configs/system_params/base.yaml

# Base system parameters
# Defines common structure and defaults for BOTH data AND model
# Each system inherits this and overrides specific values

# ============ Data Parameters ============
name: "placeholder_inverse"
data_root: "placeholder_path"
train_data_root: ${system_params.data_root}/train
val_data_root: ${system_params.data_root}/validation
ood_data_root: ${system_params.data_root}/out_of_distribution
ood_data_root_extreme: ${system_params.data_root}/out_of_distribution_extreme
test_data_root: ${system_params.data_root}/test
pde_name: "placeholder_pde"
num_channels: 1
cutoff_first_n_frames: 0

# ============ Model - System-Specific Parameters ============
params_to_predict: []
normalize: False
logspace: False
mlp_type: "mlp"  # Default to standard MLP (2ddf overrides to "conv")
downsampler_input_dim: 2  # 1 for 1D systems, 2 for 2D systems

# ============ FNO Architecture ============
fno_hidden_channels: 64
fno_encoder_layers: 4
fno_downsampler_layers: 4
fno_dropout: 0
fno_mlp_layers: 1
fno_n_modes: 16

fno_hidden_channels_50k: 16
fno_encoder_layers_50k: 6

fno_hidden_channels_50mil: 200
fno_encoder_layers_50mil: 4

fno_downsampler:
  _target_: pdeinvbench.models.downsampler.ConvDownsampler
  input_dimension: ${system_params.downsampler_input_dim}
  n_layers: ${model.downsampler_layers}
  in_channels: ${model.hidden_channels}
  out_channels: ${model.hidden_channels}
  kernel_size: 3
  stride: 1
  padding: 2
  dropout: ${model.dropout}

# ============ ResNet Architecture ============
resnet_hidden_channels: 128
resnet_encoder_layers: 13
resnet_downsampler_layers: 4
resnet_dropout: 0
resnet_mlp_layers: 1

resnet_downsampler:
  _target_: pdeinvbench.models.downsampler.ConvDownsampler
  input_dimension: ${system_params.downsampler_input_dim}
  n_layers: ${model.downsampler_layers}
  in_channels: ${model.hidden_channels}
  out_channels: ${model.hidden_channels}
  kernel_size: 3
  stride: 1
  padding: 2
  dropout: ${model.dropout}

# ============ ScOT Architecture ============
scot_hidden_channels: 32
scot_encoder_layers: 4
scot_downsampler_layers: 4
scot_dropout: 0
scot_mlp_layers: 1
scot_mlp_hidden_size: 32
scot_condition_on_time: False
scot_embed_dim: 36
scot_hidden_size: 32
scot_patch_size: 4
scot_num_heads: [3, 6, 12, 24]
scot_skip_connections: [2, 2, 2, 2]
scot_depths: [1, 1, 1, 1]

scot_downsampler:
  _target_: pdeinvbench.models.downsampler.ConvDownsampler
  input_dimension: ${system_params.downsampler_input_dim}
  n_layers: ${model.downsampler_layers}
  in_channels: ${model.hidden_channels}
  out_channels: ${model.hidden_channels}
  kernel_size: 3
  stride: 1
  padding: 2
  dropout: ${model.dropout}