Revert "Auto3DSeg skip trained algos"

monai/apps/auto3dseg/auto_runner.py

@@ -281,7 +281,7 @@ def __init__(
         # determine if we need to analyze, algo_gen or train from cache, unless manually provided
         self.analyze = not self.cache["analyze"] if analyze is None else analyze
         self.algo_gen = not self.cache["algo_gen"] if algo_gen is None else algo_gen
-        self.train = train
+        self.train = not self.cache["train"] if train is None else train
         self.ensemble = ensemble  # last step, no need to check
 
         self.set_training_params()
@@ -758,8 +758,7 @@ def run(self):
             logger.info("Skipping algorithm generation...")
 
         # step 3: algo training
-        auto_train_choice = self.train is None
-        if self.train or (auto_train_choice and not self.cache["train"]):
+        if self.train:
             history = import_bundle_algo_history(self.work_dir, only_trained=False)
 
             if len(history) == 0:
@@ -768,15 +767,10 @@ def run(self):
                     "Possibly the required algorithms generation step was not completed."
                 )
 
-            if auto_train_choice:
-                history = [h for h in history if not h["is_trained"]]  # skip trained
-
-            if len(history) > 0:
-                if not self.hpo:
-                    self._train_algo_in_sequence(history)
-                else:
-                    self._train_algo_in_nni(history)
-
+            if not self.hpo:
+                self._train_algo_in_sequence(history)
+            else:
+                self._train_algo_in_nni(history)
             self.export_cache(train=True)
         else:
             logger.info("Skipping algorithm training...")
@@ -804,4 +798,4 @@ def run(self):
                     self.save_image(pred)
                 logger.info(f"Auto3Dseg ensemble prediction outputs are saved in {self.output_dir}.")
 
-        logger.info("Auto3Dseg pipeline is completed successfully.")
+        logger.info("Auto3Dseg pipeline is complete successfully.")

monai/apps/auto3dseg/utils.py

@@ -47,14 +47,11 @@ def import_bundle_algo_history(
         if isinstance(algo, BundleAlgo):  # algo's template path needs override
             algo.template_path = algo_meta_data["template_path"]
 
-        best_metrics = "best_metrics"
-        is_trained = best_metrics in algo_meta_data
-
         if only_trained:
-            if is_trained:
-                history.append({name: algo, "is_trained": is_trained, best_metrics: algo_meta_data[best_metrics]})
+            if "best_metrics" in algo_meta_data:
+                history.append({name: algo})
         else:
-            history.append({name: algo, "is_trained": is_trained, best_metrics: algo_meta_data.get(best_metrics, None)})
+            history.append({name: algo})
 
     return history