| work_dir: ./results | |
| ckpt_dir: ./results/checkpoints/ | |
| log_dir: ./results/logs/ | |
| print_config: true | |
| ignore_warnings: true | |
| test_after_training: false | |
| save_config_to_wandb: true | |
| verbose: true | |
| seed: 11 | |
| torch_matmul_precision: high | |
| name: FV3GFS-Ipol6h | |
| name_suffix: null | |
| suffix: null | |
| trainer: | |
| profiler: {} | |
| _target_: pytorch_lightning.Trainer | |
| accelerator: gpu | |
| devices: 4 | |
| strategy: ddp_find_unused_parameters_false | |
| min_epochs: 1 | |
| max_epochs: 60 | |
| gradient_clip_val: 0.5 | |
| accumulate_grad_batches: 3 | |
| precision: 16 | |
| num_sanity_val_steps: 1 | |
| val_check_interval: 1.0 | |
| deterministic: true | |
| log_every_n_steps: 50 | |
| model: | |
| _target_: src.models.sfno.sfnonet.SphericalFourierNeuralOperatorNet | |
| embed_dim: 256 | |
| spectral_transform: sht | |
| filter_type: linear | |
| operator_type: dhconv | |
| num_layers: 8 | |
| use_mlp: true | |
| mlp_ratio: 2.0 | |
| scale_factor: 1 | |
| separable: false | |
| spectral_layers: 3 | |
| activation_function: gelu | |
| pos_embed: true | |
| dropout_filter: 0 | |
| dropout_mlp: 0.1 | |
| pos_emb_dropout: 0.0 | |
| drop_path_rate: 0.1 | |
| num_blocks: 8 | |
| sparsity_threshold: 0.0 | |
| normalization_layer: instance_norm | |
| hard_thresholding_fraction: 1.0 | |
| checkpointing: 0 | |
| time_scale_shift_before_filter: true | |
| loss_function: | |
| _target_: src.losses.losses.LpLoss | |
| p: 2 | |
| relative: true | |
| name: SFNO | |
| verbose: true | |
| num_conditional_channels: 0 | |
| with_time_emb: true | |
| datamodule: | |
| data_dir: /data | |
| batch_size: 6 | |
| eval_batch_size: 2 | |
| num_workers: 8 | |
| pin_memory: false | |
| persistent_workers: true | |
| drop_last: false | |
| shuffle_train_data: true | |
| verbose: true | |
| window: 1 | |
| horizon: 6 | |
| max_train_samples: null | |
| max_val_samples: 80 | |
| forcing_names: | |
| - DSWRFtoa | |
| in_names: | |
| - HGTsfc | |
| - PRESsfc | |
| - surface_temperature | |
| - air_temperature_0 | |
| - air_temperature_1 | |
| - air_temperature_2 | |
| - air_temperature_3 | |
| - air_temperature_4 | |
| - air_temperature_5 | |
| - air_temperature_6 | |
| - air_temperature_7 | |
| - specific_total_water_0 | |
| - specific_total_water_1 | |
| - specific_total_water_2 | |
| - specific_total_water_3 | |
| - specific_total_water_4 | |
| - specific_total_water_5 | |
| - specific_total_water_6 | |
| - specific_total_water_7 | |
| - eastward_wind_0 | |
| - eastward_wind_1 | |
| - eastward_wind_2 | |
| - eastward_wind_3 | |
| - eastward_wind_4 | |
| - eastward_wind_5 | |
| - eastward_wind_6 | |
| - eastward_wind_7 | |
| - northward_wind_0 | |
| - northward_wind_1 | |
| - northward_wind_2 | |
| - northward_wind_3 | |
| - northward_wind_4 | |
| - northward_wind_5 | |
| - northward_wind_6 | |
| - northward_wind_7 | |
| out_names: | |
| - PRESsfc | |
| - surface_temperature | |
| - air_temperature_0 | |
| - air_temperature_1 | |
| - air_temperature_2 | |
