| { |
| "model_name": "Earthformer", |
| "model_type": "earthformer", |
| "architectures": [ |
| "Earthformer" |
| ], |
| "framework": "PyTorch", |
| "domain": "climate-and-atmosphere", |
| "task": "spatiotemporal-forecasting", |
| "implementation": { |
| "entry_point": "model/earthformer.py", |
| "scope": "two-level hierarchical Cuboid Attention space-time Transformer with BTHWC input and output" |
| }, |
| "architecture": { |
| "family": "hierarchical space-time Transformer with Cuboid Attention", |
| "attention_mechanism": "cuboid-window attention with optional global vectors", |
| "input_format": "BTHWC", |
| "encoder": { |
| "levels": 2, |
| "stem": "Conv2d 3x3 stride 2", |
| "downsample": "Conv2d 3x3 stride 2", |
| "cuboid_pattern": [ |
| [ |
| 2, |
| 4, |
| 4 |
| ] |
| ] |
| }, |
| "decoder": { |
| "cuboid_pattern": "axial", |
| "cross_attention": "CuboidCross(T,1,1): future queries attend to history at each spatial site", |
| "prediction": "learned future query with per-frame up-projection and encoder skip connection" |
| }, |
| "activation": "GELU", |
| "normalization": "LayerNorm", |
| "repository_default_config": { |
| "purpose": "CPU smoke verification with synthetic SEVIR data", |
| "dims": [ |
| 4, |
| 8 |
| ], |
| "depths": [ |
| 1, |
| 1 |
| ], |
| "heads": 1, |
| "num_global_vectors": 1, |
| "ff_ratio": 2.0, |
| "dropout": 0.0 |
| } |
| }, |
| "data": { |
| "dataset": "SEVIR", |
| "variable": "vertically_integrated_liquid", |
| "frame_interval_minutes": 5, |
| "input_length": 13, |
| "output_length": 12, |
| "channels": 1, |
| "official_spatial_size": [ |
| 384, |
| 384 |
| ], |
| "official_sampling": "sequent with stride 12", |
| "default_smoke_spatial_size": [ |
| 32, |
| 32 |
| ], |
| "normalization": "unit" |
| }, |
| "configuration_sources": [ |
| "conf/config.yaml", |
| "model/earthformer.py", |
| "script/data_loader.py", |
| "configuration.json" |
| ] |
| } |
|
|
