| { |
| "model_name": "PrecipitationSRCNN", |
| "model_type": "precipitation_srcnn", |
| "architectures": [ |
| "PrecipitationSRCNN" |
| ], |
| "framework": "PyTorch", |
| "domain": "weather", |
| "task": "daily precipitation statistical downscaling", |
| "implementation": { |
| "entry_point": "model/precipitationsrcnn.py", |
| "scope": "Core-method and full-data-dimension reduced-scale end-to-end engineering reproduction", |
| "train_script": "scripts/train.py", |
| "inference_script": "scripts/inference.py", |
| "evaluation_script": "scripts/result.py", |
| "synthetic_data_script": "scripts/fake_data.py" |
| }, |
| "architecture": { |
| "input_shape": ["B", 2, 216, 488], |
| "output_shape": ["B", 1, 216, 488], |
| "paper_hidden_channels": [64, 32], |
| "kernels": [9, 1, 5] |
| }, |
| "data": { |
| "format_version": "precipitation_srcnn_v1", |
| "input_variables": ["precipitation", "elevation"], |
| "target_variable": "daily precipitation", |
| "target_grid": [216, 488], |
| "unit": "mm/day" |
| }, |
| "configuration_sources": [ |
| "conf/config.yaml", |
| "model/precipitationsrcnn.py", |
| "scripts/fake_data.py", |
| "scripts/train.py", |
| "scripts/inference.py", |
| "scripts/result.py" |
| ] |
| } |
|
|
