fastwan-t2v-1.3b", "card_digest": "0bd5c7771e10ce44", "metrics": {"x0.step0": 0.0, "fake.step0": 0.0003465712070465088, "x0.step1": 0.0, "gen.step1": 6.683170795440674e-06, "fake.step1": 0.00270843505859375, "x0.step2": 1.0, "fake.step2": 0.010587543249130249, "x0.step3": 1.0, "gen.step3": 0.011355012655258179, "fake.step3": 0.02186185121536255, "x0.step4": 1.0, "fake.step4": 0.003451891243457794, "params.w5_student": 6.644270548064443e-05, "params.w5_critic": 0.00018422111178113666}, "tolerances": {"x0.step0": 0.0, "later": "band"}, "env": {"python": "3.12.13", "machine": "aarch64", "commit": "420ed38", "torch": "2.12.0+cu130", "cuda": "13.0", "gpu": "NVIDIA GB200", "diffusers": "0.39.0", "transformers": "5.13.0", "attention": {"policy": "AUTO", "available": ["FLASH_ATTN", "SDPA"]}}, "detail": "goldens c459a1897"}
@@ -82,3 +82,21 @@ loop's `dmd_inference_table` — training reuses inference definitions).
 Capture pins uncond embeds by encoding the canonical Wan negative prompt
 through main's own text stack (the recipe normally gets them via the
 validation path).
+
+## VSA+DMD2 sparse distillation — added 2026-07-23
+
+Gate `anchor.train-vsa_dmd2-main`: PASS. The FastWan recipe composition:
+VSA-built student on FastWan weights (deterministic gate projections),
+DENSE-built scorers on the base checkpoint — discovered from main's own
+loader rejecting gate keys for scorer roles: teacher/critic score via plain
+flash, NOT sparsity-0 VSA (the train loop's "dense copy" metadata is ignored
+by the flash impl). Student rollout runs sparsity 0.8.
+
+x0 rollout bitwise through the first student update; all gen/fake losses
+within the measured band (main-vs-main drifts to 4.8e-2 at step3 under
+sparse-student updates — an order noisier than dense DMD2's 7.2e-4);
+param slices ~1e-4 (info).
+
+Deferred (documented): the shipped recipe random-initializes student gate
+projections from the BASE checkpoint — an init-RNG parity gate for later,
+same caveat as the VSA finetune gate.