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CNO
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# Paper-faithful configuration for arXiv:2302.01178, Table 12 and Appendix C.
experiment:
  name: cno_navier_stokes_2d
  paper: https://arxiv.org/pdf/2302.01178
  seed: 0                    # Paper-unspecified, explicit reproducibility choice.
  deterministic: true

paths:
  data_dir: /public/share/sugonhpcapp01/onestore/onedatasets/RPB_CNO/data
  train_file: NavierStokes_64x64_IN.h5
  id_test_file: NavierStokes_64x64_IN.h5
  ood_test_file: NavierStokes_128x128_OUT.h5
  checkpoint: weight/best_model.pth
  results_dir: results

data:
  input_key: input
  output_key: output
  train:
    start: 0
    stop: 750
  validation:
    start: 768
    stop: 896
  test_id:
    start: 896
    stop: 1024
  test_ood:
    start: 0
    stop: 128

# The paper requires [0,1] training normalization and reuse at test time but
# does not publish its constants. These extrema were measured once from the
# supplied 64x64 ID benchmark and are fixed for every split, including OOD.
normalization:
  source: supplied_64x64_id_benchmark
  input_min: -1.4294605255126953
  input_max: 1.4294605255126953
  output_min: -2.0383081436157227
  output_max: 2.0602376461029053
  epsilon: 1.0e-12

model:
  in_channels: 1
  out_channels: 1
  base_width: 32             # d_e in Table 12.
  levels: 3                  # M in Table 12.
  bottleneck_residual_blocks: 8
  intermediate_residual_blocks: 1
  kernel_size: 3
  latent_channels: 64        # Paper-unspecified lift/project internal width.
  activation_upsampling_factor: 2  # N_sigma.
  filter_taps: 12            # N_tap.
  filter_half_width: 0.8     # c_h.
  cutoff_denominator: 2.0001
  leaky_relu_slope: 0.2      # Paper-unspecified, official supplemental fact.

training:
  epochs: 1000
  batch_size: 32
  num_workers: 4
  optimizer: Adam
  learning_rate: 0.001
  weight_decay: 1.0e-10
  scheduler: StepLR
  scheduler_step_size: 1
  scheduler_gamma: 0.98
  early_stopping_patience: 50
  log_interval: 5
  device: auto

inference:
  batch_size: 16
  num_workers: 2
  device: auto
  metric_epsilon: 1.0e-12

paper_reference:
  metric: relative_median_l1_percent
  id: 2.76
  ood: 7.04