corridorkey-mrp-mlx/docs/plans
cmoyates b3b7df271d
feat: MLX memory optimizations — bf16, fused decode, deterministic GC
Phase 1: selective bf16 mixed precision (backbone fp32, decoders bf16,
sigmoid always fp32). dtype param on GreenFormer, all outputs guaranteed
fp32.

Phase 2: FusedDecoderPair batches 3 upsample ops by concatenating
alpha+fg projections along channel axis. Bit-exact parity with unfused
path.

Phase 3: deterministic GC pipeline in tile loop (del + gc.collect +
mx.clear_cache) and engine.py intermediate tensor cleanup.

7 new tests: bf16 dtype/range/nan, fused-vs-unfused parity, fp32
default unchanged. 80 passed, 0 failures.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-08 21:21:01 -02:30
..
2026-03-01-feat-2048-smoke-test-plan.md feat: add 2048 smoke test for native-resolution validation 2026-03-01 07:04:28 -03:30
2026-03-01-feat-corridorkey-mlx-inference-port-plan.md feat(phase6): optimization, benchmarking, and tiled inference 2026-03-01 06:24:10 -03:30
2026-03-01-feat-engine-integration-surface-plan.md feat: add CorridorKeyMLXEngine integration surface 2026-03-01 06:43:07 -03:30
2026-03-01-fix-converter-review-feedback-plan.md feat(phase3): PyTorch→MLX weight converter (#1) 2026-03-01 05:16:56 -03:30
2026-03-01-phase4-hiera-backbone-plan.md feat(phase4): MLX Hiera backbone port (#2) 2026-03-01 05:55:24 -03:30
2026-03-03-refactor-deep-modules-plan.md docs: add deep modules refactor plan 2026-03-03 09:45:43 -03:30
2026-03-08-feat-mlx-memory-optimizations-plan.md feat: MLX memory optimizations — bf16, fused decode, deterministic GC 2026-03-08 21:21:01 -02:30