| - air_temperature_3 | |
| - air_temperature_4 | |
| - air_temperature_5 | |
| - air_temperature_6 | |
| - air_temperature_7 | |
| - specific_total_water_0 | |
| - specific_total_water_1 | |
| - specific_total_water_2 | |
| - specific_total_water_3 | |
| - specific_total_water_4 | |
| - specific_total_water_5 | |
| - specific_total_water_6 | |
| - specific_total_water_7 | |
| - eastward_wind_0 | |
| - eastward_wind_1 | |
| - eastward_wind_2 | |
| - eastward_wind_3 | |
| - eastward_wind_4 | |
| - eastward_wind_5 | |
| - eastward_wind_6 | |
| - eastward_wind_7 | |
| - northward_wind_0 | |
| - northward_wind_1 | |
| - northward_wind_2 | |
| - northward_wind_3 | |
| - northward_wind_4 | |
| - northward_wind_5 | |
| - northward_wind_6 | |
| - northward_wind_7 | |
| auxiliary_names: null | |
| prediction_horizon: null | |
| _target_: src.datamodules.fv3gfs_ensemble.FV3GFSEnsembleDataModule | |
| data_dir_stats: /data/stats | |
| training_sub_paths: null | |
| prescriber: | |
| _target_: fme.core.prescriber.Prescriber | |
| prescribed_name: surface_temperature | |
| mask_name: ocean_fraction | |
| mask_value: 1 | |
| module: | |
| optimizer: | |
| name: adamw | |
| lr: 0.0004 | |
| weight_decay: 1.0e-05 | |
| eps: 1.0e-08 | |
| betas: | |
| - 0.9 | |
| - 0.99 | |
| scheduler: | |
| _target_: torch.optim.lr_scheduler.CosineAnnealingLR | |
| T_max: 60 | |
| monitor: val/avg/crps | |
| mode: min | |
| name: '' | |
| use_ema: true | |
| ema_decay: 0.9999 | |
| enable_inference_dropout: true | |
| num_predictions: 16 | |
| prediction_inputs_noise: 0.0 | |
| logging_infix: '' | |
| log_every_step_up_to: 1000 | |
| verbose: true | |
| seed: 11 | |
| work_dir: ./results | |
| _target_: src.experiment_types.interpolation.InterpolationExperiment | |
| stack_window_to_channel_dim: true | |
| callbacks: | |
| model_checkpoint: | |
| _target_: pytorch_lightning.callbacks.ModelCheckpoint | |
| monitor: val/avg/crps | |
| mode: min | |
| save_top_k: 1 | |
| save_last: true | |
| verbose: true | |
| dirpath: ./results/checkpoints/01HER6GMAMHXPA62240XSV4TD4 | |
| filename: FV3GFS-Ipol6h_None_epoch{epoch:03d}_seed11 | |
| auto_insert_metric_name: false | |
| watch_model: | |
| _target_: src.utilities.wandb_callbacks.WatchModel | |
| log: all | |
| log_freq: 500 | |
| summarize_best_val_metric: | |
| _target_: src.utilities.wandb_callbacks.SummarizeBestValMetric | |
| learning_rate_logging: | |
| _target_: pytorch_lightning.callbacks.LearningRateMonitor | |
| logger: | |
| wandb: | |
| _target_: src.utilities.wandb_callbacks.MyWandbLogger | |
| entity: ai2cm | |
| name: FV3GFS-Ipol6h_SFNO_EMA_256x8h_L2R_44lr_10mlpDr_10dpr_15wd_cos_11seed | |
| tags: | |
| - fv3gfs | |
| - interpolation | |
| notes: '...' | |
| project: FME-v2-salva | |
| group: FV3GFS-Ipol6h_SFNO_EMA_256x8h_L2R_44lr_10mlpDr_10dpr_15wd_cos | |
| resume: allow | |
| reinit: true | |
| mode: online | |
| save_dir: ./results/ | |
| offline: false | |
| id: 01HER6GMAMHXPA62240XSV4TD4 | |
| log_model: false | |
| prefix: '' | |
| n_gpus: 4 | |
| effective_batch_size: 72 | |