2 Commits

Include renames

Author	SHA1	Message	Date
Omar SobhandClaude Fable 5	366a46b471	rtx-interpret: seeded SAE init + coupled per-unit optimizer reset ... SparseAutoencoder::new_seeded draws encoder/decoder weights via randn_seeded with per-tensor SplitMix64-derived seeds (same derivation as MambaBlock::new_seeded), so identical (config, seed) gives bit-exact SAEs — without it, cross-instance loss comparisons are noise (measured downstream: 0.09 vs 0.65 starts on identical data). SAETrainer::reinitialize_neuron couples the encoder-unit weight reinit with zeroing that unit's optimizer moment rows (encoder row, bias slot, decoder column), so external generate-and-test callers can't reset weights while leaving optimizer state stale — previously only the trainer's internal dead-neuron resampling did both. Note train_step's update rule is plain SGD today, so the moment reset is inert until the Adam path is switched on; the coupling is the contract either way, and a doctored-checkpoint test pins the row/column semantics. Also drops a vacuous assert!(true) smoke test that failed clippy's assertions_on_constants. Co-Authored-By: Claude Fable 5 <[email protected]> Claude-Session: https://claude.ai/code/session_01B1feFAQxjbCRHePUdxuNra	2026-08-28 20:49:11 -05:00
redclawsystems	4d88dc0584	Initial commit	2026-03-04 00:08:42 +00:00