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defaults: | ||
- override hydra/job_logging: none | ||
- override hydra/hydra_logging: none | ||
- _self_ | ||
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start_date: 2024-01-01T00:00:00 | ||
end_date: 2024-01-02T00:00:00 | ||
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checkpoint_path: /pfs/lustrep4/scratch/project_465001383/aifs/experiments/reference/o96_pretrain/checkpoint/3fb85b72ba9647d5ae4fe86ce1b5a885/inference-last.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: ['cp', 'u_600', 'v_600', 'z_600', 't_600', 'q_600', 'w_600', 'longitude', 'latitude'] | ||
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: /pfs/lustrep4//scratch/project_465001383/aifs/dataset/ERA5/ | ||
files: | ||
global_dataset: aifs-od-an-oper-0001-mars-n320-2023-2024-6h-v2.zarr | ||
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num_gpus_per_node: 8 | ||
num_gpus_per_model: 8 | ||
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] | ||
# - verif: | ||
# filename_pattern: verif/2t/n320_at_ref.nc | ||
# variable: 2t | ||
# obs: | ||
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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'] |