feat(Config): added flag to save models

config/presets.py

@@ -32,4 +32,5 @@ def get_default_config() -> RawConfig:
         event_filter="cusum_fixed",
         labeling="two_class",
         forecasting_horizon=50,
+        save_models=False,
     )

config/types.py

@@ -28,6 +28,7 @@ class RawConfig(BaseModel):
     event_filter: Literal["none", "cusum_vol", "cusum_fixed"]
     labeling: Literal["two_class", "three_class_balanced", "three_class_imbalanced"]
     forecasting_horizon: int
+    save_models: bool
 
     directional_models: list[str]
     meta_models: list[str]
@@ -50,6 +51,7 @@ class Config:
     labeling: EventLabeller
     forecasting_horizon: int
     no_of_classes: Literal["two", "three-balanced", "three-imbalanced"]
+    save_models: bool
 
     mode: Literal["training", "inference"]
 

run_pipeline.py

@@ -35,7 +35,8 @@ def run_pipeline(
         wandb,
         sweep,
     )
-    save_models(pipeline_outcome, config)
+    if config.save_models:
+        save_models(pipeline_outcome, config)
     return pipeline_outcome, config