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moved config folder outside bris module
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,86 @@ | ||
| defaults: | ||
| - override hydra/job_logging: none | ||
| - override hydra/hydra_logging: none | ||
| - _self_ | ||
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| start_date: 2024-11-24T12:00:00 | ||
| end_date: 2024-11-24T18:00:00 | ||
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| checkpoint_path: /lustre/storeB/project/nwp/bris/aram/fix-memory-issue/experiments2/inference-aifs-by_step-epoch_000-step_000150.ckpt | ||
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| leadtimes: 12 | ||
| timestep: 6h | ||
| frequency: 6h | ||
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| deterministic: True | ||
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| lam_dataset: ${hardware.paths.data}${hardware.files.lam_dataset} | ||
| global_dataset: ${hardware.paths.data}${hardware.files.global_dataset} | ||
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| # If the user wants to release GPU cache and memory | ||
| # This option releases unused cached/memory used by torch | ||
| release_cache: False | ||
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| # Determine how much the encoder and decoder is chunked | ||
| inference_num_chunks: 16 | ||
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| dataloader: | ||
| batch_size: 1 | ||
| prefetch_factor: 2 | ||
| num_workers: 1 | ||
| pin_memory: True | ||
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| read_group_size: 1 #Do not change this, not implemented properly | ||
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| predict: | ||
| cutout: | ||
| - dataset: ${lam_dataset} | ||
| - dataset: ${global_dataset} | ||
| rename: | ||
| q_600 : tp # tp does not exist in the global dataset. tp is diagnostic, rename is sufficient | ||
| min_distance_km: 0 | ||
| adjust: all | ||
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| datamodule: | ||
| _target_: anemoi.training.data.dataset.NativeGridDataset | ||
| _convert_: all | ||
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| hardware: | ||
| paths: | ||
| data: /lustre/storeB/project/nwp/bris/aram/fix-memory-issue/debug_files/ | ||
| files: | ||
| lam_dataset: meps_20241124T18Z.zarr | ||
| global_dataset: ifs_20241124T18Z.zarr | ||
| dataset_obs: name_of_dataset | ||
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| num_gpus_per_node: 1 | ||
| num_gpus_per_model: 1 | ||
| num_nodes: 1 | ||
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| model: | ||
| _target_: bris.model.BrisPredictor | ||
| _convert_: all | ||
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| checkpoints: | ||
| - my_interpolator: | ||
| type: interpolator | ||
| path: interpolator.ckpt | ||
| - my_forecaster: | ||
| type: forecaster | ||
| path: forecast.ckpt | ||
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| routing: | ||
| - decoder_index: 0 | ||
| domain: 0 | ||
| outputs: | ||
| - netcdf: | ||
| filename_pattern: meps_pred_%Y%m%dT%HZ.nc | ||
| variables: [2t, 2d] | ||
| - decoder_index: 0 | ||
| domain: 1 | ||
| outputs: | ||
| - netcdf: | ||
| filename_pattern: era_pred_%Y%m%dT%HZ.nc | ||
| variables: [2t, 2d] | ||
|
|
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,192 @@ | ||
| defaults: | ||
| - override hydra/job_logging: none | ||
| - override hydra/hydra_logging: none | ||
| - _self_ | ||
|
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||
| start_date: 2023-11-24T12:00:00 | ||
| end_date: 2023-11-24T18:00:00 | ||
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| checkpoint_path: /lustre/storeB/project/nwp/aifs/havardhh/bris-inference/inference-anemoi-by_time-epoch_075-step_149656.ckpt | ||
