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Roadmap¤

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

Current Status¤

Artifex is under active development. Core functionality is implemented and tested, but the library continues to evolve.

Completed Features¤

  • 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

  • Geometric: Point clouds, meshes, voxels

  • Infrastructure

  • Unified frozen dataclass configuration system
  • Protocol-based architecture
  • Factory pattern for model creation
  • Comprehensive test coverage (80%+)
  • GPU/CPU device management
  • Composable loss functions

In Progress¤

  • Advanced Scaling Features (experimental)
  • Multi-GPU training support
  • TPU compatibility improvements
  • Gradient accumulation

  • Memory optimization

  • Benchmark Suite (in progress)

  • FID, IS metrics for images
  • Perplexity for text
  • Geometric evaluation metrics

  • Standardized benchmark datasets

  • Documentation (ongoing)

  • API reference completion
  • Tutorial expansion
  • Example coverage

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

Version Milestones¤

v0.1.x (Current)¤

Focus: Core functionality and stability

  • All basic model types implemented
  • Frozen dataclass configuration system
  • Comprehensive testing
  • Documentation foundation

v0.2.x (Planned)¤

Focus: Performance and scaling

  • 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 for contribution:

  1. Documentation: Examples, tutorials, API docs
  2. Testing: Expanding test coverage
  3. Models: New model implementations
  4. Performance: Optimization PRs

See the GitHub Issues for current tasks and feature requests.

See Also¤