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config.yaml
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config.yaml
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# Global settings for the benchmark
training_id: "delete_me5"
surrogates: ["MultiONet"]
batch_size: [256]
epochs: [10]
dataset:
name: "branca24"
log10_transform: False
normalise: "disable" # "minmax" # "standardise", "minmax", "disable"
use_optimal_params: True
tolerance: 1e-30
devices: ["cpu"]
seed: 42
verbose: False
# Models to train
interpolation:
enabled: True
intervals: [2, 3, 4, 5, 6, 7, 8, 10]
extrapolation:
enabled: True
cutoffs: [50, 60, 70, 80, 90]
sparse:
enabled: True
factors: [2, 4, 8, 16, 32]
batch_scaling:
enabled: False
sizes: [16, 1024, 8192]
uncertainty:
enabled: True
ensemble_size: 5 # Number of models for deep ensemble
# Evaluations during benchmark
losses: True
gradients: True
timing: True
compute: True
compare: True # Whether to compare the surrogates