⚡ do not build dataloaders for multiprocessing

src/move/tasks/identify_associations.py

@@ -829,11 +829,17 @@ def identify_associations(config: MOVEConfig) -> None:
         logger.info(f"Perturbation type: {task_config.target_value}")
         output_subpath = Path(output_path) / "perturbation_visualization"
         output_subpath.mkdir(exist_ok=True, parents=True)
-
-        dataloaders = prepare_for_continuous_perturbation(
-            config, output_subpath, baseline_dataloader
-        )
+        if not task_config.multiprocess:
+            dataloaders = prepare_for_continuous_perturbation(
+                config, output_subpath, baseline_dataloader
+            )
         feature_mask = nan_mask
+        con_dataset_names = config.data.continuous_names
+        target_idx = con_dataset_names.index(
+            task_config.target_dataset
+        )  # dataset index
+        logger.debug(f"Cont. shapes: {baseline_dataset.con_shapes} [take {target_idx}]")
+        num_perturbed = baseline_dataset.con_shapes[target_idx]
 
     # Identify associations between categorical and continuous features:
     else:
@@ -848,13 +854,21 @@ def identify_associations(config: MOVEConfig) -> None:
         target_value = one_hot_encode_single(target_mapping, task_config.target_value)
         feature_mask = np.all(target_dataset == target_value, axis=2)  # 2D: N x P
         feature_mask |= np.sum(target_dataset, axis=2) == 0
-        dataloaders = prepare_for_categorical_perturbation(
-            config, interim_path, baseline_dataloader, cat_list
+        if not task_config.multiprocess:
+            dataloaders = prepare_for_categorical_perturbation(
+                config, interim_path, baseline_dataloader, cat_list
+            )
+        num_perturbed = target_dataset.shape[-1]
+        logger.info(
+            f"Cat. shapes: {baseline_dataset.cat_shapes}"
+            f" [take {target_dataset_idx}]"
         )
+        target_shape = baseline_dataset.cat_shapes[target_dataset_idx]
+        num_perturbed = target_shape[0]
 
     # APPROACH EVALUATION ##########################
-    num_perturbed = len(dataloaders) - 1  # P
-    logger.debug(f"# perturbed features: {num_perturbed}")
+    # num_perturbed = len(dataloaders) - 1  # P
+    # logger.debug(f"# perturbed features: {num_perturbed}")
 
     if task_type == "bayes":
         task_config = cast(IdentifyAssociationsBayesConfig, task_config)
@@ -895,7 +909,7 @@ def identify_associations(config: MOVEConfig) -> None:
     elif task_type == "ttest":
         task_config = cast(IdentifyAssociationsTTestConfig, task_config)
         if task_config.multiprocess:
-            logger.warning("Multiprocessing is not supported for ttest approach.")
+            raise NotImplementedError("Multiprocessing is not supported for T-test.")
         sig_ids, *extra_cols = _ttest_approach(
             task_config,
             train_dataloader,
@@ -915,7 +929,7 @@ def identify_associations(config: MOVEConfig) -> None:
     elif task_type == "ks":
         task_config = cast(IdentifyAssociationsKSConfig, task_config)
         if task_config.multiprocess:
-            logger.warning("Multiprocessing is not supported for KS approach.")
+            raise NotImplementedError("Multiprocessing is not supported for KS.")
         sig_ids, *extra_cols = _ks_approach(
             config,
             task_config,