Add model configuration

config.json

@@ -0,0 +1,68 @@
+{
+  "architectures": [
+    "GPPLUS"
+  ],
+  "framework": "pytorch",
+  "model_name": "GP_for_TO",
+  "model_type": "gp_for_to",
+  "source_config": "conf/config.yaml",
+  "root": {
+    "problem": "doublepipe",
+    "seed": 11,
+    "output_names": [
+      "u",
+      "v",
+      "p",
+      "ro"
+    ],
+    "runtime": {
+      "onescience_src": null
+    },
+    "data": {
+      "n_train_per_bc": 25,
+      "n_col_domain": 10000
+    },
+    "model": {
+      "mean_function": "neural_network",
+      "nn_layers_base": [
+        64,
+        64,
+        64,
+        64,
+        64
+      ],
+      "dtype": "float32"
+    },
+    "training": {
+      "device": "auto",
+      "gpu": 0,
+      "num_iter": 50000,
+      "lr_default": 0.001,
+      "diff_method": "Numerical",
+      "checkpoint_path": "./weight/gp_for_to.pt",
+      "output_dir": "./result/training",
+      "plot_outputs": true,
+      "checkpoints": [
+        1000,
+        10000,
+        20000,
+        30000,
+        40000,
+        50000
+      ]
+    },
+    "inference": {
+      "device": "auto",
+      "gpu": 0,
+      "checkpoint_path": "./weight/gp_for_to.pt",
+      "output_dir": "./result/inference",
+      "n_col_domain": 10000
+    },
+    "fake_data": {
+      "problem": "doublepipe",
+      "n_train_per_bc": 25,
+      "n_col_domain": 10000,
+      "output_dir": "./data/fake"
+    }
+  }
+}