🐞 Fix issues when validation and test split modes set to none

src/anomalib/engine/engine.py

@@ -22,6 +22,7 @@
 from anomalib.callbacks.thresholding import _ThresholdCallback
 from anomalib.callbacks.visualizer import _VisualizationCallback
 from anomalib.data import AnomalibDataModule, AnomalibDataset, PredictDataset
+from anomalib.data.utils import TestSplitMode
 from anomalib.deploy.export import ExportType, export_to_onnx, export_to_openvino, export_to_torch
 from anomalib.models import AnomalyModule
 from anomalib.utils.normalization import NormalizationMethod
@@ -633,7 +634,7 @@ def train(
         test_dataloaders: EVAL_DATALOADERS | None = None,
         datamodule: AnomalibDataModule | None = None,
         ckpt_path: str | None = None,
-    ) -> _EVALUATE_OUTPUT:
+    ) -> _EVALUATE_OUTPUT | None:
         """Fits the model and then calls test on it.
 
         Args:
@@ -650,6 +651,9 @@ def train(
             ckpt_path (str | None, optional): Checkpoint path. If provided, the model will be loaded from this path.
                 Defaults to None.
 
+        Returns:
+            _EVALUATE_OUTPUT | None: A List of dictionaries containing the test results. 1 dict per dataloader.
+
         CLI Usage:
             1. you can pick a model, and you can run through the MVTec dataset.
                 ```python
@@ -671,7 +675,12 @@ def train(
             self.trainer.validate(model, val_dataloaders, None, verbose=False, datamodule=datamodule)
         else:
             self.trainer.fit(model, train_dataloaders, val_dataloaders, datamodule, ckpt_path)
-        self.trainer.test(model, test_dataloaders, ckpt_path=ckpt_path, datamodule=datamodule)
+
+        if datamodule is not None and datamodule.test_split_mode == TestSplitMode.NONE:
+            logger.info(f"The test_split_mode is set to '{TestSplitMode.NONE}'. Skipping test stage.")
+            logger.warning(f"Found {len(datamodule.test_data)} images in the test set.")
+            return None
+        return self.trainer.test(model, test_dataloaders, ckpt_path=ckpt_path, datamodule=datamodule)
 
     def export(
         self,

src/anomalib/utils/config.py

@@ -19,6 +19,8 @@
 from jsonargparse import Path as JSONArgparsePath
 from omegaconf import DictConfig, ListConfig, OmegaConf
 
+from anomalib.data.utils import ValSplitMode
+
 logger = logging.getLogger(__name__)
 
 
@@ -122,6 +124,7 @@ def update_config(config: DictConfig | ListConfig | Namespace) -> DictConfig | L
     config.results_dir.path = str(project_path)
 
     config = _update_nncf_config(config)
+    config = _update_val_config(config)
 
     # write the original config for eventual debug (modified config at the end of the function)
     (project_path / "config_original.yaml").write_text(to_yaml(config_original))
@@ -214,6 +217,21 @@ def _update_nncf_config(config: DictConfig | ListConfig) -> DictConfig | ListCon
     return config
 
 
+def _update_val_config(config: DictConfig | ListConfig) -> DictConfig | ListConfig:
+    """Skip validation if `val_split_mode` is set to 'none'.
+
+    Args:
+        config (DictConfig | ListConfig): Configurable parameters of the current run.
+
+    Returns:
+        DictConfig | ListConfig: Updated configurable parameters in DictConfig object.
+    """
+    if config.data.init_args.val_split_mode == ValSplitMode.NONE and config.trainer.limit_val_batches != 0.0:
+        logger.warning("Running without validation set. Setting trainer.limit_val_batches to 0.")
+        config.trainer.limit_val_batches = 0.0
+    return config
+
+
 def _show_warnings(config: DictConfig | ListConfig | Namespace) -> None:
     """Show warnings if any based on the configuration settings.