diff --git a/deepmd/tf/descriptor/se_a_mask.py b/deepmd/tf/descriptor/se_a_mask.py
index b79e806fca..d9891cf0da 100644
--- a/deepmd/tf/descriptor/se_a_mask.py
+++ b/deepmd/tf/descriptor/se_a_mask.py
@@ -311,7 +311,7 @@ def build(
         aparam[:, :] is the real/virtual sign for each atom.
         """
         aparam = input_dict["aparam"]
-        with tf.variable_scope("fitting_attr" + suffix, reuse=reuse):
+        with tf.variable_scope("fitting_attr" + suffix, reuse=tf.AUTO_REUSE):
             t_aparam_nall = tf.constant(True, name="aparam_nall", dtype=tf.bool)
         self.mask = tf.cast(aparam, tf.int32)
         self.mask = tf.reshape(self.mask, [-1, natoms[1]])
diff --git a/deepmd/tf/fit/dos.py b/deepmd/tf/fit/dos.py
index 382d11f45e..928c8f5b32 100644
--- a/deepmd/tf/fit/dos.py
+++ b/deepmd/tf/fit/dos.py
@@ -439,7 +439,7 @@ def build(
             if self.aparam_inv_std is None:
                 self.aparam_inv_std = 1.0
 
-        with tf.variable_scope("fitting_attr" + suffix, reuse=reuse):
+        with tf.variable_scope("fitting_attr" + suffix, reuse=tf.AUTO_REUSE):
             t_dfparam = tf.constant(self.numb_fparam, name="dfparam", dtype=tf.int32)
             t_daparam = tf.constant(self.numb_aparam, name="daparam", dtype=tf.int32)
             t_numb_dos = tf.constant(self.numb_dos, name="numb_dos", dtype=tf.int32)
diff --git a/deepmd/tf/fit/ener.py b/deepmd/tf/fit/ener.py
index c2aef0610a..8e856bada4 100644
--- a/deepmd/tf/fit/ener.py
+++ b/deepmd/tf/fit/ener.py
@@ -537,7 +537,7 @@ def build(
             if "t_bias_atom_e" in nvnmd_cfg.weight.keys():
                 self.bias_atom_e = nvnmd_cfg.weight["t_bias_atom_e"]
 
-        with tf.variable_scope("fitting_attr" + suffix, reuse=reuse):
+        with tf.variable_scope("fitting_attr" + suffix, reuse=tf.AUTO_REUSE):
             t_dfparam = tf.constant(self.numb_fparam, name="dfparam", dtype=tf.int32)
             t_daparam = tf.constant(self.numb_aparam, name="daparam", dtype=tf.int32)
             self.t_bias_atom_e = tf.get_variable(