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jgrusewski 2df1ea92e1 feat(ml): WAVE 29 DQN Codebase Cleanup & Refactoring Campaign

BREAKING CHANGES:
- Removed orphaned dqn.rs monolithic trainer (4,975 lines)
- Removed orphaned dqn_ensemble.rs module (816 lines)
- Removed orphaned tft.rs and tft_complete_int8_integration_test.rs
- TFT trainer split into modular directory structure

DQN Module Refactoring:
- Split trainers/dqn.rs into modular structure (config.rs, statistics.rs, trainer.rs)
- Fixed hyperopt 39D search space (continuous params only)
- Boolean flags (use_dueling, use_double_dqn, use_per, use_noisy_nets) are now FIXED architectural decisions
- use_distributional defaults to false (Candle BUG #36 - scatter_add gradient issues)

Clean Module Structure:
- ml/src/trainers/dqn/ directory with proper mod.rs exports
- ml/src/trainers/tft/ directory with config.rs, types.rs, model.rs, trainer.rs, tests.rs
- All P0 features validated: TD-error clamping, batch diversity, LR scheduler, priority staleness

Documentation:
- Added comprehensive docs in docs/codebase-cleanup/
- ADR-001 for DQN refactoring decisions
- Rainbow DQN component matrix and quick reference guides

Build Status: Compiles with zero errors

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

2025-11-27 23:46:13 +01:00

2.3 KiB

Raw Blame History

DQN Trainer Refactoring Plan

Current State

File: ml/src/trainers/dqn.rs
Lines: 4,975
Target: <1,000 lines per module

Module Extraction Strategy

Module 1: `dqn/config.rs` (~800 lines)

Lines 48-747

Constants: EPISODE_LENGTH, type aliases (FeatureVector, FeatureVector51)
FeatureStatistics struct + impl (lines 78-157)
DQNHyperparameters struct (lines 425-610)
DQNHyperparameters impl methods (lines 615-747)

Module 2: `dqn/agent_wrapper.rs` (~260 lines)

Lines 164-424

DQNAgentType enum (wrapper for Standard/RegimeConditional)
QValueStats struct
All DQNAgentType impl methods (unified API)

Module 3: `dqn/training_monitor.rs` (~270 lines)

Lines 748-1012

TrainingMonitor struct
All validation methods (rewards, actions, Q-values)
Episode tracking

Module 4: `dqn/trainer.rs` (~3900 lines -> split further)

Lines 1013-4975 This needs further breakdown:

4a. trainer_core.rs: Struct definition, constructors, epoch metrics
4b. training_loop.rs: Main train() and train_from_parquet() methods
4c. data_loading.rs: OHLCV extraction, feature creation
4d. checkpointing.rs: Checkpoint save/load logic

Module 5: `dqn/mod.rs` (~50 lines)

Public re-exports maintaining current API
Module declarations

Public API Preservation

Current public exports from trainers/dqn:

pub use dqn::{DQNHyperparameters, DQNTrainer};

New structure ensures:

// dqn/mod.rs re-exports everything
pub use config::{DQNHyperparameters, FeatureStatistics, EPISODE_LENGTH};
pub use agent_wrapper::{DQNAgentType, QValueStats};
pub use training_monitor::TrainingMonitor;
pub use trainer::DQNTrainer;

Dependencies to Update

Tests: 19 DQN test files reference trainers::dqn::
Hyperopt adapter: hyperopt/adapters/dqn.rs (3,162 lines)
Trainers mod: trainers/mod.rs re-export

Verification Steps

Extract modules incrementally
cargo check --package ml after each extraction
Update imports in dependent files
Run test suite: cargo test --package ml --lib
Verify no breaking changes to public API

Risk Mitigation

Keep original dqn.rs as dqn.rs.backup until verification complete
Incremental extraction with build checks
Test after each module extraction

2.3 KiB Raw Blame History