Update model configuration

config.json

@@ -1,128 +1,18 @@
 {
-  "architectures": [
-    "FNO2d"
-  ],
-  "framework": "pytorch",
-  "model_name": "FNO",
-  "model_type": "fno",
-  "source_config": "config/config.yaml",
-  "paper": {
-    "title": "Fourier Neural Operator for Parametric Partial Differential Equations",
-    "arxiv": "2010.08895",
-    "experiment": "FNO-2D Navier-Stokes, nu=1e-5, T=20",
-    "viscosity": 1e-05,
-    "reference_relative_l2": 0.1556,
-    "reference_parameter_count": 414517,
-    "reference_epoch_seconds_v100": 127.8
-  },
-  "data": {
-    "root": "/public/share/sugonhpcapp01/onestore/onedatasets/FNO_data",
-    "file": "NavierStokes_V1e-5_N1200_T20.mat",
-    "key": "u",
-    "layout": "N,H,W,T",
-    "dtype": "float32",
-    "expected_shape": [
-      1200,
-      64,
-      64,
-      20
-    ],
-    "resolution": [
-      64,
-      64
-    ],
-    "ntrain": 1000,
-    "ntest": 200,
-    "train_start": 0,
-    "test_start": 1000,
-    "history": 10,
-    "horizon": 10,
-    "recording_interval": 1.0,
-    "future_times": [
-      11,
-      12,
-      13,
-      14,
-      15,
-      16,
-      17,
-      18,
-      19,
-      20
-    ],
-    "normalization": "none"
-  },
-  "model": {
-    "name": "FNO2d",
-    "input_channels": 10,
-    "output_channels": 1,
-    "use_grid": true,
-    "grid_channels": 2,
-    "grid_include_endpoint": false,
-    "width": 32,
-    "modes1": 12,
-    "modes2": 12,
-    "num_layers": 4,
-    "projection_width": 128,
-    "activation": "relu",
-    "normalization": "batch_norm",
-    "block_order": "relu(batch_norm(spectral_plus_pointwise))",
-    "fft_norm": "backward",
-    "spectral_init": "scaled_uniform_complex"
-  },
-  "training": {
-    "epochs": 500,
-    "batch_size": 20,
-    "optimizer": "adam",
-    "learning_rate": 0.001,
-    "weight_decay": 0.0,
-    "scheduler": "step_lr",
-    "scheduler_step_size": 100,
-    "scheduler_gamma": 0.5,
-    "seed": 0,
-    "dtype": "float32",
-    "amp": false,
-    "gradient_clipping": null,
-    "ema": false,
-    "distributed": "single",
-    "num_workers": 0,
-    "pin_memory": true,
-    "deterministic": true,
-    "relative_l2_epsilon": 1e-12,
-    "train_rollout_steps": 10,
-    "evaluation_rollout_steps": 10,
-    "checkpoint_monitor": "train_full_relative_l2",
-    "checkpoint_mode": "min",
-    "evaluate_test_every_epoch": true
-  },
-  "inference": {
-    "batch_size": 20,
-    "seed": 0,
-    "dtype": "float32",
-    "rollout_steps": 10
-  },
-  "paths": {
-    "checkpoint": "weight/best_model.pth",
-    "results_dir": "results",
-    "train_history": "results/train_history.json",
-    "predictions": "results/predictions.npz",
-    "metrics": "results/metrics.json",
-    "per_sample_metrics": "results/per_sample_metrics.csv",
-    "training_curves": "results/training_curves.png",
-    "rollout_figure": "results/sample_000_rollout.png",
-    "run_metadata": "results/run_metadata.json",
-    "summary": "results/summary.md"
-  },
-  "assumptions": [
-    "The paper does not specify a validation split; the best checkpoint is selected using train full-trajectory relative L2, never test error.",
-    "The paper does not specify batch size or seed; batch_size=20 and seed=0 are explicit engineering assumptions.",
-    "The paper does not define the exact relative-L2 reduction; ratios are computed per sample and then averaged with epsilon=1e-12.",
-    "The paper does not specify the projection hidden width; projection_width=128 is configurable.",
-    "Coordinate-grid input is configurable and enabled; the periodic grid excludes the duplicated endpoint.",
-    "The block ordering is ReLU(BatchNorm(spectral + pointwise)); the paper states ReLU and batch normalization but not their exact order.",
-    "Adam uses weight_decay=0.0 because the paper does not state an additional weight-decay regularizer."
-  ],
-  "conflicts": [
-    "The paper states d_v=32 but reports 414,517 parameters without enough connection details to reproduce both uniquely. Width 32 takes precedence and the actual parameter count must be reported."
-  ]
+  "name": "FNO2d",
+  "input_channels": 10,
+  "output_channels": 1,
+  "use_grid": true,
+  "grid_channels": 2,
+  "grid_include_endpoint": false,
+  "width": 32,
+  "modes1": 12,
+  "modes2": 12,
+  "num_layers": 4,
+  "projection_width": 128,
+  "activation": "relu",
+  "normalization": "batch_norm",
+  "block_order": "relu(batch_norm(spectral_plus_pointwise))",
+  "fft_norm": "backward",
+  "spectral_init": "scaled_uniform_complex"
 }