Merge pull request #682 from CheukHinHoJerry/fix_dn_mh_ft

Fixing multihead finetuning with density normalization
ACEsuit · Nov 11, 2024 · abd7e5e · abd7e5e
2 parents c1184eb + 6da2377
commit abd7e5e
Showing 1 changed file with 16 additions and 2 deletions.
diff --git a/mace/tools/finetuning_utils.py b/mace/tools/finetuning_utils.py
@@ -75,7 +75,7 @@ def load_foundations_elements(
         )
         if (
             model.interactions[i].__class__.__name__
-            == "RealAgnosticResidualInteractionBlock"
+            in ["RealAgnosticResidualInteractionBlock", "RealAgnosticDensityResidualInteractionBlock"]
         ):
             model.interactions[i].skip_tp.weight = torch.nn.Parameter(
                 model_foundations.interactions[i]
@@ -101,7 +101,21 @@ def load_foundations_elements(
                 .clone()
                 / (num_species_foundations / num_species) ** 0.5
             )
-
+        if (
+            model.interactions[i].__class__.__name__
+            in ["RealAgnosticDensityInteractionBlock", "RealAgnosticDensityResidualInteractionBlock"]
+        ):
+            # Assuming only 1 layer in density_fn
+            getattr(model.interactions[i].density_fn, "layer0").weight = (
+                torch.nn.Parameter(
+                    getattr(
+                        model_foundations.interactions[i].density_fn,
+                        "layer0",
+                    )
+                    .weight
+                    .clone()
+                )
+            )
     # Transferring products
     for i in range(2):  # Assuming 2 products modules
         max_range = max_L + 1 if i == 0 else 1