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| leadtimes: 12 | ||
| timestep: 6h | ||
| frequency: 6h | ||
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| deterministic: True | ||
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| global_dataset: ${hardware.paths.data}${hardware.files.global_dataset} | ||
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| # If the user wants to release GPU cache and memory | ||
| # This option releases unused cached/memory used by torch | ||
| release_cache: False | ||
|
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| dataloader: | ||
| batch_size: 1 | ||
| prefetch_factor: 2 | ||
| num_workers: 1 | ||
| pin_memory: True | ||
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| read_group_size: 1 #Do not change this, not implemented properly | ||
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| predict: | ||
| dataset: ${global_dataset} | ||
| drop: ['sdor', 'slor', 'cp', 'u_600', 'v_600', 'z_600', 't_600', 'q_600', 'w_600'] | ||
| start: ${start_date} | ||
| end: ${end_date} | ||
| frequency: ${frequency} | ||
| reorder: ${reorder} | ||
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| datamodule: | ||
| _target_: anemoi.training.data.dataset.NativeGridDataset #anemoi.training.data.dataset.ZipDataset | ||
| _convert_: all | ||
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| hardware: | ||
| paths: | ||
| data: /lustre/storeB/project/nwp/aifs/datasets/ | ||
| files: | ||
| global_dataset: aifs-od-an-oper-0001-mars-o96-2016-2023-6h-v6.zarr | ||
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| num_gpus_per_node: 1 | ||
| num_gpus_per_model: 1 | ||
| num_nodes: 1 | ||
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| model: | ||
| _target_: bris.model.BrisPredictor | ||
| _convert_: all | ||
|
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||
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| checkpoints: | ||
| - my_interpolator: | ||
| type: interpolator | ||
| path: interpolator.ckpt | ||
| - my_forecaster: | ||
| type: forecaster | ||
| path: forecast.ckpt | ||
|
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||
| routing: | ||
| - decoder_index: 0 | ||
| domain: 0 | ||
| outputs: | ||
| - netcdf: | ||
| filename_pattern: era_pred_%Y%m%dT%HZ.nc | ||
| variables: [2t, 2d] | ||
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| # - decoder_index: 0 | ||
| # domain: 1 | ||
| # outputs: | ||
| # - verif: | ||
| # filename: global/2t/%R.nc # global/2t/legendary_gnome.nc | ||
| # variable: 2t | ||
| # thresholds: [0, 10, 20] | ||
| # quantile_levels: [0.1, 0.9] | ||
| # obs: | ||
| # - netcdf: | ||
| # path: 2t.nc | ||
| # - verif: | ||
| # filename: global/mslp/%R.nc # global/2t/legendary_gnome.nc | ||
| # variable: mslp | ||
| # thresholds: [970, 1000, 1020] | ||
| # quantile_levels: [0.1, 0.9] | ||
| # obs: | ||
| # - netcdf: | ||
| # path: mslp.nc | ||
| # | ||
| # - decoder_index: 1 | ||
| # domain: 0 | ||
| # outputs: | ||
| # - netcdf: | ||
| # filename_pattern: netatmo_%Y%m%dT%HZ.nc | ||
|
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| reorder: ['10u', | ||
| '10v', | ||
| '2d', | ||
| '2t', | ||
| 'cos_julian_day', | ||
| 'cos_latitude', | ||
| 'cos_local_time', | ||
| 'cos_longitude', | ||
| 'insolation', | ||
| 'lsm', | ||
| 'msl', | ||
| 'q_100', | ||
| 'q_1000', | ||
| 'q_150', | ||
| 'q_200', | ||
| 'q_250', | ||
| 'q_300', | ||
| 'q_400', | ||
| 'q_50', | ||
| 'q_500', | ||
| 'q_700', | ||
| 'q_850', | ||
| 'q_925', | ||
| 'sin_julian_day', | ||
| 'sin_latitude', | ||
| 'sin_local_time', | ||
| 'sin_longitude', | ||
| 'skt', | ||
| 'sp', | ||
| 't_100', | ||
| 't_1000', | ||
| 't_150', | ||
| 't_200', | ||
| 't_250', | ||
| 't_300', | ||
| 't_400', | ||
| 't_50', | ||
| 't_500', | ||
| 't_700', | ||
