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Added config files for legacy run (legendary_gnome) and o96 single gr…
…id model.
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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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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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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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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'] |