hyperparameter search

xsk07 · Sep 3, 2024 · db3d529 · db3d529
1 parent 78c60e2
commit db3d529
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Showing 3 changed files with 185 additions and 67 deletions.
diff --git a/hpsearch/config/DBLP_v1_GCN_hp_tuning.json b/hpsearch/config/DBLP_v1_GCN_hp_tuning.json
@@ -11,13 +11,13 @@
     "oracle": {
         "class": "hpsearch.oracle.torch.OracleTorch",
         "parameters": {
-            "epochs": 500,
+            "epochs": 200,
             "batch_size": 64,
             "optimizer": {
                 "class": "torch.optim.AdamW",
                 "parameters": {
-                    "lr":0.005597827355896938,
-                    "weight_decay":0.022451620056299467
+                    "lr":0.006,
+                    "weight_decay":0.004
                 }
             },
             "loss_fn": {
@@ -29,10 +29,10 @@
             "model": {
                 "class": "src.oracle.nn.gcn.DownstreamGCN",
                 "parameters": {
-                    "num_conv_layers":5,
+                    "num_conv_layers":6,
                     "num_dense_layers":9,
-                    "conv_booster":2,
-                    "linear_decay":0.3211868888719398
+                    "conv_booster":5,
+                    "linear_decay":0.4
                 }
             }
         }

diff --git a/hpsearch/hp_tuner.py b/hpsearch/hp_tuner.py
@@ -24,7 +24,7 @@ def optimize(self):
 
         #Create a study object and optimize the objective function
         study = optuna.create_study(direction='maximize')
-        
+
         try:
             study.optimize(self.objective, n_trials=self.n_trials, show_progress_bar=True)
         except KeyboardInterrupt:
@@ -38,11 +38,11 @@ def objective(self, trial):
 
         #Suggest values of the hyperparameters using a trial object.
         #batch_size = trial.trial.suggest_categorical('batch_size', [32, 64])
-        learning_rate = trial.suggest_float('lr', 1e-5, 1e-1)
-        weight_decay = trial.suggest_float('weight_decay', 1e-5, 1e-1)
-        num_conv_layers =  trial.suggest_int('num_conv_layers', 1, 10)
-        num_dense_layers = trial.suggest_int('num_dense_layers', 1, 10)
-        conv_booster = trial.suggest_int('conv_booster', 1, 10)
+        learning_rate = trial.suggest_float('lr', 1e-03, 1e-01)
+        weight_decay = trial.suggest_float('weight_decay', 1e-05, 1e-01)
+        num_conv_layers =  trial.suggest_int('num_conv_layers', 1, 5)
+        num_dense_layers = trial.suggest_int('num_dense_layers', 1, 5)
+        conv_booster = trial.suggest_int('conv_booster', 1, 5)
         linear_decay = trial.suggest_float('linear_decay', 0, 2)
 
         self.oracle_config['parameters']['optimizer']['parameters']['lr'] = learning_rate

diff --git a/notebooks/dataset_generator.ipynb b/notebooks/dataset_generator.ipynb