| # IRIS: Iterative Refinement Image Synthesizer |
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| A mobile-first image generation architecture designed from recent research (2025-2026). |
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| **17/17 tests pass** — all modules verified for shape correctness, gradient flow, weight sharing, numerical stability, and actual training convergence. |
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| See `iris/README.md` for full documentation. |
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| ## Quick Start |
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| ```python |
| from iris import IRIS, get_model_config, flow_matching_loss, euler_sample |
| import torch |
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| model = IRIS(**get_model_config("iris-small")) # 40M params |
| z_0 = torch.randn(4, 32, 16, 16) * 2.5 |
| text_emb = torch.randn(4, 16, 512) |
| losses = flow_matching_loss(model, z_0, text_emb, num_iterations=4) |
| losses["loss"].backward() |
| ``` |
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| ## Model Variants |
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| | Config | Params | Tokens | FP16 Memory | |
| |--------|--------|--------|-------------| |
| | iris-tiny | 10.3M | 16 | 21 MB | |
| | iris-small | 40.0M | 16 | 80 MB | |
| | iris-base | 53.4M | 64 | 107 MB | |
| | iris-medium | 181.2M | 64 | 362 MB | |
| | iris-large | 430.9M | 64 | 862 MB | |
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