Fix docs, config and folder support for tiled ensemble

docs/source/markdown/guides/how_to/pipelines/tiled_ensemble.md

@@ -50,7 +50,7 @@ General settings at the top of the config file are used to set up the random `se
 
 ```{code-block} yaml
 seed: 42
-accelerator: "gpu"
+accelerator: "cuda"
 default_root_dir: "results"
 ```
 

src/anomalib/pipelines/tiled_ensemble/components/utils/ensemble_engine.py

@@ -50,8 +50,12 @@ def setup_ensemble_workspace(args: dict, versioned_dir: bool = True) -> Path:
             Path: path to new workspace root dir
         """
         model_name = args["TrainModels"]["model"]["class_path"].split(".")[-1]
-        dataset_name = args["data"]["class_path"].split(".")[-1]
-        category = args["data"]["init_args"]["category"]
+        # get dataset name if present in init_args
+        dataset_name = args["data"]["init_args"].get("name", None)
+        if dataset_name is None:
+            # if not specified, take class name
+            dataset_name = args["data"]["class_path"].split(".")[-1]
+        category = args["data"]["init_args"].get("category", "")
         root_dir = Path(args["default_root_dir"]) / model_name / dataset_name / category
         return create_versioned_dir(root_dir) if versioned_dir else root_dir / "latest"
 

src/anomalib/pipelines/tiled_ensemble/test_pipeline.py

@@ -8,6 +8,7 @@
 
 import torch
 
+from anomalib import TaskType
 from anomalib.data.utils import TestSplitMode
 from anomalib.pipelines.components.base import Pipeline, Runner
 from anomalib.pipelines.components.runners import ParallelRunner, SerialRunner
@@ -48,9 +49,12 @@
         """
         runners: list[Runner] = []
 
-        if args["data"]["init_args"]["test_split_mode"] == TestSplitMode.NONE:
+        test_split_mode = args["data"]["init_args"].get("test_split_mode", None)
+        if test_split_mode == TestSplitMode.NONE:
             logger.info("Test split mode set to `none`, skipping test phase.")
             return runners
+        if test_split_mode is None:
+            logger.warning("Test split mode not set in data config, dataset specific default will be used.")
 
         seed = args["seed"]
         accelerator = args["accelerator"]
@@ -59,7 +63,12 @@
         normalization_stage = NormalizationStage(args["normalization_stage"])
         threshold_stage = ThresholdStage(args["thresholding"]["stage"])
         model_args = args["TrainModels"]["model"]
-        task = args["data"]["init_args"]["task"]
+
+        task = args["data"]["init_args"].get("task", None)
+        if task is None:
+            logger.info("Task not provided, defaulting to segmentation. Set 'task' in config data section to change.")
+            task = TaskType.SEGMENTATION
+
         metrics = args["TrainModels"]["metrics"]
 
         predict_job_generator = PredictJobGenerator(

src/anomalib/pipelines/tiled_ensemble/train_pipeline.py

@@ -92,9 +92,12 @@
                 ),
             )
 
-        if data_args["init_args"]["val_split_mode"] == ValSplitMode.NONE:
+        val_split_mode = data_args["init_args"].get("val_split_mode", None)
+        if val_split_mode == ValSplitMode.NONE:
             logger.warning("No validation set provided, skipping statistics calculation.")
             return runners
+        if val_split_mode is None:
+            logger.warning("Validation split mode not set in data config, dataset specific default will be used.")
 
         # 2. predict using validation data
         if accelerator == "cuda":

tools/tiled_ensemble/ens_config.yaml

@@ -1,5 +1,5 @@
 seed: 42
-accelerator: "gpu"
+accelerator: "cuda"
 default_root_dir: "results"
 
 tiling: