Update app.py

app.py

@@ -558,7 +558,7 @@ def modelTFT(csv_file, prax):
             train_dataloader,
             val_dataloader,
             model_path="optuna_test",
-            n_trials=7,
+            n_trials=5,
             max_epochs=MAX_EPOCHS,
             gradient_clip_val_range=(0.01, 0.5),
             hidden_size_range=(8, 64),
@@ -568,7 +568,7 @@ def modelTFT(csv_file, prax):
             dropout_range=(0.1, 0.3),
             trainer_kwargs=dict(limit_train_batches=30),
             reduce_on_plateau_patience=4,
-            pruner=optuna.pruners.MedianPruner(n_min_trials=5, n_startup_trials=5),
+            pruner=optuna.pruners.MedianPruner(n_min_trials=3, n_startup_trials=3),
             use_learning_rate_finder=False,  # use Optuna to find ideal learning rate or use in-built learning rate finder
         )
     #torch.cuda.empty_cache()
@@ -582,6 +582,7 @@ def modelTFT(csv_file, prax):
         #fast_dev_run=True,  # comment in to check that networkor dataset has no serious bugs
         callbacks=[lr_logger, early_stop_callback],
         logger=logger,
+        precision="bf16-mixed", 
     )
     
     tft = TemporalFusionTransformer.from_dataset(
@@ -795,7 +796,7 @@ def modelTFT_OpenGap(csv_file, prax):
             train_dataloader,
             val_dataloader,
             model_path="optuna_test",
-            n_trials=7,
+            n_trials=5,
             max_epochs=MAX_EPOCHS,
             gradient_clip_val_range=(0.01, 0.5),
             hidden_size_range=(8, 64),
@@ -805,7 +806,7 @@ def modelTFT_OpenGap(csv_file, prax):
             dropout_range=(0.1, 0.3),
             trainer_kwargs=dict(limit_train_batches=30),
             reduce_on_plateau_patience=4,
-            pruner=optuna.pruners.MedianPruner(n_min_trials=5, n_warmup_steps=5),
+            pruner=optuna.pruners.MedianPruner(n_min_trials=3, n_warmup_steps=3),
             use_learning_rate_finder=False,  # use Optuna to find ideal learning rate or use in-built learning rate finder
         )
     #torch.cuda.empty_cache()
@@ -819,6 +820,7 @@ def modelTFT_OpenGap(csv_file, prax):
         #fast_dev_run=True,  # comment in to check that networkor dataset has no serious bugs
         callbacks=[lr_logger, early_stop_callback],
         logger=logger,
+        precision="bf16-mixed",
     )
     
     tft = TemporalFusionTransformer.from_dataset(