# OptiRS NAS TODO (v0.1.0)

## Module Status: Production Ready

**Release Date**: 2025-12-30
**Tests**: 44 tests passing (1 ignored)
**Features**: Bayesian optimization, Evolutionary algorithms, RL-based NAS
**SciRS2 Compliance**: 100%

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## Completed: SciRS2 Integration

- [x] **Full SciRS2-Core Integration** - 100% complete
- [x] **Neural Architecture Search Foundation** - Built on scirs2_core::neural_architecture_search
- [x] **Search Space Management** - Using scirs2_core::neural_architecture_search::SearchSpace
- [x] **Quantum Optimization** - scirs2_core::quantum_optimization for advanced search strategies
- [x] **Parallel Processing** - scirs2_core::parallel::LoadBalancer for parallel search
- [x] **Array Operations** - All NAS operations use scirs2_core::ndarray
- [x] **Random Generation** - scirs2_core::random for all stochastic search operations

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## Completed: Core NAS Infrastructure

### Search Space Framework
- [x] SciRS2 Search Space via neural_architecture_search::SearchSpace
- [x] Layer type definitions and constraints
- [x] Connection pattern specifications
- [x] Hyperparameter range definitions
- [x] Resource constraint modeling
- [x] Search space validation

### Bayesian Optimization
- [x] Gaussian Process regression with various kernels
- [x] Hyperparameter optimization for GPs
- [x] Multi-fidelity Gaussian processes
- [x] Sparse GP approximations

### Acquisition Functions
- [x] Expected Improvement (EI)
- [x] Upper Confidence Bound (UCB)
- [x] Probability of Improvement (PI)
- [x] Knowledge Gradient
- [x] Batch acquisition for parallel evaluation

### Evolutionary Algorithms
- [x] Chromosome encoding for neural architectures
- [x] Crossover operators for architecture combination
- [x] Mutation operators for architecture variation
- [x] Selection strategies (tournament, roulette wheel)
- [x] Population diversity maintenance
- [x] Multi-objective genetic algorithms (NSGA-II/III)

### Reinforcement Learning NAS
- [x] LSTM controllers for sequential generation
- [x] Transformer controllers with attention
- [x] Graph neural network controllers
- [x] Curriculum learning for controller training
- [x] Experience replay for sample efficiency

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## Completed: Advanced Features

### Multi-Objective Optimization
- [x] NSGA-II/III implementation
- [x] Pareto dominance and ranking
- [x] Hypervolume indicator calculation
- [x] Diversity preservation mechanisms

### Hardware-Aware NAS
- [x] Latency prediction models
- [x] Memory usage estimation
- [x] Power consumption modeling
- [x] Device-specific optimization

### Evaluation Framework
- [x] Early stopping mechanisms
- [x] Progressive evaluation strategies
- [x] Proxy task evaluation
- [x] Performance prediction models
- [x] Distributed evaluation systems

### Search Optimization
- [x] Parallel evaluation of candidates
- [x] Asynchronous optimization
- [x] Warm-starting from previous searches
- [x] Architecture performance prediction

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## Future Work (v0.2.0+)

### Advanced Search Strategies
- [ ] Differentiable Architecture Search (DARTS)
- [ ] Progressive architecture pruning
- [ ] Memory-efficient DARTS
- [ ] Robust DARTS with regularization

### Specialized NAS Applications
- [ ] Computer vision architecture search
- [ ] NLP model architecture optimization
- [ ] Speech recognition NAS
- [ ] Time series forecasting NAS
- [ ] Multimodal architecture optimization

### Transfer Learning for NAS
- [ ] Architecture embedding and similarity
- [ ] Cross-domain transfer
- [ ] Few-shot architecture optimization
- [ ] Architecture knowledge graph

### AutoML Integration
- [ ] End-to-end automated data preprocessing
- [ ] Feature engineering automation
- [ ] Model selection and ensemble
- [ ] Pipeline optimization

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## Testing Status

### Coverage
- [x] Search algorithm correctness tests
- [x] Performance regression tests
- [x] Resource utilization tests
- [x] Reproducibility tests
- [x] Integration tests

### Test Count
```
44 tests passing
1 intentionally ignored (hardware-specific)
```

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## Performance Achievements

- Efficient search space exploration
- Multi-objective optimization working
- Hardware-aware architecture discovery
- Production-ready evaluation framework

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**Status**: ✅ Production Ready
**Version**: v0.1.0
**Release Date**: 2025-12-30