| { |
| "model_name": "Surya", |
| "model_type": "surya", |
| "architectures": [ |
| "Surya" |
| ], |
| "framework": "PyTorch", |
| "domain": "heliophysics", |
| "task": "solar-dynamics-forecasting", |
| "implementation": { |
| "entry_point": "model/surya.py", |
| "scope": "spectral-gated and long-short-attention autoregressive forecasting of aligned SDO AIA/HMI observations", |
| "train_script": "scripts/train.py", |
| "inference_script": "scripts/inference.py", |
| "evaluation_script": "scripts/result.py", |
| "synthetic_data_script": "scripts/fake_data.py" |
| }, |
| "architecture": { |
| "family": "spectral-gated spatiotemporal transformer", |
| "image_size": 32, |
| "patch_size": 4, |
| "input_channels": 13, |
| "input_steps": 2, |
| "forecast_steps": 4, |
| "embed_dim": 64, |
| "depth": 4, |
| "spectral_blocks": 1, |
| "num_heads": 4, |
| "window_size": 3, |
| "global_tokens": 4, |
| "prediction_mode": "autoregressive" |
| }, |
| "data": { |
| "datasets": [ |
| "SDO/AIA", |
| "SDO/HMI" |
| ], |
| "protocol": "synthetic_SDO_AIA_HMI", |
| "format": "NPZ", |
| "input_key": "inputs", |
| "input_shape": [ |
| "N", |
| 2, |
| 13, |
| "H", |
| "W" |
| ], |
| "target_key": "targets", |
| "target_shape": [ |
| "N", |
| "S", |
| 13, |
| "H", |
| "W" |
| ], |
| "activity_key": "activity", |
| "activity_shape": [ |
| "N", |
| "S" |
| ], |
| "channel_names": [ |
| "AIA_94", |
| "AIA_131", |
| "AIA_171", |
| "AIA_193", |
| "AIA_211", |
| "AIA_304", |
| "AIA_335", |
| "AIA_1600", |
| "HMI_magnetogram", |
| "HMI_continuum", |
| "HMI_doppler", |
| "HMI_vector_x", |
| "HMI_vector_y" |
| ], |
| "normalization": "signum-log followed by configured per-channel affine normalization", |
| "default_train_file": "data/train.npz", |
| "default_test_file": "data/test.npz" |
| }, |
| "configuration_sources": [ |
| "conf/config.yaml", |
| "model/surya.py", |
| "scripts/fake_data.py", |
| "scripts/train.py", |
| "scripts/inference.py", |
| "scripts/result.py" |
| ] |
| } |
|
|
