| { |
| "model_name": "DINCAE", |
| "model_type": "dincae", |
| "architectures": ["DINCAE"], |
| "framework": "PyTorch", |
| "domain": "ocean", |
| "task": "probabilistic-sst-gap-reconstruction", |
| "implementation": { |
| "entry_point": "model/dincae.py", |
| "scope": "core-method reduced-spatial-scale engineering reproduction with paper dimensions recorded separately", |
| "train_script": "scripts/train.py", |
| "inference_script": "scripts/inference.py", |
| "evaluation_script": "scripts/result.py", |
| "synthetic_data_script": "scripts/fake_data.py" |
| }, |
| "architecture": { |
| "engineering_input_shape": ["B", 10, 32, 32], |
| "engineering_output_shape": ["B", 2, 32, 32], |
| "paper_input_shape": ["B", 10, 112, 112], |
| "paper_output_shape": ["B", 2, 112, 112], |
| "engineering_filters": [8, 12, 18, 27], |
| "paper_filters": [16, 24, 36, 54], |
| "paper_bottleneck": [2646, 529, 2646], |
| "decoder": "nearest-neighbor upsampling with encoder skips" |
| }, |
| "data": { |
| "dataset": "AVHRR Pathfinder daily SST", |
| "format_version": "dincae_avhrr_v1", |
| "paper_period": "1985-2009", |
| "paper_time_steps": 5266, |
| "paper_grid": [112, 112], |
| "engineering_grid": [32, 32], |
| "input_channels": 10, |
| "output_channels": 2, |
| "synthetic": true |
| }, |
| "configuration_sources": [ |
| "conf/config.yaml", |
| "model/dincae.py", |
| "scripts/fake_data.py", |
| "scripts/train.py", |
| "scripts/inference.py", |
| "scripts/result.py" |
| ] |
| } |
|
|
