tf: add fparam/aparam support for finetune (#3313)

Fix #3256. Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu> (cherry picked from commit d629616)
deepmodeling · Apr 6, 2024 · 36a93f2 · 36a93f2
1 parent 0341466
commit 36a93f2
Showing 1 changed file with 16 additions and 1 deletion.
diff --git a/deepmd/fit/ener.py b/deepmd/fit/ener.py
@@ -850,7 +850,22 @@ def change_energy_bias(
                     box = test_data["box"][:numb_test]
                 else:
                     box = None
-                ret = dp.eval(coord, box, atype, mixed_type=mixed_type)
+                if dp.get_dim_fparam() > 0:
+                    fparam = test_data["fparam"][:numb_test]
+                else:
+                    fparam = None
+                if dp.get_dim_aparam() > 0:
+                    aparam = test_data["aparam"][:numb_test]
+                else:
+                    aparam = None
+                ret = dp.eval(
+                    coord,
+                    box,
+                    atype,
+                    mixed_type=mixed_type,
+                    fparam=fparam,
+                    aparam=aparam,
+                )
                 energy_predict.append(ret[0].reshape([numb_test, 1]))
         type_numbs = np.concatenate(type_numbs)
         energy_ground_truth = np.concatenate(energy_ground_truth)