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### base config ###
full_field: &FULL_FIELD
loss: 'l2'
lr: 1E-3
scheduler: 'ReduceLROnPlateau'
retrain: !!bool False
num_data_workers: 4
dt: 1 # how many timesteps ahead the model will predict
n_history: 0 #how many previous timesteps to consider
prediction_type: 'iterative'
prediction_length: 41 #applicable only if prediction_type == 'iterative'
n_initial_conditions: 5 #applicable only if prediction_type == 'iterative'
ics_type: "default"
save_raw_forecasts: !!bool True
save_channel: !!bool False
masked_acc: !!bool False
maskpath: None
perturb: !!bool False
add_grid: !!bool False
N_grid_channels: 0
gridtype: 'sinusoidal' #options 'sinusoidal' or 'linear'
roll: !!bool False
max_epochs: 50
batch_size: 64
#afno hyperparams
num_blocks: 8
nettype: 'afno'
patch_size: 8
width: 56
modes: 32
#options default, residual
target: 'default'
in_channels: [0,1]
out_channels: [0,1] #must be same as in_channels if prediction_type == 'iterative'
normalization: 'zscore' #options zscore (minmax not supported)
train_data_path: '/pscratch/sd/j/jpathak/wind/train'
valid_data_path: '/pscratch/sd/j/jpathak/wind/test'
inf_data_path: '/pscratch/sd/j/jpathak/wind/out_of_sample' # test set path for inference
exp_dir: '/pscratch/sd/j/jpathak/ERA5_expts_gtc/wind'
time_means_path: '/pscratch/sd/j/jpathak/wind/time_means.npy'
global_means_path: '/pscratch/sd/j/jpathak/wind/global_means.npy'
global_stds_path: '/pscratch/sd/j/jpathak/wind/global_stds.npy'
orography: !!bool False
orography_path: None
log_to_screen: !!bool True
log_to_wandb: !!bool True
save_checkpoint: !!bool True
enable_nhwc: !!bool False
optimizer_type: 'FusedAdam'
crop_size_x: None
crop_size_y: None
two_step_training: !!bool False
plot_animations: !!bool False
add_noise: !!bool False
noise_std: 0
afno_backbone_ljkj: &LJKJ
<<: *FULL_FIELD
log_to_wandb: !!bool False
lr: 5E-4
batch_size: 8
patch_size: 4
depth : 4 # default 12
max_epochs: 1500
scheduler: 'CosineAnnealingLR'
in_channels: [0, 1 ,2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
out_channels: [0, 1 ,2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
prediction_length: 100
orography: !!bool False
orography_path: None
exp_dir: './results/tec_256'
train_data_path: './train'
valid_data_path: './test'
inf_data_path: './out_of_sample'
time_means_path: './time_means.npy'
global_means_path: './global_means.npy'
global_stds_path: './global_stds.npy'
afno_backbone_ustc:
<<: *LJKJ
batch_size: 64