4 Commits

Include renames

Author	SHA1	Message	Date
osobhandClaude Fable 5	1e3c604896	feat(meta,jepa): expose GPU features through meta-crates; wire JEPA cluster plan and real shard loading ... Meta-crates (Phase 2): - rtx-core / rtx-training / rtx-inference-stack gain cuda and metal features threading into their sub-crates; GPU was previously unreachable through the user-facing bundles. - rtx-training restores rtx-distributed (the hpc-channels blocker is gone) so the advertised DistributedTransformerTrainer resolves; drops the unused rtx-runtime dep. - rtx-transformers drops unused rtx-backend/rtx-backend-cpu deps (stale comment referenced a teacher that never used them). Never-compiled CUDA paths fixed (surfaced by the new feature wiring, verified on RTX 5060 Ti / CUDA 13.1): - rtx-compress build.rs: missing Path/Command/fs imports. - rtx-flash-attention flash_decode_forward: reborrow &mut kernel args. - rtx-transformers: rope kernel include path, cudarc 0.18 Arc<CudaModule>, PushKernelArg imports in jepa_gpu, edition-2024 ref patterns. - rtx-memory: full cudarc 0.18 port (CudaContext, stream-based alloc, DevicePtr accessors, error enum formatting) across gpu_pinning, gpu_transfer, gpu_real, gpu_allocator/arena, gpu_tests. JEPA (Phase 3): - JepaRunConfig::apply_cluster_plan consumes ClusterTrainingPlan (batch size, TP/DP, world size, total steps) so jepa_cluster is no longer standalone dead config; ViTSizeStr::approx_params_m feeds JepaParallelConfig::for_model_and_cluster. - WebDatasetShard::load reads real .tar shards from disk via the existing parser (gzip rejected explicitly); to_in_memory documented as synthetic/test-only. - New image-decode feature actually defines the dep for the previously unreachable cfg(feature = "image-decode") JPEG/PNG decode path. Co-Authored-By: Claude Fable 5 <[email protected]>	2026-07-09 19:25:51 -07:00
Omar SobhandClaude Sonnet 4.6	f487196367	feat(batch27): JEPA ViT bridge, WebDataset shard reading, training loop ... Gap 2 — rtx-vision ViT bridge (jepa_vision_bridge.rs, 8 tests): - ViT::forward_features(): patch reps without classification head - ViT::encode_patch_indices(): shape-correct placeholder for GPU dispatch - RtxVisionJepaEncoder implementing JepaEncoder (vision-bridge feature) - From<&ViTConfig> for JepaViTConfig config conversion - rtx-vision added as optional dep; vision-bridge feature gate Gap 3 — WebDataset tar-shard reading (jepa_data.rs, +12 tests, 47 total): - parse_tar_bytes(): pure stdlib tar parser (512-byte block format) - read_webdataset_shard(): file reader with ShardLoadStats timing - WebDatasetRecord: key, image_bytes, label, extension - ShuffleBuffer: fixed-capacity reservoir sampling via LCG PRNG - JepaDataPipeline::from_filesystem(): validates paths, loads shards, builds pipeline Gap 5 — Training loop runner (jepa_runner.rs + examples/jepa_train.rs, 15 tests): - JepaRunConfig with TOML-style key=value parser - run_jepa_training(): full training loop (JepaTrainerV2, cosine LR, checkpointing) - JepaCheckpoint::save() writes JSON summary; load() stub - examples/jepa_train.rs: --config/--size/--steps/--dry-run CLI flags Co-Authored-By: Claude Sonnet 4.6 <[email protected]>	2026-06-27 15:23:55 +00:00
osobhandClaude Opus 4.8	1b1ce0604a	SMT E1: SetEncoderTeacher — the predictive-state oracle (time-parallel, tape-trained) ... Promotes the proven attention set-encoder smoke test (PR #4, tape_train_smoke.rs) into a reusable rtx-transformers layer for Supervised Memory Training. The teacher maps a window of past tokens to a fixed-size memory M via embed → self-attention → residual → mean-pool → memory projection, with a decoder head supervised by predict-the-future MSE so that M becomes a sufficient statistic of the past. - Trains end-to-end on Autodiff<CpuBackend> (the gradient-correct real backend from PR #3), with a self-contained deterministic host-side Adam. - Time-parallel by construction (one window → one memory, no recurrence to unroll) — this is the oracle whose trajectory the recurrent Mamba updater is later behaviorally cloned against, so the recurrent net never needs BPTT. - Exposes named_params/set_named_params so the caller (omni-think's PredictiveStateTeacher facade) owns safetensors persistence + BLAKE3 sealing. - Adds rtx-backend + rtx-backend-cpu deps (the tape needs a concrete backend). Tests: teacher trains (loss >5x drop), encode is deterministic + fixed-size, params round-trip. fmt + clippy(-D warnings) clean on the new module. Co-Authored-By: Claude Opus 4.8 (1M context) <[email protected]>	2026-06-16 09:37:55 -07:00
redclawsystems	4d88dc0584	Initial commit	2026-03-04 00:08:42 +00:00