ignore ema val when full_val is false

Author: OutisLi

deepmd/pt/train/training.py

@@ -1027,7 +1027,9 @@ def _create_ema_full_validator(
         validation_data: DpLoaderSet | None,
     ) -> FullValidator | None:
         """Create the runtime EMA full validator when it is active."""
-        if not self._is_validation_requested(validating_params, "ema_full_validation"):
+        if not self._is_validation_requested(
+            validating_params, "full_validation"
+        ) or not validating_params.get("ema_full_validation", False):
             return None
         self._raise_if_full_validation_unsupported(validation_data)
         if self.model_ema is None:

deepmd/utils/argcheck.py

@@ -4257,10 +4257,11 @@ def validating_args() -> Argument:
     )
     doc_ema_full_validation = (
         "Whether to additionally run the same full validation flow on the "
-        "EMA-smoothed model. This reuses the existing full validation schedule, "
-        "metric, start step, and best-checkpoint settings, writes results to an "
-        "EMA-specific validation log such as `val_ema.log`, and saves EMA best "
-        "checkpoints with a `best_ema.ckpt` prefix. Requires "
+        "EMA-smoothed model when `validating.full_validation=true`. This reuses "
+        "the existing full validation schedule, metric, start step, and "
+        "best-checkpoint settings, writes results to an EMA-specific validation "
+        "log such as `val_ema.log`, and saves EMA best checkpoints with a "
+        "`best_ema.ckpt` prefix. Requires "
         "`training.enable_ema=true`."
     )
     doc_max_best_ckpt = (
@@ -4374,7 +4375,7 @@ def validate_full_validation_config(
     training_params = data.get("training", {}) or {}
     full_validation_enabled = bool(validating.get("full_validation", False))
     ema_full_validation_enabled = bool(validating.get("ema_full_validation", False))
-    if not full_validation_enabled and not ema_full_validation_enabled:
+    if not full_validation_enabled:
         return
     if float(validating.get("full_val_start", 0.0)) == 1.0:
         return

source/tests/pt/test_training.py

@@ -1063,17 +1063,22 @@ def test_restart_restores_ema_state(self) -> None:
     @patch("deepmd.pt.train.validation.FullValidator.evaluate_all_systems")
     def test_ema_full_validation_writes_separate_outputs(self, mocked_eval) -> None:
         mocked_eval.side_effect = [
+            {"mae_e_per_atom": 10.0},
             {"mae_e_per_atom": 1.0},
+            {"mae_e_per_atom": 10.0},
             {"mae_e_per_atom": 0.5},
+            {"mae_e_per_atom": 10.0},
             {"mae_e_per_atom": 0.75},
+            {"mae_e_per_atom": 10.0},
             {"mae_e_per_atom": 0.25},
         ]
         config = deepcopy(self.config)
+        config["validating"]["full_validation"] = True
         config["validating"]["ema_full_validation"] = True
         trainer = get_trainer(config)
         trainer.run()
 
-        self.assertFalse(Path("val.log").exists())
+        self.assertTrue(Path("val.log").exists())
         self.assertTrue(Path("val_ema.log").exists())
         self.assertTrue(Path("best_ema.ckpt-4.t-1.pt").exists())
         self.assertFalse(Path("best_ema.ckpt-1.t-1.pt").exists())
@@ -1085,6 +1090,24 @@ def test_ema_full_validation_writes_separate_outputs(self, mocked_eval) -> None:
             [{"metric": 0.25, "step": 4}],
         )
 
+    @TRAINING_TEST_TIMEOUT
+    @patch("deepmd.pt.train.validation.FullValidator.evaluate_all_systems")
+    def test_ema_full_validation_ignored_without_full_validation(
+        self, mocked_eval
+    ) -> None:
+        config = deepcopy(self.config)
+        config["training"]["enable_ema"] = False
+        config["validating"]["full_validation"] = False
+        config["validating"]["ema_full_validation"] = True
+        trainer = get_trainer(config)
+        trainer.run()
+
+        mocked_eval.assert_not_called()
+        self.assertFalse(Path("val.log").exists())
+        self.assertFalse(Path("val_ema.log").exists())
+        self.assertIsNone(trainer.model_ema)
+        self.assertIsNone(trainer.ema_full_validator)
+
 
 if __name__ == "__main__":
     unittest.main()