config.yaml

# Global settings for the benchmark
training_id: "all_models_3"
surrogates: ["LatentPoly", "LatentNeuralODE"]
batch_size: [256, 256]
epochs: [15000, 10000]
dataset: 
  name: "osu2008"
  log10_transform: True
  normalise: "minmax" # "standardise", "minmax", "disable"
  use_optimal_params: True
devices: ["cuda:5", "cuda:6", "cuda:7", "cuda:8"]
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