Commit Graph

7 Commits

Author SHA1 Message Date
jgrusewski
aa19b42255 refactor(ml): move UnifiedTrainable to ml-core + delete 6K dead deployment code
- Move UnifiedTrainable trait, TrainingMetrics, CheckpointMetadata, and
  checkpoint helpers from ml to ml-core (zero new dependencies — ml-core
  already had candle-core + serde_json)
- Wrap Mamba2SSM in Mamba2TrainableAdapter to satisfy orphan rule (trait
  in ml-core, type in ml-supervised — all other 9 models already used
  wrapper pattern)
- Make Mamba2SSM::validate() pub for cross-crate adapter access
- Delete 5 permanently disabled deployment modules (cfg(any()) — never
  compiled): registry, hot_swap, validation, monitoring, endpoints
  (-5,842 lines)
- Delete 2 undeclared dead files in training/: dqn_trainer.rs,
  transformer_trainer.rs (-138 lines)
- Fix pre-existing compute_loss test shape mismatch in mamba adapter

UnifiedTrainable in ml-core unblocks future trainers/ extraction (17.8K
lines) since model-specific trainers can now depend on ml-core for the
trait without pulling in the full ml monolith.

14 files changed, +128 -6,497 (net -6,369 lines)
Tests: 274 ml-core + 948 ml = 1,222 passed, 0 failed

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-08 15:17:22 +01:00
jgrusewski
7d1b0f232f refactor(ml): move core types to ml-core + dedup MLError (5a)
Move all inline type definitions from ml/src/lib.rs to ml-core:
MLError, MLResult, Trade, MarketRegime, HealthStatus, Features,
MLModel trait, ModelRegistry, ParallelExecutor, LatencyOptimizer,
TrainingMetrics, ValidationMetrics, InferenceResult, ModelMetadata.

Dedup: consolidate ConfigError{reason}/ConfigurationError(msg) into
single ConfigError(String) tuple variant (was 2 variants, 174 refs).

Cleanup: convert create_hft_* free functions to associated methods
(HFTPerformanceProfile::ultra_low_latency(), ParallelExecutor::hft()).

ml facade re-exports via `pub use ml_core::*`.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-08 15:13:41 +01:00
jgrusewski
2aedc2ae1a feat(ml): comprehensive GPU saturation audit — 58 fixes across all 10 models
Phase 1 — Fix broken models (P0):
- Diffusion: wire optimizer_step to actually apply gradients (was no-op)
- TLOB: connect forward pass to projection layers (was Tensor::zeros)
- Mamba2: F64→F32 migration across 5 files (~30x faster on L40S tensor cores)

Phase 2 — Eliminate hot-path GPU sync stalls:
- Mamba2: keep dt on GPU in discretize_ssm (4 functions, no CPU round-trip)
- TFT: gate attention weight logging to eval only (8 syncs/forward eliminated)
- Mamba2: defer loss scalar after backward (pipeline stall removed)
- Mamba2: delete dead gradient clipping (4N wasted GPU syncs removed)

Phase 3 — Enable BF16 for supervised models:
- Flip mixed_precision defaults to true in 4 config locations
- Fix cuda_layer_norm to support BF16/F16 via F32 intermediate

Phase 4 — Raise hyperopt bounds for datacenter GPUs:
- 7 adapters with VRAM-aware tiers (TFT, Liquid, TGGN, KAN, xLSTM,
  Diffusion, TLOB) — L40S gets full hidden_dim range
- Fix L40S tier boundary (was excluded at <48000, now >=40000)

Phase 5 — Update memory estimates:
- 10 param_count estimates updated (DQN 200K→12M, TFT 2M→50M, etc.)
- Fix power-of-two rounding (was wasting up to 49% of budget)
- Correct MODEL_OVERHEAD_MB in DQN/PPO/TFT adapters

Phase 6 — Fix per-epoch CPU bottlenecks:
- PPO: deduplicate double advantage normalization (correctness fix)
- PPO: GPU tensor reward normalization + explained variance
- Fuse per-parameter grad norm to single GPU sync (xLSTM, KAN, TGGN)

Phase 7 — Data pipeline:
- GpuBufferPool: use from_slice (eliminate staging buffer copy)

Phase 8 — Correctness:
- TFT: remove broken .detach() in forward_checkpointed (restore gradients)
- Update stale RTX 3050 Ti doc references

33 files changed, 2451 tests pass, 0 clippy warnings.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-02 15:41:23 +01:00
jgrusewski
680c12d2c0 refactor: delete 4,800 lines of dead ML code and remove MLFeatureExtractor dependency
- Delete push_metrics.rs (Pushgateway client, zero consumers)
- Delete 5 legacy test/bench files for MLFeatureExtractor + SimpleDQNAdapter
- Remove MLFeatureExtractor from trading_agent_service, use direct bar scoring
- Remove with_feature_extractor() method and Arc<MLFeatureExtractor> parameter
- Remove bench target from common/Cargo.toml

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-01 18:29:43 +01:00
jgrusewski
7744becdd5 feat(training): move metrics to common::metrics, fix all clippy errors
Move Prometheus training metrics from example-local baseline_common/
to common::metrics::{server,training_metrics} following the existing
grpc_metrics.rs pattern. Fix 29 let_underscore_must_use clippy errors
in push_metrics.rs, 3 shadow lint errors in training binaries, and
demote gradient clipping log from warn to debug.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-01 15:56:43 +01:00
jgrusewski
9b85b9efd5 feat(ml): add Pushgateway metrics client for training jobs
Training jobs are short-lived K8s Jobs that can't be reliably scraped
by Prometheus. This adds a TrainingMetricsPusher that pushes epoch-level
metrics (loss, accuracy, throughput, gradient health, checkpoints) to
the Pushgateway so they persist for Prometheus to scrape.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-01 02:36:05 +01:00
jgrusewski
9c3d741a08 refactor: restructure repo — crates/, bin/, testing/ layout
Move 17 library crates into crates/, CLI binary into bin/fxt,
consolidate 10 test crates into testing/, split config crate
from deployment config files.

Root directory reduced from 38+ to ~17 directories.
All Cargo.toml paths and build.rs proto refs updated.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-25 11:56:00 +01:00