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Roadmap¤

This document outlines the development status and planned improvements for Artifex.

Current Status: Major Refactoring¤

Artifex is undergoing a significant architectural refactoring. The library is being restructured for better modularity, maintainability, and API consistency.

Note: During this refactoring period:

  • APIs may change without deprecation warnings
  • Some tests may fail or be skipped
  • Documentation may not reflect current implementation

Components Under Refactoring¤

  • Core Model Implementations
  • VAE Family: VAE, Beta-VAE, VQ-VAE, Conditional VAE
  • GAN Family: DCGAN, WGAN, StyleGAN, CycleGAN, PatchGAN
  • Diffusion Models: DDPM, DDIM, Score-based, DiT, Latent Diffusion
  • Normalizing Flows: RealNVP, Glow, MAF, IAF, Neural Spline Flows
  • Energy-Based Models: Langevin dynamics, MCMC sampling
  • Autoregressive Models: PixelCNN, WaveNet, Transformer-based

  • Geometric Models: Point clouds, meshes, SE(3) molecular flows

  • Multi-Modal Support

  • Image: Convolutional architectures, quality metrics
  • Text: Tokenization, language modeling
  • Audio: Spectral processing, WaveNet
  • Protein: Structure generation with physical constraints
  • Tabular: Mixed data types
  • Timeseries: Sequential patterns
  • Molecular: Chemical structure generation

  • Geometric: Point clouds, meshes, voxels

  • Infrastructure

  • Unified frozen dataclass configuration system
  • Protocol-based architecture
  • Factory pattern for model creation
  • GPU/CPU device management
  • Explicit functional loss building blocks

In Progress¤

  • Test Suite Restructuring
  • Reorganizing test hierarchy
  • Improving test isolation
  • Updating test fixtures

  • Coverage reporting improvements

  • API Stabilization

  • Consistent method signatures
  • Clear public/private boundaries
  • Improved error messages

  • Type annotation completion

  • Documentation Updates

  • Syncing docs with code changes
  • Updating code examples
  • API reference refresh

Planned Features¤

  • Performance Optimizations
  • JIT compilation improvements
  • Memory-efficient attention
  • Gradient checkpointing

  • Mixed precision training

  • Additional Model Variants

  • Consistency models
  • Flow matching
  • Rectified flows

  • Additional transformer architectures

  • Extended Modality Support

  • Video generation
  • 3D scene understanding

  • Multi-modal alignment

  • Training Improvements

  • Advanced learning rate schedules
  • Automatic hyperparameter tuning

  • Training visualization dashboard

  • Scaling Features

  • Multi-GPU training support
  • TPU compatibility
  • Gradient accumulation
  • Memory optimization

Version Milestones¤

v0.1.x (Current - Refactoring)¤

Focus: Architecture refactoring and API stabilization

  • Restructuring codebase for better modularity
  • Stabilizing public APIs
  • Improving test coverage and reliability
  • Updating documentation

v0.2.x (Planned)¤

Focus: Stability and performance

  • Stable, documented APIs
  • Multi-GPU support
  • Memory optimizations
  • Extended benchmark suite
  • Performance profiling tools

v0.3.x (Planned)¤

Focus: Advanced features

  • Additional model architectures
  • Video and multi-modal support
  • Advanced fine-tuning methods
  • Production deployment tools

Contributing¤

We welcome contributions in all areas. Priority areas during the refactoring period:

  1. Testing: Helping stabilize and expand test coverage
  2. Documentation: Keeping docs in sync with code changes
  3. Bug Reports: Reporting issues encountered during refactoring
  4. Code Review: Reviewing refactoring PRs

See the GitHub Issues for current tasks and feature requests.

See Also¤