| """ |
| IRIS: Iterative Refinement Image Synthesizer |
| ============================================= |
| |
| A mobile-first image generation architecture that combines: |
| - PDE-SSM spatial mixing (O(N log N), native 2D, no scanning) |
| - Weight-shared iterative refinement (6 blocks × R iterations) |
| - Structured latent canvas (DC-AE with coarse-to-fine channels) |
| - Tiny PixelShuffle decoder (0.1M params) |
| - Multi-Query Attention + 2D RoPE |
| - Flow matching training with logit-normal timestep sampling |
| |
| Usage: |
| from iris.model import IRIS |
| from iris.configs import get_model_config |
| from iris.flow_matching import flow_matching_loss, euler_sample |
| |
| model = IRIS(**get_model_config("iris-small")) |
| |
| # Training |
| losses = flow_matching_loss(model, latents, text_embeddings) |
| |
| # Sampling |
| images = euler_sample(model, noise, text_embeddings, num_steps=20) |
| """ |
|
|
| from .model import IRIS |
| from .configs import get_model_config, CONFIGS |
| from .flow_matching import flow_matching_loss, euler_sample |
|
|
| __version__ = "0.1.0" |
| __all__ = ["IRIS", "get_model_config", "CONFIGS", "flow_matching_loss", "euler_sample"] |
|
|