| 't_850', | ||
| 't_925', | ||
| 'tcw', | ||
| 'tp', | ||
| 'u_100', | ||
| 'u_1000', | ||
| 'u_150', | ||
| 'u_200', | ||
| 'u_250', | ||
| 'u_300', | ||
| 'u_400', | ||
| 'u_50', | ||
| 'u_500', | ||
| 'u_700', | ||
| 'u_850', | ||
| 'u_925', | ||
| 'v_100', | ||
| 'v_1000', | ||
| 'v_150', | ||
| 'v_200', | ||
| 'v_250', | ||
| 'v_300', | ||
| 'v_400', | ||
| 'v_50', | ||
| 'v_500', | ||
| 'v_700', | ||
| 'v_850', | ||
| 'v_925', | ||
| 'w_100', | ||
| 'w_1000', | ||
| 'w_150', | ||
| 'w_200', | ||
| 'w_250', | ||
| 'w_300', | ||
| 'w_400', | ||
| 'w_50', | ||
| 'w_500', | ||
| 'w_700', | ||
| 'w_850', | ||
| 'w_925', | ||
| 'z', | ||
| 'z_100', | ||
| 'z_1000', | ||
| 'z_150', | ||
| 'z_200', | ||
| 'z_250', | ||
| 'z_300', | ||
| 'z_400', | ||
| 'z_50', | ||
| 'z_500', | ||
| 'z_700', | ||
| 'z_850', | ||
| 'z_925'] |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,96 @@ | ||
| defaults: | ||
| - override hydra/job_logging: none | ||
| - override hydra/hydra_logging: none | ||
| - _self_ | ||
|
|
||
| start_date: 2024-12-03T00:00:00 | ||
| end_date: 2024-12-03T06:00:00 | ||
|
|
||
| checkpoint_path: /lustre/storeB/project/nwp/aifs/aram/fmi/checkpoint/aifs_inference_o96_10k_stretched_grid.ckpt | ||
|
|
||
| leadtimes: 12 | ||
| timestep: 6h | ||
| frequency: 6h | ||
|
|
||
| deterministic: True | ||
|
|
||
| lam_dataset: ${hardware.paths.data}${hardware.files.lam_dataset} | ||
| global_dataset: ${hardware.paths.data}${hardware.files.global_dataset} | ||
|
|
||
| # If the user wants to release GPU cache and memory | ||
| # This option releases unused cached/memory used by torch | ||
| release_cache: False | ||
|
|
||
| dataset: | ||
| cutout: | ||
| - dataset: ${hardware.paths.data}${hardware.files.lam_dataset} | ||
| - dataset: ${hardware.paths.data}${hardware.files.global_dataset} | ||
| neighbours: 2 | ||
| min_distance_km: 0 | ||
| adjust: all | ||
|
|
||
| dataloader: | ||
| batch_size: 1 | ||
| prefetch_factor: 2 | ||
| num_workers: 1 | ||
| pin_memory: True | ||
|
|
||
| read_group_size: 1 #Do not change this, not implemented properly | ||
|
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| predict: | ||
| # cutout: | ||
| # - dataset: ${lam_dataset} | ||
| # # following ckpt does not support 800 levels, dropping these | ||
| # drop: [u_800, v_800, w_800, z_800, q_800,t_800] | ||
| # - dataset: ${global_dataset} | ||
| # drop: [u_800, v_800, w_800, z_800, q_800,t_800] | ||
| # neighbours: 2 | ||
| # min_distance_km: 0 | ||
| # adjust: all | ||
| dataset: ${dataset} | ||
| drop: [u_800, v_800, w_800, z_800, q_800,t_800] | ||
| start: ${start_date} | ||
| end: ${end_date} | ||
|
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| datamodule: | ||
| _target_: anemoi.training.data.dataset.NativeGridDataset | ||
| _convert_: all | ||
|
|
||
| hardware: | ||
| paths: | ||
| data: /lustre/storeB/project/nwp/aifs/aram/fmi/dataset/ | ||
| files: | ||
| lam_dataset: meps-2024120306.zarr | ||
| global_dataset: hres-2024120306.zarr | ||
|
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| num_gpus_per_node: 1 | ||
| num_gpus_per_model: 1 | ||
| num_nodes: 1 | ||
|
|
||
| model: | ||
| _target_: bris.model.BrisPredictor | ||
| _convert_: all | ||
|
|
||
|
|
||
| checkpoints: | ||
| - my_interpolator: | ||
| type: interpolator | ||
| path: interpolator.ckpt | ||
| - my_forecaster: | ||
| type: forecaster | ||
| path: forecast.ckpt | ||
|
|
||
| routing: | ||
| - decoder_index: 0 | ||
| domain: 0 | ||
| outputs: | ||
| - netcdf: | ||
| filename_pattern: fmi_meps_pred_%Y%m%dT%HZ.nc | ||
| variables: [2t, 2d] | ||
| - decoder_index: 0 | ||
| domain: 1 | ||
| outputs: | ||
| - netcdf: | ||
| filename_pattern: fmi_era_pred_%Y%m%dT%HZ.nc | ||
| variables: [2t, 2d] | ||
|
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