| { |
| "model_name": "DGMR", |
| "model_type": "dgmr", |
| "architectures": [ |
| "DGMR" |
| ], |
| "framework": "PyTorch", |
| "domain": "climate-and-atmosphere", |
| "task": "precipitation-nowcasting", |
| "implementation": { |
| "entry_point": "model/dgmr.py", |
| "scope": "YAML-configured DGMR conditional GAN wrapper with vendored Open Climate Fix generator, spatial and temporal discriminators, and training losses" |
| }, |
| "architecture": { |
| "family": "conditional generative adversarial network for probabilistic radar nowcasting", |
| "generator": "context conditioning stack plus latent conditioning stack and a four-scale ConvGRU autoregressive sampler", |
| "discriminator": "combined spatial and temporal discriminators with spectrally normalized residual blocks", |
| "training_objective": "hinge GAN loss plus weighted grid-cell regularizer", |
| "input_format": "BTCHW", |
| "output_format": "BTCHW", |
| "activation": "ReLU", |
| "normalization": "BatchNorm", |
| "repository_default_config": { |
| "purpose": "small connectivity-validation configuration", |
| "num_context": 4, |
| "forecast_steps": 6, |
| "input_channels": 1, |
| "output_shape": 128, |
| "conv_type": "standard", |
| "latent_channels": 384, |
| "context_channels": 192, |
| "generation_steps": 6, |
| "grid_lambda": 20.0, |
| "precip_weight_cap": 24.0 |
| }, |
| "paper_configuration": { |
| "num_context": 4, |
| "forecast_steps": 18, |
| "input_channels": 1, |
| "output_shape": 256, |
| "latent_channels": 768, |
| "context_channels": 384, |
| "generation_steps": 6, |
| "grid_lambda": 20.0, |
| "precip_weight_cap": 24.0 |
| } |
| }, |
| "data": { |
| "dataset": "ERA5Datapipe-compatible HDF5 placeholder radar sequences", |
| "variable": "rain_radar", |
| "input_length": 4, |
| "output_length": 6, |
| "channels": 1, |
| "default_smoke_spatial_size": [ |
| 128, |
| 128 |
| ], |
| "paper_frame_interval_minutes": 5, |
| "paper_output_length": 18, |
| "paper_spatial_size": [ |
| 256, |
| 256 |
| ], |
| "normalization": "identity statistics in synthetic data; real-data statistics are read from HDF5" |
| }, |
| "configuration_sources": [ |
| "conf/config.yaml", |
| "model/dgmr.py", |
| "model/dgmr_official/", |
| "scripts/train.py", |
| "scripts/fake_data.py", |
| "README.md" |
| ] |
| } |
|
|
