naprawa błędów

src/penguins/pipelines/modeling/nodes.py

@@ -13,12 +13,13 @@ def split_data(data: pd.DataFrame) -> Tuple:
     return train, test
 
 
-def train_model(train: pd.DataFrame) -> TabularPredictor:
+def train_model(train: pd.DataFrame, test: pd.DataFrame) -> TabularPredictor:
     """Train a model on the given data."""
     mlflow.set_experiment("penguins")
     classificator = TabularPredictor(label="species", log_to_file=False, problem_type="multiclass",
                                      eval_metric="accuracy")
     classificator.fit(train, time_limit=120)
+    classificator.evaluate(test)
     for key, value in classificator.fit_summary()["model_performance"].items():
         mlflow.log_metric(f"{key}_accuracy", value)
     return classificator

src/penguins/pipelines/modeling/pipeline.py

@@ -13,7 +13,7 @@ def create_pipeline() -> Pipeline:
     return pipeline([
         node(
             func=split_data,
-            inputs=["model_input_table", "params:model_options"],
+            inputs=["model_input_table"],
             outputs=["train", "test"],
             name="split_data_node",
         ),

src/penguins/settings.py

@@ -24,6 +24,7 @@
 # Class that manages how configuration is loaded.
 from kedro.config import OmegaConfigLoader  # noqa: import-outside-toplevel
 
+# CONFIG_LOADER_CLASS = OmegaConfigLoader
 ConfigLoaderClass = OmegaConfigLoader
 # Keyword arguments to pass to the `CONFIG_LOADER_CLASS` constructor.
 # CONFIG_LOADER_ARGS = {