devin-lai's picture
Release v0.4.0: selective MLX model downloads
3da88e3 verified
Raw History Blame Contribute Delete
5.37 kB
{
"schema_version": 1,
"id": "r3-deployment-control",
"campaign_id": "h3-m5pro-round-03",
"contract_sha256": "cbd4ce596524b59629216716299ee8677b10f49140de962384153aaaa2e55dec",
"complete": true,
"change_class": "control",
"hypothesis": "Native reduction matching QK/RoPE fusion and shape-qualified Metal 4 FC2 tiling reduce full generation latency without changing a denoising tensor or pixel.",
"context": {
"hardware": "Apple M5 Pro, 16 GPU cores, 64 GiB unified memory",
"os": "macOS 27.0.1 arm64",
"software": "MLX/MLX Metal 0.32.4; Python 3.12.14; strict precision environment",
"environment": "AC Automatic power; MLX_ENABLE_TF32=0, MLX_CONV_WINOGRAD=0; user background apps unchanged; no thermal warning recorded",
"timing_boundary": "Pipeline.generate total_s: warm text cache, original CPU RNG, six heads, decode, trace and PNG save. Excludes interpreter startup and external quality scoring.",
"memory_metric": "Parent macOS physical footprint sampled at 100ms, current-interval maximum; includes Metal, excludes compiler XPC. MLX allocator separately; do not sum. Both compiled variants may be resident.",
"cache_state": "Resident shared native weights and VAE; shape warmup for each variant. Exact conditioning caches warmed outside timed population.",
"execution_policy": "Single GPU benchmark process; per-case repeats alternate control/candidate then candidate/control then control/candidate. Warmup and first-load excluded from timed population."
},
"variant": {
"id": "control",
"code_sha256": "5625a5a38d92a68faf5d27aa72cd66cd0bc50d1794f143075f25db4351df56f9",
"model_sha256": "3274a3e5fe0d2ea0d63f66b020beb193276a0a9d8de7ea466b312fbae9a2746f",
"config_sha256": "8354e62638cc6104a5d188c26cb42ebc3f9048f222a15254fe9033dc384b902a",
"command": [
".venv/bin/python",
"-m",
"experiments.r3.images",
"--deployment",
"--variants",
"qk-fc2",
"--model",
"/Users/devin/Desktop/minimax-h3-image-opt/models/MiniMax-H3-Image",
"--text-encoder",
"/Users/devin/Desktop/minimax-h3-image-opt/models/MiniMax-H3/text_encoder",
"--output",
"outputs/optimization-r3-deployment"
]
},
"quality": {
"variant_sha256": "91fbe66f6a9108076fe18e6b1f476a1d6e042834b86218da5b1810e4a26f4284",
"reference_sha256": "201be3382041aec890cbd766c2f88a43799f7e2d33807e9a1504f7e29e422065",
"evaluator_sha256": "4db0c5e8606ffc011bf85dbadabc482468a2e49cd5a1757a774620d493eba7ee",
"outputs": {
"product": "eaed6c290ea3f7843ed4a789614cf3ad384d5acf3d0e0cc40a569fdcb850390f",
"portrait": "4226310bd1d79a0d0d4c0b572e2e7729541f5f171260cfeefd5e73b0a4196a47",
"edit": "b4b5875fea6451b9c7c24efc7903945a454ae7885ed3016bfc361b4799b2508e",
"holdout-detail": "561b18aa708d61a5accbfd12f2280e8f7e303505324c43471ba06d60fe0351d5"
},
"metrics": {
"max_abs_error": 0,
"nonfinite_values": 0
}
},
"runs": [
{
"case": "product",
"repeat": 0,
"seconds": 68.77809108304791,
"peak_memory_bytes": 42843920992,
"output_sha256": "eaed6c290ea3f7843ed4a789614cf3ad384d5acf3d0e0cc40a569fdcb850390f"
},
{
"case": "product",
"repeat": 1,
"seconds": 65.85317666619085,
"peak_memory_bytes": 42928544448,
"output_sha256": "eaed6c290ea3f7843ed4a789614cf3ad384d5acf3d0e0cc40a569fdcb850390f"
},
{
"case": "product",
"repeat": 2,
"seconds": 64.79533495893702,
"peak_memory_bytes": 42819443440,
"output_sha256": "eaed6c290ea3f7843ed4a789614cf3ad384d5acf3d0e0cc40a569fdcb850390f"
},
{
"case": "portrait",
"repeat": 0,
"seconds": 64.64417616720311,
"peak_memory_bytes": 43071298312,
"output_sha256": "4226310bd1d79a0d0d4c0b572e2e7729541f5f171260cfeefd5e73b0a4196a47"
},
{
"case": "portrait",
"repeat": 1,
"seconds": 64.91441170801409,
"peak_memory_bytes": 42932624232,
"output_sha256": "4226310bd1d79a0d0d4c0b572e2e7729541f5f171260cfeefd5e73b0a4196a47"
},
{
"case": "portrait",
"repeat": 2,
"seconds": 64.66372808301821,
"peak_memory_bytes": 43044674408,
"output_sha256": "4226310bd1d79a0d0d4c0b572e2e7729541f5f171260cfeefd5e73b0a4196a47"
}
],
"evidence": [
{
"path": "outputs/optimization-r3-deployment/runs.jsonl",
"sha256": "2e292337bf063e1a3401e06ed913059c00ab55e725370d0cebace78616ec93c7"
},
{
"path": "outputs/optimization-r3-deployment/source-manifest.json",
"sha256": "5625a5a38d92a68faf5d27aa72cd66cd0bc50d1794f143075f25db4351df56f9"
},
{
"path": "reports/optimization-r3/deployment/quality-audit.json",
"sha256": "9ca5a230623a6e864905c3eb4415744e5ba316581124124491d1b402de6b2fc7"
},
{
"path": "reports/optimization-r3/deployment/summary.json",
"sha256": "b5bb2dbed4be970e4dfd1e5100e83bdfc65a817ca91994448da8aa2ef3cefd82"
}
],
"extensions": {
"canonical_output": "SHA256 decoded RGB uint8 bytes in row-major order",
"model_identity": "model_sha256 is the pinned model/source provenance manifest hash; no new full checkpoint rehash",
"reference_scope": "Incremental identity to MLX BF16 recipe, not CUDA or unpublished FP32 training weights",
"trace_identical": true
}
}